The mission of the IEEE Women in Engineering Distinguished Lecturers Program (virtual) is to help enhance the professional knowledge and vitality of IEEE Women in Engineering members by apprising them of the latest industry trends, research results, and their practical applications. The Distinguished Lecturers Program highlights IEEE WIE’s partnership with the Societies/Council Program.
This program will allow IEEE WIE Affinity Groups to virtually invite the lecturers to speak at their events. IEEE WIE hopes that the wealth of knowledge these distinguished lecturers possess will help enrich WIE Affinity Group events and strengthen IEEE WIE’s endeavor to provide support to its members.
Find below a list of lecturers who have consented to offer their time and talent to virtually speak at IEEE WIE Affinity Groups’ meetings/seminars/panel discussions.
Distinguished Lecturers
Aerospace & Electronic Systems Society
Aerospace and Electronic Systems Society
Maria Sabrina Greco (R8)
Maria Sabrina Greco
Maria S. Greco graduated in Electronic Engineering in 1993 and received the Ph.D. degree in Telecommunication Engineering in 1998, from University of Pisa, Italy. From December 1997 to May 1998 she joined the Georgia Tech Research Institute, Atlanta, USA as a visiting research scholar where she carried on research activity in the field of radar detection in non-Gaussian background. In 1993 she joined the Department of Information Engineering of the University of Pisa, where she is Associate Professor since December 2011. She’s IEEE fellow since January 2011 and she was co-recipient of the 2001 IEEE Aerospace and Electronic Systems Society’s Barry Carlton Award for Best Paper and recipient of the 2008 Fred Nathanson Young Engineer of the Year award for contributions to signal processing, estimation, and detection theory. She’s IEEE SPS Distinguished Lecturer for the years 2014-15. She has been general-chair, technical chair and organizing committee member of many conferences (EUSIPCO2006, WDD2007, RadCon2008, CAMSAP2009, CIP2010, CAMSAP2011, SAM2014, ICASSP2014). She was guest co-editor of the special issue of the Journal of the IEEE Signal Processing Society on Special Topics in Signal Processing on “Adaptive Waveform Design for Agile Sensing and Communication,” published in June 2007 and s lead guest editor of the special issue of International Journal of Navigation and Observation on” Modelling and Processing of Radar Signals for Earth Observation published in August 2008. She’s Associate Editor of IET Proceedings – Sonar, Radar and Navigation since 2009, of the IEEE Transactions on Signal Processing (2009-2013), Associate Editor in Chief of the IEEE Aerospace and Electronic Systems Magazine since 2011, member of the Editorial Board of the Journal of Advances in Signal Processing (JASP) since 2008, member of the IEEE Signal Processing Theory and Methods (SPTM) and chair of the EDU Subcommittee (2009-2014), and member of the Signal Array Processing (SAM) Technical Committees (2010-2015). She’s also member of the IEEE AESS Radar Panel and of IEEE AESS Board of Governors (2012-2014). Her general interests are in the areas of statistical signal processing, estimation and detection theory. In particular, her research interests include radar clutter models, spectral analysis, coherent and incoherent detection in non-Gaussian clutter, CFAR techniques, radar waveform diversity and bistatic/multistatic radars. She co-authored three book chapters, more than 150 journal and conference papers.
Talk Topic:
1.Sea & Land Clutter Statistical Analysis & Modeling
2.Advanced Techniques of Radar Detection in Non-Gaussian Background
3.Cognitive Radar
Abstract:
1. The modeling of the clutter echoes is a central issue for the design and performance evaluation of radar systems. Main goal of this lecture is to describe the state-of-the-art approaches to the modeling and understanding of land and sea clutter echoes and their implications on performance prediction and signal processors design. The lecture first introduces radar sea and ground clutter phenomena, measurements and measurement limitations, at high and low resolution, high and low grazing angles with particular attention to classical model for RCS prediction. Most part of the lecture will be dedicated to modern statistical and spectral models for high resolution sea and ground clutter and to the methods of experimental validation using recorded data sets. Some comparison between monostatic and bistatic sea clutter data will be provided together with some results on non-stationarity analysis of the high-resolution sea clutter.
2. For several decades, the Gaussian assumption on the disturbance modeling in radar systems has been widely used to deal with detection problems. But, in modern high-resolution radar systems, the disturbance cannot be modelled as Gaussian distributed, and the classical detectors suffer from high losses. In this talk, after a brief description of modern statistical and spectral models for high-resolution clutter, coherent optimum and sub-optimum detectors, designed for such a background, will be presented and their performance analyzed against a non-Gaussian disturbance. Different interpretations of the various detectors are provided that highlight the relationships and the differences among them. After this first part, some discussion will be dedicated to how to make adaptive the detectors, by incorporating a proper estimate of the disturbance covariance matrix. Recent works on Maximum Likelihood and robust covariance matrix estimation have proposed different approaches such as the Approximate ML (or Fixed-Point) Estimator or the M-estimators. These techniques allow to improve the detection performance in terms of false alarm regulation and detection gain in SNR. Some of results with simulated and real recorded data will be shown.
3. Over the past fifteen years, “cognition” has emerged as an enabling technology for incorporating learning and adaptivity on both transmit and receive to optimize or make more robust the radar performance in dynamic environments. The term ‘cognitive radar’ was coined in 2006, but the foundations of the cognitive systems date back several decades to research on knowledge-aided signal processing, and adaptive radar design. The main element of cognitive radar systems is the ‘perception-action cycle’, that is the feedback mechanism between receiver and transmitter that allows the radar system to learn information about a target and its environment and adapt its transmissions so as to optimize one or more missions, according to a desired goal. But a truly cognitive radar should not be only able to adapt on the fly its transmission waveforms and parameters based on internal fixed rules and on what learned about the environment, but it should also be able to optimize these rules learning with time from its mistakes, as some biological system does. And this is still a big challenge for radar experts. This talk will provide an overview of the main concept, of methods for modeling cognitive processes in a radar system and of some application example. Some insights into future directions of research will be provided as concluding remarks.
Aerospace and Electronic Systems Society
Kathleen Kramer (R6)
Kathleen Kramer
Kathleen A. Kramer is a Professor of Electrical Engineering at the University of San Diego, San Diego, CA. She worked to develop new engineering programs as a founding member of the faculty and eventually became the chair of electrical engineering, and then serving as Director of Engineering (2004-2013), providing academic leadership for all of the university’s engineering programs. She has also been a Member of Technical Staff at several companies, including ViaSat, Hewlett Packard, and Bell Communications Research. She maintains an active research agenda and has recent publications in the areas of multisensor data fusion, evidence accrual, intelligent systems, and neural and fuzzy systems. Her teaching interests are in the areas of signal processing, mechatronics and robotics, and communication systems. She is a Fellow of ABET, and leader in the development of criteria for cyber security, mechatronics and robotics. She is served as AESS Cyber Security Technical Operations Panel Chair (2017-2022) and is a member of the AESS Avionics Technical Operations Panel. She served as the 2019-21 IEEE Secretary & Director, leading Governance across the IEEE. She received the B.S. degree in electrical engineering magna cum laude with a second major in physics from Loyola Marymount University, and the M.S. and Ph.D. degrees in electrical engineering from the California Institute of Technology.
Talk Topics:
1. Feature Object Extraction – Fusing Evidence, Not Rolling the Die
2.Navigation: The Road to GPS & Getting Beyond It
3.Navigation: Application Approaches and Advances from 4.GPS/GNSS, Vulnerabilities, Security and Opportunities
5.Evolving Cyber Systems in Avionics
Abstract:
1. Information assurance, also referred to as cyber security, is the process of protecting information from theft, destruction, or manipulation. Cyber threats, including for complex communications and navigation systems, can be either from internal or external sources, sudden or taking time to develop, such as a slow denial of service (DOS) attack. Some techniques have been developed to behave as sensors to quickly assess elements of attacks that rely on a decision engine to fuse the information to estimate whether or not an attack is underway. Interpreting cybersecurity as a sensor fusion problem, includes a number of additional alternative techniques into the solution space. The concept of evidence accrual is to gather measurements over time from different sensors to provide estimates of what event is occurring. A classification fusion technique using feature extraction and fuzzy logic known as Feature Object Extraction is developed and applied to problems such as cyber security and GPS attacks. The feature-aided object extraction technique was developed for the classification problem to fuse different features and generate both a classification and a measure of the quality of the classification estimate. Unlike most probabilistic techniques that increase the probability of one class by lowering the probability on other classes, the technique allow evidence to be applied to individual classes and recovery from erroneous negative information that traditionally would eliminate a possibility.
2. Navigation can be viewed as merely determining position or direction, but more commonly it relies on knowledge of position or direction to control or monitor movement from one place to another. In this talk, the field of navigation is introduced, including the evolution of techniques up through modern navigation dominated by electronic navigation including radio, radar, and satellite. The working of GPS, a navigation system based on a constellation of satellites in medium earth orbit that provides positioning information with global coverage is explained. Since its launch in 1978, it has been in ever wider use for finding and keeping track of just about anything: people, animals, boats, trucks, planes, and more. Its initial military uses have expanded far into civilian applications both for individuals and for large-scale commerce and transportation. The wide availability of first personal vehicle GPS navigation and later mobile phone-based navigation have changed how the world does business and how people and goods are moved around. As more and more vehicles and people rely upon it, any threats to GPS navigation become more dangerous. This is a result that more systems have become completely or primarily dependent on GPS for guidance and navigation. Simple jamming of the GPS can render a system completely blind to its location, while more sophisticated attacks can spoof a GPS signal to control its navigation. Future trends and technologies to address the security issue and to move forward in navigation are discussed.
3. Navigation can be viewed as merely determining position or direction, but more commonly it relies on knowledge of position or direction to control or monitor movement from one place to another. An overview of navigation foundations and approaches is provided, including the evolution of techniques up through modern navigation dominated by electronic navigation including radio, radar, and satellite. The working of global navigation satellite systems, such as GPS is considered. The utility and vulnerabilities these systems, with ever increasing reliance is discussed. The initial military uses of GPS to expansion far into civilian applications, and subsequent other GNSS are considered. The wide availability of first personal navigation has changed more than transportation, and with these applications, the potential vulnerabilities and risks. Security issues, future trends and technologies to address these, and the trends moving forward in navigation are discussed.
4. Avionics systems are part of a formerly slow-changing industry and that have emerged as cyber-physical systems, in an air and space transport system context, where practical implementation is complex, multi-agent, and safety critical. Autonomy advancements technically rely on separation assurance and collision avoidance for multi-agent systems. Vision based advancements in navigation address difficult problems, with major implementation challenges. Efforts to advance traffic management for emerging systems, face important challenges particularly to involve UAS and to approach low earth orbit systems. Artificial intelligence techniques promise new solutions, particularly where autonomy of functions are needed, but are particularly challenged by the priority on certification for safety.
Aerospace and Electronic Systems Society
Jian Li (R3)
Jian Li
Dr. Jian Li received the M.Sc. and Ph.D. degrees in electrical engineering from The Ohio State University, Columbus, in 1987 and 1991, respectively. She is currently a Professor in the Department of Electrical and Computer Engineering, University of Florida, Gainesville. Her current research interests include spectral estimation, statistical and array signal processing, and their applications to radar, sonar, and biomedical engineering.
Dr. Li’s publications include Robust Adaptive Beamforming (2005, Wiley), Spectral Analysis: the Missing Data Case (2005, Morgan & Claypool), MIMO Radar Signal Processing (2009, Wiley), and Waveform Design for Active Sensing Systems — A Computational Approach (2011, Cambridge University Press).
Dr. Li is a Fellow of IEEE and a Fellow of IET. She is a Fellow of the European Academy of Sciences (Brussels). She is a co-author of the paper that has received the M. Barry Carlton Award for the that has received the Best Paper Award in 2013 from the IEEE Signal Processing Society best paper published in IEEE Transactions on Aerospace and Electronic Systems in 2005. She is also a co-author of a paper published in IEEE Transactions on Signal processing.
Talk Topic:
1. Over a Century of Array Signal Processing
2. Automotive MIMO Radar
Abstract:
1. Since the introduction of phased array in 1905 by Karl Braun, a Nobel Laureate, array signal processing has advanced significantly over the past century. The era of adaptive array was started by Jack Capon, signified by his seminal paper in 1969. The Capon beamformer has better resolution and much better interference rejection capability than the data-independent beamformer by Karl Braun, provided that the array steering vector corresponding to the signal of interest (SOI) and the array covariance matrix is accurately known, and the SOI is uncorrelated to all other signals impinging on the array. However, whenever the knowledge of the SOI steering vector is imprecise, the number of data snapshots is scarce, or the SOI is correlated with a multipath, which are often the cases encountered in practice, the performance of the Capon beamformer may become worse than that of the data-independent beamformer. For over 50 years, making the Capon beamformer robust has attracted much interest and tens of thousands of papers on robust adaptive array processing have been published in the literature. To fundamentally overcome the limitations of the Capon family of beamformers, iterative approaches have been introduced in the recent literature. Most notably, the iterative adaptive approach (IAA) was published in 2010 and is shown to possess strong robustness, and can work well under single snapshot and arbitrary array scenarios. We will compare the non-parametric and user parameter free IAA algorithm with other well-known algorithms, including the data-independent beamformer, the Capon beamformer, the OMP algorithm introduced in the compressed sensing literature, as well as the parametric MUSIC and ESPRIT algorithms.
2. Almost all new and future vehicles are equipped with MIMO radar for enhanced safety and for various autonomous driving levels. The challenges, such as mutual interferences, of automotive MIMO radar will be discussed. Possible promising research directions, ranging from probing sequence syntheses to receiver filter designs, will be provided.
Circuits & Systems Society
Circuits and Systems Society
Alysaa Apsel (R1)
Alysaa Apsel
Alyssa Apsel received the B.S. from Swarthmore College in 1995 and the Ph.D. from Johns Hopkins University, Baltimore, MD, in 2002. She joined Cornell University in 2002, where she is currently Director of Electrical and Computer Engineering and the IBM Professor of Engineering. Her current research is on the leading edge of ultra-low power and flexible RF interfaces for IoT. Her group has pioneered the use of coupled oscillators for network synchronization of mesh networks and a variety of techniques for flexible RF systems. She has authored or coauthored over 100 refereed publications including one book in related fields of RF mixed signal circuit design, ultra-low power radio, interconnect design and planning, photonic integration, and process invariant circuit design techniques resulting in ten patents. She has received a number of best paper awards and the National Science Foundation CAREER Award in addition to being selected by Technology Review Magazine as one of the Top Young Innovators in 2004. More recently Professor Apsel served as a Distinguished Lecturer for IEEE CAS from 2018-2019 and was named an IEEE Fellow.
Talk Topic:
- Ubiquitous, Seamless, and Future Proofed: How Wireless Circuits Can Push IoT
Abstract:
In 2021 the number of IoT devices reached 46 billion, a 200% increase over the number in 2016*. By 2030 this number is expected to jump to 125 billion. While the FCC and other regulators have added licensed and unlicensed spectrum across several bands over the past few years to accommodate these new users, the need for increased wireless capacity and radios that can quickly adapt to new standards remains. Needless to say, the RF circuit designer has a significant role to play in solving these problems. As the market continues to grow, regulating bodies in various countries will undoubtedly continue to work to free up and reallocate spectrum and users will continue to find more ways to use that spectrum. Users will need both short reach and low power IoT devices that can operate independently and share spectrum as well as new WiFi and cellular radios that can quickly adapt to new environments and standards. In this talk I will look at several unconventional approaches to making radios flexible. I will examine how to add flexibility to the RF front end itself to accommodate changing standards and environments while keeping design and circuit costs low. I will show techniques for both broadband and tunable narrowband systems that can enable flexibility while maintaining high performance. Finally, I will look at an approach from the network side, of how to use a hardware support to build functional low power networks that can communicate point to point in a scalable fashion. Using such radios can reduce communication bottlenecks in centralized systems as well as enable more devices and sensors with greater flexibility. With these examples I will discuss the potential for future flexible analog RF designs and the current limits of this approach.
Circuits and Systems Society
Milin Zhang (R10)
Milin Zhang
Milin Zhang is an associate professor in the Department of Electronic Engineering at Tsinghua University. She received her B.S. and M.S. degrees in electronic engineering from Tsinghua University, Beijing, China, in 2004 and 2006, respectively, and her Ph.D. degree in the Electronic and Computer Engineering Department, Hong Kong University of Science and Technology (HKUST), Hong Kong. After finishing her doctoral studies, she worked as a postdoctoral researcher at the University of Pennsylvania (U Penn). She joined Tsinghua University in 2016. Her research interests include designing of various non-traditional imaging sensors and biomedical sensing circuit, system design and applications. She serves and has served as the TPC member of ISSCC, CASS, CICC, A-SSCC and Bio CAS. She is the Chapter chair of the SSCS Beijing chapter. She is the Distinguished Lecture of CASS. She has received the Best Paper Award of the Bio CAS Track of the 2014 International Symposium on Circuits and Systems (ISCAS), the Best Paper Award (1st place) of the 2015 Biomedical Circuits and Systems Conference (Bio CAS), the best student paper award (2nd place) of ISCAS 2017.
Talk Topics:
1. Low Power, Low Noise Analog-Front-End for Biomedical Signal Acquisition
2. Low Power, High Efficiency Transmitter for Wireless Biomedical Recorder
Abstract:
Low noise amplifiers are one of the most significant modules in the design of a bio-signal sensor interface. An AFE features input- referred noise (IRN) as low as to μV level is required to fit the requirement of a high precision acquisition. In addition, the performance of low-power consumption is also expected to extend the battery life, as well as to reduce self-heating of the implanted device for safety. This seminar will focus on the design of a low-noise, low total harmonic distortion (THD) chopper amplifier. It will first cover an introduction on different types of the AFEs. The trade-off between the noise and power will be outlined, which is typically quantitatively measured in terms of noise-efficiency factor. System implementation and applications will also be discussed.
Circuits and Systems Society
Xuan “Silvia” Zhang (R5)
Xuan Silvia Zhang
Dr. Xuan ‘Silvia’ Zhang is an Associate Professor in the Preston M. Green Department of Electrical and Systems Engineering at Washington University in St. Louis. She works across the fields of integrated circuits/VLSI design, computer architecture, and electronic design automation. Dr. Zhang is an IEEE Circuits and Systems Society (CAS) Distinguished Lecturer for 2022-2023, the winner of IEEE St. Louis Section Outstanding Researcher and Outstanding Women in Engineering in 2022, and the recipient of NSF CAREER Award in 2020. She receives ISLPED Best Paper Award in 2022, AsianHOST Best Paper Award in 2020, DATE Best Paper Award in 2019, and ISLPED Design Contest Award in 2013. Her work has also been nominated for Best Paper Awards at DAC 2022, ASP-DAC 2021, MLCAD 2020, DATE 2019, and DAC 2017.
Talk Topic:
- In-Sensor AI Computing for Efficient Real-Time Machine Perception
Abstract:
Artificial intelligence (AI) and machine learning (ML) technologies have fueled many burgeoning applications from on-device learning and personalized recommendations to self-driving cars and collaborative robots. Despite these unprecedented advancements, the holy grail of enabling fully autonomous machine intelligence remains far from our grasp. One key challenge is the lack of performant and efficient hardware implementation, especially in the case of embedded/edge devices with rich sensory inputs yet stringent resource constraints. In this talk, I will present our work to tackle this challenge from a unique angle that leverages brain/neuro-inspired techniques beyond the conventional binary digital abstractions. Specifically, we leverage information processing ability innate in the analog/mixed-signal (AMS) domain and exploit co-located compute and memory organization. I will introduce how our method transforms in-sensor visual computing by embedding AI computation directly inside the pixel circuits, delivering much-improved performance and efficiency. I envision the future sensor-rich intelligent devices will be powered by distinctive yet complementary computing paradigms as an enabling technology for experiential and embodied AI and internet of connected edge intelligence.
Communications Society
Communications Society
Sinem Coleri (R8)
Sinem Coleri
Sinem Coleri is a Professor and the Chair of the Department of Electrical and Electronics Engineering at Koc University. She is also the founding director of Wireless Networks Laboratory (WNL) and director of Ford Otosan Automotive Technologies Laboratory. Sinem Coleri received the BS degree in electrical and electronics engineering from Bilkent University in 2000, the M.S. and Ph.D. degrees in electrical engineering and computer sciences from University of California Berkeley in 2002 and 2005. She worked as a research scientist in Wireless Sensor Networks Berkeley Lab under sponsorship of Pirelli and Telecom Italia from 2006 to 2009. Since September 2009, she has been a faculty member in the department of Electrical and Electronics Engineering at Koc University. Her research interests are in 6G wireless communications and networking, machine learning for wireless networks, machine-to-machine communications, wireless networked control systems and vehicular networks. Dr. Coleri has more than 150 publications with citations over 10180 (Google scholar profile). She has received numerous awards and recognitions, including N2Women: Stars in Computer Networking and Communications in 2022; TUBITAK (The Scientific and Technological Research Council of Turkey) Incentive Award and IEEE Vehicular Technology Society Neal Shepherd Memorial Best Propagation Paper Award in 2020. Dr. Coleri has been Interim Editor-in-Chief of IEEE Open Journal of the Communications Society since 2023, Executive Editor of IEEE Communications Letters since 2023, Editor-at-Large of IEEE Transactions on Communications since 2023, Senior Editor of IEEE Access since 2022, Editor of IEEE Transactions on Vehicular Technology since 2016 and Editor of IEEE Transactions on Machine Learning in Communications and Networking since 2022. Dr. Coleri is an IEEE Fellow and IEEE ComSoc Distinguished Lecturer.
Talk Topic:
- AI Based Ultra-Reliable Wireless Networked Control Systems in 6G
Abstract:
Unlike previous generation networks that were mainly designed to meet the requirements of human-type communications, 5G networks enable the collection of data from the machines with the total number of devices expected to be around 26 billion in 2026 according to Ericsson Mobility Report. The next step in 6G systems is to enable a new spectrum of control applications based on these data, such as extended reality, remote surgery, autonomous vehicle platoons. The design of communication systems for control applications requires meeting the strict delay and reliability requirements of communication systems, addressing the semantics of the control systems and achieving robustness in resource management. In the first part of this talk, ultra-reliable channel modeling and communication techniques are presented for the joint design of control and communication systems based on extreme value theory and artificial intelligence (AI). AI enables predicting the channel parameters with higher accuracy while incorporating various system inputs and providing adaptivity to time-varying scenarios at high frequency bands, including THz, optical and mmwave communication. In the second part of the talk, the importance and means of achieving explainability and robustness are presented for AI based radio resource management in 6G networks. The usage of explainable and robust AI techniques for feature attribution, model simplification, model compression and sensitivity analysis in radio resource management is demonstrated.
Communications Society
Michele Nogueira (R9)
Michele Nogueira
Dr. Nogueira is an Associate Professor in the Computer Science Department at the Federal University of Minas Gerais (UFMG), Brazil. She received her doctorate in Computer Science from the University Pierre et Marie Curie – Sorbonne Université, France. She was on sabbatical leave at Carnegie Mellon University, USA (2016-2017). Her research interests include wireless networks, cybersecurity, and network resilience. She has worked on providing resilience to self-organized, cognitive, and wireless networks through adaptive and opportunistic approaches. Dr. Nogueira was one of the pioneers in addressing survivability issues in self-organized wireless networks, and the work “A Survey of Survivability in Mobile Ad Hoc Networks” is one of her prominent scientific contributions. She has received Academic Scholarships from the Brazilian Government in her undergraduate and graduate years and international grants such as the ACM SIGCOMM Geodiversity program. She has served as Associate Technical Editor for the IEEE Communications Magazine and the IEEE ComSoc Internet Technical Committee chair. She is an ACM and IEEE Senior Member.
Talk Topic:
- Data Science for Cybersecurity: An Overview Focused on Networking
Abstract:
Cyberattacks are constantly ravaging valuable data, wasting time and costly resources, and negatively affecting the reputation of companies and institutions worldwide. Big, high-profile organizations have suffered the consequences of cyberattacks with a high impact on the organizations themselves, their customers, collaborators, and society. WannaCry and other ransomware software are still a threat that affects computers, encrypting data and demanding ransom payments in Bitcoin cryptocurrency. Another example is sophisticated versions of Distributed Denial-of-Service attacks (DDoS attacks), launched from Internet-connected devices — such as IP cameras, residential gateways, and baby monitors, cause major Internet platforms and services to be unavailable to many users worldwide. These examples highlight the power and potential of cyberattacks, revealing a constant improvement and sophistication in attacking strategies. Cybersecurity is no longer what it used to be; we are in the era of ubiquitous systems, and we expect more than 75 billion devices or smart things to be connected by 2025. We observe the design of different solutions to tackle this problem, for instance, digital passports for seamless entry at Dubai Airport, supported by blockchain technology, expecting it to stand as proof of all the transactions on the network. However, how is academia addressing the sophistication of cyberattacks? Can we anticipate the next moves of attackers to protect our information assets? How could academia benefit from the data generated in the network to create security intelligence and prevent attacks? This talk intends to elicit a discussion around these questions and present an overview of correlated research developed by Dr. Nogueira’s research team and future directions in these topics.
Communications Society
Damla Turgut (R3)
Damla Turgut
Dr. Turgut is Charles Millican Professor of Computer Science at the University of Central Florida (UCF). She is the co-director of the AI Things Laboratory. She held visiting researcher positions at the University of Rome “La Sapienza”, Imperial College of London, and KTH Royal Institute of Technology, Sweden. Her research interests include wireless ad hoc, sensor, underwater, vehicular, and social networks, edge/cloud computing, smart cities, smart grids, IoT-enabled healthcare and augmented reality, as well as considerations of privacy in the Internet of Things. Dr. Turgut serves on several editorial boards and program committees of prestigious ACM and IEEE journals and conferences. Her most recent honors include the NCWIT 2021 Mentoring Award for Undergraduate Research (MAUR), the UCF Research Incentive Award, and the UCF Women of Distinction Award. Since 2019, she serves as the N2Women Board Co-Chair where she co-leads the activities of the N2Women Board in supporting female researchers in the fields of networking and communications. She is an IEEE ComSoc Distinguished Lecturer, IEEE Senior Member, and the Chair-Elect of the IEEE Technical Committee on Computer Communications (TCCC).
Talk Topic:
- Physical and computational modeling of smart homes
Abstract:
Novel “smart” technologies such as smart homes, smart grids, variable pricing, and local energy markets promise both better overall efficiency for the providers, a greener home, and lower prices. However, they also create unexpected problems. During the February 2021 North-American Ice Storm, the deregulated energy market in Texas came dangerously close to collapse, leading to rolling brownouts and loss of service in many homes that relied on electric power for heating. As a response, the variable pricing system shot up to $5000 per kilowatt hour, generating very high bills for customers who did not lose service. This behavior penalized customers but did nothing to help in the ongoing crisis. Although it did not happen on this occasion, a controller that would sell the home’s energy reserves to take advantage of the high pricing would be even more dangerous for customers facing freezing temperatures. The lesson we can learn from these events is that “smart” systems must be extensively tested, including for black swan events for which no previous data is available. In this talk, we discuss the need for extensive modeling and simulation for all the components of such homes, including the physical environment, the smart controllers, the behavior of the humans, and the external environment, including the smart grids and local energy market to which the systems connect.
Control Systems Society
Control Systems Society
Maria Domenica Di Benedetto (R8)
Maria Domenica Di Benedetto
Maria Domenica Di Benedetto is a Professor of Automatic Control at University of L’Aquila (Italy). She received her Master degree in Electrical Engineering and Computer Science from University of Roma “La Sapienza” and holds the PhD degree (“Docteur-Ingenieur” Spécialité Automatique et Traitement du Signal) and the degree “Doctorat d’Etat ès Sciences” (Spécialité Sciences Physiques), both from Université de Paris-Sud (Orsay, France). She has been Adjunct Professor from 1995 to 2002, and McKay Professor from 1990 to 1995, at the Department of EECS of the University of California at Berkeley. She held visiting positions at MIT, at the University of Michigan Ann Arbor, and at the Ecole Nationale Supérieure de Mécanique in Nantes (France). Her research interests are in the areas of nonlinear and hybrid systems control theory, diagnosability and predictability in cyber-physical systems, and applications to traffic control, smart grids and biological systems. From 2001 to 2019, Prof. Di Benedetto has been the Director of the Italian Center of Excellence for Research DEWS “Architectures and Design methodologies for Embedded controllers, Wireless interconnect and System-on-Chip” established at the University of L’Aquila in 2001. She has been the President of the Italian Association of Researchers in Automatic Control (SIDRA) from 2013 to 2019. She is the President of the European Embedded Control Institute since 2009. Dr. Di Benedetto is a Fellow of the IEEE and IFAC. She has been a member of the IEEE Control Systems Technical Fields Award Committee, Chair of the Standing Committee on Fellow Nominations of the IEEE CSS, member of the IEEE Fellow Evaluation Committee of the IEEE CSS. She is the IFAC Chair of the Nathaniel B. Nichols Medal Selection Committee for the 2020-2023 triennium. She is currently a Distinguished Lecturer of the IEEE CSS and is serving as the VP for Membership Activities (2020-21) in the Executive Committee of the IEEE CSS. She is Editor of the IEEE Press Book Series in Control Systems Theory and Applications.
Talk Topic:
- Diagnosability of hybrid dynamical systems
Abstract:
Hybrid systems, i.e., heterogeneous systems that include discrete and continuous-time subsystems, have been used to model control applications e.g. in automotive control, air traffic management systems, smart grids and intelligent manufacturing. Failure in this kind of applications can cause irreparable damage to the physical controlled systems and to the people who depend on it, or may cause large direct and indirect economic losses. Therefore, security for hybrid systems represent a significant concern. In this respect, observability and diagnosability play an important role since they are essential in characterizing the possibility of identifying the system’s hybrid state, and in particular, the occurrence of specific states that may correspond to malfunctioning due to a fault or an adversarial attack. In this talk, I review and place in context how the continuous and the discrete dynamics, as well as their interactions, intervene in the observability and diagnosability properties of a general class of hybrid systems. I also illustrate under which conditions the hybrid system’s state can be correctly estimated even when the system is under attack. An example related to network topology changes due to faults or attacks will illustrate the results.
Control Systems Society
Emilia Fridman (R8)
Emilia Fridman
Emilia Fridman received the M.Sc. degree from Kuibyshev State University, USSR, in 1981 and the Ph.D. degree from Voronezh State University, USSR, in 1986, all in mathematics. From 1986 to 1992 she was an Assistant and Associate Professor in the Department of Mathematics at Kuibyshev Institute of Railway Engineers, USSR. Since 1993 she has been at Tel Aviv University, where she is currently Professor of Electrical Engineering-Systems. She has held visiting positions at the Weierstrass Institute for Applied Analysis and Stochastics in Berlin (Germany), INRIA in Rocquencourt (France), Ecole Centrale de Lille (France), Valenciennes University (France), Leicester University (UK), Kent University (UK), CINVESTAV (Mexico), Zhejiang University (China), St. Petersburg IPM (Russia), Melbourne University (Australia), Supelec (France), KTH (Sweden). Her research interests include time-delay systems, networked control systems, distributed parameter systems, robust control, singular perturbations and nonlinear control. She has published two monographs and more than 200 articles in international scientific journals. She serves/served as Associate Editor in Automatica, SIAM Journal on Control and Optimization and IMA Journal of Mathematical Control and Information. In 2014 she was Nominated as a Highly Cited Researcher by Thomson ISI. Since 2018, she has been the incumbent for Chana and Heinrich Manderman Chair on System Control at Tel Aviv University. She is IEEE Fellow since 2019. In 2021 she was recipient of IFAC Delay Systems Life Time Achievement Award and of Kadar Award for outstanding research in Tel Aviv University. She is currently a member of the IFAC Council.
Talk Topic:
- Using Delays for Control
- Constructive Methods for Robust Control of Distributed Parameter Systems
Abstract:
1. In this talk by “using delays” I understand either Time-Delay Approaches to control problems (that originally may be free of delays) or intentional inserting delays to the feedback. I will start with an old Time-Delay approach – to sampled-data control. In application to network-based control with communication constraints, this is the only approach that allows treating transmission delays larger than the sampling intervals. I will continue with “using artificial delays” via simple Lyapunov functionals that lead to feasible LMIs for small delays and to simple sampled-data implementation. Finally I will present a New Time-Delay approach – this time to Averaging. The existing results on averaging (that have been developed for about 60 years starting from the works of Bogoliubov and Mitropolsky) are qualitative: the original system is stable for small enough values of the parameter if the averaged system is stable. Our approach provides the first quantitative bounds on the small parameter making averaging-based control (including vibrational and extremum seeking control) reliable.
2. Many important plants (e.g. flexible manipulators or heat transfer processes) are governed by partial differential equations (PDEs) and are often described by models with a significant degree of uncertainty. Some PDEs may not be robust with respect to arbitrary small time-delays in the feedback. Robust finite-dimensional controller design for PDEs is a challenging problem. In this talk two constructive methods for finite-dimensional control will be presented: Spatial decomposition (or sampling in space) method, where the spatial domain is divided into N subdomains with N sensors and actuators located in each subdomain; Modal decomposition method, where the controller is designed on the basis of a finite-dimensional system that captures the dominant dynamics of the infinite-dimensional one. Sufficient conditions ensuring the stability and performance of the closed-loop system are established in terms of simple linear matrix inequalities that are always feasible for appropriate choice of controllers. We will discuss delayed and sampled-data implementations as well as application to network-based deployment of multi-agents.
Control Systems Society
Sandra Hirche (R8)
Sandra Hirche
Sandra Hirche holds the TUM Liesel Beckmann Distinguished Professorship and heads the Chair of Information-oriented Control in the Faculty of Electrical and Computer Engineering at Technical University of Munich (TUM), Germany (since 2013). She received the diploma engineer degree in Aeronautical and Aerospace Engineering in 2002 from the Technical University Berlin, Germany, and the Doctor of Engineering degree in Electrical and Computer Engineering in 2005 from the Technische Universität München, Munich, Germany. From 2005 – 2007 she has been a Post Doc Fellow of the Japanese Society for the Promotion of Science at the Fujita Laboratory at Tokyo Institute of Technology, Japan. Prior to her present appointment she has been an Associate Professor at TUM. Her main research interests include learning, cooperative, and networked control with applications in human-robot interaction, multi-robot systems, and general robotics. She has published more than 200 papers in international journals, books and refereed conferences. She has received multiple awards such as the Rohde & Schwarz Award for her PhD thesis, the IFAC World Congress Best Poster Award in 2005 and – together with students – Best Paper Awards of IEEE Worldhaptics and IFAC Conference of Maneuvering and Control of Marine Craft in 2009 and the Outstanding Student Paper Award of the IEEE Conference on Decision and Control 2018. In 2013 she has been awarded with an ERC Starting Grant on the “Control based on Human Models” and in 2019 with the ERC Consolidator Grant on “Safe data-driven control for human-centric systems”. Sandra Hirche is Fellow of the IEEE and received the IEEE Control System Society Distinguished Member Award. She has served as IEEE Control System Society (CSS) Vice-President for Member Activities (2014/15), as Chair for Student Activities in the IEEE CSS (2009-2014), as Chair of the CSS Awards Subcommittee on “CDC Best Student-Paper Award” (2010-2014), and has been elected member of the Board of Governors of IEEE CSS (2010-2013). She has been Co-Chair of the IFAC TC 1.5 “Networked Control Systems” (2010-2017).
Talk Topic:
- Online Learning Control for Personalized Robotic Rehabilitation and Assistance 2. High Performance control for Robots in Extreme Environments 3. “To Sample or not to Sample?” – Efficient Online Learning in Closed Loop Control Systems with Guarantees
Abstract:
One of the central societal challenges is to prolong independent living for elderly and promote well. Personalized robotic rehabilitation and assistance is considered one of the enabling technologies with control design playing a significant role. Focusing on sensorimotor rehabilitation and assistance, personalized control should be able to adapt to the high inter-personal variability in human motor behavior but also to intra-personal changes over time. Control adaptation is further challenged by the sparsity of person-specific data because calibration routines need to be brief for user acceptance. Above all, guaranteed safety is one of the key requirements. In this talk we will present recent results on learning-based control with performance and safety guarantees for highly uncertain systems with particular focus on challenges arising from personalized rehabilitation and assistance. In order to achieve high sample efficiency as well as transparency of the system, available knowledge of dynamic models will be exploited and and augmented by Bayesian non-parametric model components. Epistemic uncertainty due to limited training data will explicitly be taken into account in the control design in order to achieve uncertainty-aware behavior of the closed loop system. Online learning as well as realtime capabilities are further important aspects discussed in this talk. The results will be demonstrated in user intention-driven shared control designs for upper limb rehabilitation and assistance with exoskeletons.
2. One of the central societal challenges is to prolong independent living for elderly and promote well. Personalized robotic rehabilitation and assistance is considered one of the enabling technologies with control design playing a significant role. Focusing on sensorimotor rehabilitation and assistance, personalized control should be able to adapt to the high inter-personal variability in human motor behavior but also to intra-personal changes over time. Control adaptation is further challenged by the sparsity of person-specific data because calibration routines need to be brief for user acceptance. Above all, guaranteed safety is one of the key requirements. In this talk we will present recent results on learning-based control with performance and safety guarantees for highly uncertain systems with particular focus on challenges arising from personalized rehabilitation and assistance. In order to achieve high sample efficiency as well as transparency of the system, available knowledge of dynamic models will be exploited and and augmented by Bayesian non-parametric model components. Epistemic uncertainty due to limited training data will explicitly be taken into account in the control design in order to achieve uncertainty-aware behavior of the closed loop system. Online learning as well as real time capabilities are further important aspects discussed in this talk. The results will be demonstrated in user intention-driven shared control designs for upper limb rehabilitation and assistance with exoskeletons.
3. Online learning in closed loop control systems is very attractive because it allows the automated identification of highly nonlinear dynamical systems as well as a fast adaptation to dynamically changing environments. Yet, depending on the application the data collection and the training of models is costly if not even prohibitive. On the one hand, the training is computationally expensive and might compromise real-time performance. In particular in non-parametric learning approaches as e.g. in Gaussian Processes, the computational tractability is tied to the number of training data. As such it is important to understand how informative training samples are and further how to improve algorithmic efficiency of training and prediction. In this talk we will demonstrate that the control task in addition to the underlying system dynamics has a strong influence on the required sample complexity. Employing Bayesian principles, we explore methods to quantify epistemic uncertainty with respect to control objectives and how they can be exploited to achieve a high sample efficiency for learning in the closed loop system. Additionally, approaches for efficient non-parametric online learning algorithms are proposed to allow the application of the presented methods under real-time constraints.
Control Systems Society
Jing Sun (R4)
Jing Sun
Jing Sun received her Ph. D degree from the University of Southern California in 1989 and her master’s and bachelor degrees from the University of Science and Technology of China in 1984 and 1982. From 1989-1993, she was an assistant professor in the Electrical and Computer Engineering Department at Wayne State University. She joined Ford Research Laboratory in 1993, where she worked on advanced powertrain system controls. After spending almost ten years in the industry, she came back to academia in 2003 and joined the University of Michigan, where she is the Michael G. Parsons Collegiate Professor and the chair in the Naval Architecture and Marine Engineering Department. She holds joint appointments in the Electrical Engineering and Computer Science Department and Mechanical Engineering Department at the same university. She holds 41 US patents and has published over 250 archived journal and conference papers. She is a Fellow of NAI (the National Academy of Inventors), IEEE, IFAC, and SNAME (the Society of Naval Architecture and Marine Engineering). She is one of the three recipients of the 2003 IEEE Control System Technology Award.
Talk Topic:
- Real-time Energy Management and Optimization for Electrified Vehicles and Ships 2. A Multi-scale Optimization Framework for Integrated Power and Thermal Management
Abstract:
1. Integrated power systems (IPS) incorporate heterogeneous power sources, including energy storage systems, to achieve improved energy efficiency and reliability. They have been a critical enabling technology for vehicle electrification. One distinctive characteristic of IPS is the highly interactive and dynamic nature, due to tight physical couplings of the multiple components involved. To achieve high efficiency, one often exploits their operating profiles and pushes these systems to operate on or close to their admissible boundary, thereby calling for predictive control. In this lecture, we will explore the unique characteristics of the IPS and discuss the challenges and solutions of real-time optimization and predictive control applied to this particular class of systems. Several examples, including the IPS for all-electric ships and the integrated solid oxide fuel cell and gas turbine (SOFC/GT) system, will be used to provide motivations and illustrate the impact of solutions.
2. Integrated power systems (IPS) incorporate heterogeneous power sources, including energy storage systems, to achieve improved energy efficiency and reliability. They have been a critical enabling technology for vehicle electrification. One distinctive characteristic of IPS is the highly interactive and dynamic nature, due to tight physical couplings of the multiple components involved. To achieve high efficiency, one often exploits their operating profiles and pushes these systems to operate on or close to their admissible boundary, thereby calling for predictive control. In this lecture, we will explore the unique characteristics of the IPS and discuss the challenges and solutions of real-time optimization and predictive control applied to this particular class of systems. Several examples, including the IPS for all-electric ships and the integrated solid oxide fuel cell and gas turbine (SOFC/GT) system, will be used to provide motivations and illustrate the impact of solutions.
Electron Devices Society
Electron Devices Society
Mukta Farooq (R1)
Mukta farooq
Dr. Mukta Farooq is a metallurgist and materials scientist, with expertise in 3-Dimensional and Heterogeneous Integration and Packaging, die and wafer level stacking, CMOS FET back end of line structures, flip-chip/C4/Cu pillar technology, lead-free alloys, chip package interaction, and intellectual property development. Mukta is currently the Heterogeneous Integration Leader for the AI Hardware Center at IBM Research. She has over 208 issued patents, and was named an IBM Lifetime Master Inventor and a member of the IBM Academy of Technology. She has received an outstanding technical achievement award for leadership in 3D Integration, and multiple high value patent awards. She has authored several external publications, given invited talks, and taught short courses. Mukta is an IEEE Fellow, a Distinguished Alumna of IIT Bombay, an EDS Distinguished Lecturer, Chair of the IEEE EDS Mid-Hudson Valley Chapter, and an active contributor to Women in Engineering. Mukta received her BS from IIT Bombay, MS from Northwestern University, and PhD from Rensselaer Polytechnic Institute.
Talk Topic:
- 3D Technology Overview, 3D Integration and Die Stacking
Abstract:
While silicon scaling has reached astonishing levels over the last half century, there has not been a corresponding level of scaling in electronic packaging technology. What is the reason behind these divergent evolutionary paths? And why is that we are now starting to see changes? More specifically, what is driving this shift from classical packaging to Heterogeneous Integration, and why has it become the mantra for High Performance Computing? This seminar will discuss these questions with a view to shedding light on the reasons behind the paradigm shifts, and the methods by which these are achieved. We will also review the essence of TSV (Through Silicon Via) and 3D process technology, which are critical elements of Heterogeneous Integration.
Electron Devices Society
Merlyne De Souza (R8)
Merlyne De Souza
Maria Merlyne De Souza received her PhD from the University of Cambridge. She became Professor of Electronics and Materials at the Emerging Technologies Research Centre, De Montfort University in 2003 and Professor of Microelectronics at the University of Sheffield in 2007. She has been a technical and executive committee member of IEEE- IEDM between 2012-2017 and IRPS 2003-2013 and is technical co-chair of ESSDERC/ESSCIRC ‘23. She has published over 110 journal papers and 180 conferences.
Talk Topic:
- Negative Capacitance beyond Ferroelectric FETs
Abstract:
This talk will discuss present-day challenges facing scaling of the MOSFET, leading to the concept of negative capacitance. We will showcase the phenomenon of negative capacitance beyond ferroelectric materials. The benefits in memory applications present opportunities for highly energy efficient neuromorphic computing systems of the future.
Electron Devices Society
Pei Wen Li (R1)
Pei Wen Li
Pei Wen Li (Senior Member, IEEE) received her Ph.D. degree in electrical engineering from Columbia University in New York City in 1994. Since 2015, she is a Professor in the Institute of Electronics at National Chiao Tung University (NCTU) (as National Yang Ming Chiao Tung University (NYCU) in 2021). Prior to joining NCTU in 2015, she was a Distinguished Professor, Chair of Electrical Engineering Department, and Director of Nano Science and Technology at National Central University. She was a Research Visiting Scholar at Caltech in 2011−2012. She worked with Vanguard International Semiconductor Corporation on DRAM technology integration in 1995- 1996. Her research themes focus on experimental germanium nanostructures and devices, encompassing quantum-dot single-electron transistors, photodetectors, light emitters, and thermoelectric devices, making use of self-assembly nanostructures in silicon integration
technology. She has published more than 300 technical journal and conference papers and holds 8 patents.
Dr. Li is an IEEE Distinguished Lecturer and has served on the VLSI Technology and Education committees of IEEE Electron Devices Society. She has been an editor of IEEE Journal of Electron Device Society since 2022 and an editorial board member of Applied Physics A, Springer since 2020. She is a senior member of the IEEE Electron Device Society and serves on various IEEE conference committees (Silicon Nanoelectronics Workshop (SNW) and Electron Devices Technology and Manufacturing (EDTM) Conference).
Talk Topics:
The Wonderful World of Designer Germanium Quantum-Dot Transistors
Abstract:
Since the inception of the first transistors in the 1940s, the enormous investment and immense body of research on Group IV semiconductors, including silicon (Si) and germanium (Ge), have spearheaded spectacular and rapid advances in ULSI technology enabling a vast landscape of applications including logic, memory, computing, and sensing, etc. Although Ge was the initial semiconductor of choice for both research and industry, it was quickly superseded by Si as the active-layer material of choice for both bipolar junction transistors and MOSFETs. However, more recently, Ge-based nanoelectronics is making a comeback. In particular, Ge nanophotonics is breaking new ground as the enabling technology for Si photonics applications. Cutting-edge research on semiconductor quantum dots (QDs) has opened up access to wide-ranging applications in electronics, photonics, quantum computing, and sensing. The “holy grail” for device manufacturing is to achieve scalability through precise control and repeatable fabrication of QDs with desired shapes, sizes, and ac-curate placement for predictable electrical and optical proper-ties. A Bohr radius of 5 nm in Si dictates the fabrication of ultrasmall Si QDs, which are difficult to controllably produce using either self-assembly or lithographic techniques. In contrast, a large Bohr radius of 25 nm in Ge enables easier modification of electronic structures using Ge QDs, imposing less stringent demands on lithographic control. Starting with our remarkable discovery of spherical Ge QD formation, we have embarked on an exciting journey of further discovery, all the while maintaining CMOS-compatible processes. We have taken advantage of the many peculiar and symbiotic interactions of Si, Ge and O interstitials to create a novel portfolio of electronic, photonic and quantum computing devices. This talk summarizes several of these completely new and counterintuitive accomplishments. Using a coordinated combination of lithographic patterning and self-assembly, sizetunable spherical Ge QDs were controllably placed at designated spatial locations within Si-containing layers. We exploited the exquisite control available through the thermal oxidation of Si1-xGex patterned structures in proximity to Si3N4/Si layers. Our so-called “designer” Ge QDs have succeeded in opening up myriad device possibilities, including paired QDs for qubits, single-hole transistors (SHTs) for charge sensing, phototransistors for Si sensing, and junctionless FETs using standard Si processing.
Electromagnetic Compatibility Society
Electromagnetic Compatibility Society
Karen Burnham (R4)
Karen Burnham
Karen Burnham is a Principal Scientist at Electro Magnetic Applications in Denver, CO. She is an iNARTE certified EMC engineer with experience in both the aerospace/defense and automotive industries. At NASA JSC, she worked on the Orion spacecraft and pyrotechnic systems. She was able to work on the Dream Chaser spacecraft and the F-35 fighter jet. She spent several years working at Ford Motor Company on traditional vehicles like the Ford Edge and Lincoln Continental as well as on their line of electric hybrid vehicles such as the Ford Explorer and Lincoln Aviator. Ms. Burnham is a member of the IEEE EMC Society Board of Directors where she serves as Assistant Vice President of Standards. She holds a BS degree in Physics from Northern Arizona University and an MS degree in Electrical Engineering from University of Houston.
Talk Topic:
- Noise Sources in Electric Vehicles
Abstract:
With electric vehicles becoming more common, the electromagnetic noise they generate is an issue that more designers must face. Ms. Burnham brings lessons learned from several years of troubleshooting electric vehicles, both hybrid and plug in, to discuss some of the most important EV noise factors.
Geoscience & Remote Sensing Society
Geoscience and Remote Sensing Society
B.S. Daya Sagar (R10)
b-s-daya-sagar
B. S. Daya Sagar (M’2003, SM’2003) is a Professor (Higher Administrative Grade, HAG) of the Systems Science and Informatics Unit (SSIU) at the Indian Statistical Institute, and Head of the Indian Statistical Institute – Bangalore Centre. Sagar received the M.Sc and Ph.D degrees from the Faculty of Engineering, Andhra University, Visakhapatnam, India, in 1991 and 1994 respectively. He is also the first Head of the SSIU. Earlier, he worked in College of Engineering, Andhra University, and Centre for Remote Imaging Sensing and Processing (CRISP), The National University of Singapore in various positions during 1992-2001. He served as Associate Professor and Researcher in the Faculty of Engineering & Technology (FET), Multimedia University, Malaysia during 2001-07. His research interests include mathematical morphology, GISci, digital image pro-cessing, fractals and multifractals their applications in extraction, analyses, and modeling of geophysical patterns. He has published over 90 papers in journals, and has authored and/or guest edited 14 books and/or special theme issues for journals. He authored a book entitled “Mathematical Morphology in Geomorphology and GISci,” CRC Press: Boca Raton, 2013, p. 546. He co-edited a special issue on “Filtering and Segmentation with Mathematical Morphology” for IEEE Journal on Selected Topics in Signal Processing (v. 6, no. 7, p. 737-886, 2012). His recent book on “Handbook of Mathematical geosciences: Fifty Years of IAMG”, Springer Publishers, p. 942, 2018 crossed the downloads of over one million. He edited a two-volume Encyclopedia of Mathematical Geosciences (Springer Nature, 1756 pages) and was released in 2023. He is an elected Fellow of Royal Geographical Society (1999), Indian Geophysical Union (2011), Indian Academy of Sciences (2022), Indian National Science Academy – INSA (2024), and was a member of New York Academy of Science during 1995-96. He received Dr. Balakrishna Memorial Award from Andhra Pradesh Akademi of Sciences in 1995, Krishnan Gold Medal from Indian Geophysical Union in 2002, and ‘Georges Matheron Award-2011 (with Lecturership)” of International Association for Mathematical Geosciences (IAMG), IAMG Certificate of Appreciation – 2018, and the IEEE Geoscience and Remote Sensing (GRSS) Distinguished Lecturer (DL) since 2020. Hs is a Member of Honors and Recognition Committee of the American Geophysical Union (AGU) for 2022-25. He is the Founding Chairman of Bangalore Section IEEE GRSS Chapter. He is on the Editorial Boards of Computers & Geosciences (Elsevier), Frontiers: Environmental Informatics, Mathematical Geosciences (Springer). More details about him can be seen at http://www.isibang.ac.in/~bsdsagar
Talk Topic:
- Research on the Development of Mathematical Morphology-Based Algorithms for Geoscience
- Remote Sensing and Geospatial Data Sciences
Abstract:
Data available at multiple spatial/spectral/temporal scales pose numerous challenges to the data scientists. Of late researchers paid wide attention to handling such data acquired through various sensing mechanisms to address intertwined topics-like pattern retrieval, pattern analysis, quantitative reasoning, and simulation and modeling-for better understanding spatiotemporal behaviors of several terrestrial phenomena and processes [1]. Georges Matheron and Jean Serra of the Centre of Mathematical Morphology, Fontainebleau founded Mathematical Morphology (MM) [2]-[5]. Since the birth of MM in the mid-1960s, its applications in a wide-ranging disciplines have illustrated that intuitive researchers can find varied application-domains to extend the applications of MM. Mathematical Morphology is one of the better choices to deal with the aforementioned intertwined topics. Various original algorithms and techniques that are mainly based on mathematical morphology have been developed and demonstrated. This lecture that presents an overview of mathematical morphology and their applications in geosciences, remotely sensed satellite data and Digital Elevation Model (DEM) processing and analysis, as well as geospatial data sciences, would be useful for those with research interests in image processing and analysis, remote sensing and geosciences, geographical information sciences, spatial statistics, and mathematical morphology, mapping of earth-like planetary surfaces, etc. The content of this broad overview of the lecture will be offered in two parts. In the first part, basic morphological transformations would be covered. An overview of the applications of those transformations, covered in the first part, to understand the granulometries, morphological filtering, morphological interpolations and extrapolations would be given with several case studies during the second part.
Industrial Electronics Society
Industrial Electronics Society
Gerard -Andre Capolino (R8)
Gerard-Andre Capolino
Gérard-André Capolino (A’1977, M’1982, SM’1989, F’2002, LF’2019) was born in Marseille (France). He received a BSc in electrical engineering from Ecole Centrale de Marseille, Marseille (France) in 1974, an MSc from CentraleSupelec, Paris, France in 1975, a Ph.D. from Aix-Marseille University, Marseille, France in 1978 and a DSc from Institut National Polytechnique de Grenoble, Grenoble, France in 1987. He held positions at the University of Yaoundé I, Cameroon, the University of Dijon, Dijon, France, and the Mediterranean Institute of Technology, Marseille, France. In 1994, he joined the University of Picardie “Jules Verne” in Amiens, France as a Full Professor, Head of the Department of Electrical Engineering (1995-1998), Director of the Energy Conversion & Intelligent Systems Laboratory (1996-2000) and Director of the European Master in Advanced Power Electrical Engineering (MAPEE) recognized by the European Commission (2004-2021). He was elevated to the rank of Chair Professor in 2013. Since September 2021, he has been appointed Emeritus Professor of Electrical Engineering in the same University and the same research lab. He is the founder of the consulting company GAC Conseils. He has been the recipient of the following distinctions: the IEEE-IES Eugene Mittelman Achievement Award in 2008, the ICEM Arthur Ellison Outstanding Achievement Award in 2010, the IEEE-PELS Diagnostics Achievement Award in 2011, the ICEM John Tegopoulous Outstanding Service Award in 2016, the IEEE-PES Cyril Veinott Electromechanical Conversion Award in 2017 and the IEEE France Section Distinguished Service Award in 2018. More than 20 DLs have been given by him till date worldwide.
Talk Topic:
1. Modern design and manufacturing of induction machines for transportation electrification
Abstract:
Transportation electrification is far to be a new topic of investigation but it has received a massive interest in the last 15 years due to the need to save energy and limit the emission of polluted gases. On the other hand, electrical machines are just considered prime movers of this means of transportation for bikes/cars/trucks, trains, ships, and even aircraft.
The aim of this lecture is to cover a large range of technologies to better understand the modern design of induction machines used for propulsion in the transportation area. No need to highlight that these machines will be always used in what is called embedded systems and the machine terminals will never be directly connected to the power grid. This last fact will always be the starting point of the design and will be the line of specific data to be considered.
After an introduction to the historical background of induction machines from principles to early manufacturing of prototypes, the classical rotating field motors/generators have been widely described. Then, the presentation has been oriented towards the modern design of induction machines for transportation. By starting from specifications, these techniques take into account electromagnetic, thermal, mechanical, material, application, and even manufacturing problems. Each part has been developed and many examples from the propulsion of vessels, cars, and aircraft have been presented. The modern design has been developed in terms of multiphysics approaches taking into account all the problems previously presented. Of course, a large part of the presentation has been based on computer-aided design from methods to well-known software. The last part of the presentation has been dedicated to the manufacturing process. All aspects of this process have been developed from material (magnetic, conduction, insulation, heat extraction, mechanical mounting) to the final outcome. For each part, several illustrative examples have been shown.
Industrial Electronics Society
Leopoldo G Franquelo (R8)
Leopoldo G Franquelo
Leopoldo G. Franquelo was born in Malaga, Spain. He received the M.Sc. and Ph.D. degrees in electrical engineering from the Universidad de Sevilla, Seville, Spain in 1977 and 1980 respectively. In 1978 he joined the Universidad de Sevilla as Research Assistant, becoming Associated Professor in 1982 and Professor since 1986. From 1998 to 2005 was Director of the Electronics Engineering Department.
His technical interests started in 1978 with Microprocessor Industrial Electronics Applications, evolving to Electronics Power Applications and in the 90’s to Application Specific ICs design for the control of Power Converters. His current research interest lies on modulation techniques for multilevel inverters and its application to power electronic systems for renewable energy systems.
He is leading a large research and teaching team in Spain that has been awarded with the “Excellence Status” by the Andalusian Government. His activity can be summarized as: 65 Publications in prestigious International Journals, including the IEEE Transactions on Industrial Electronics and the Proceedings of the IEEE, 180 publications in Conferences, 12 Patents, and 78 R&D projects. He is coauthor of the paper “The age of Multilevel Converters arrives”, awarded with the 2008 IEEE Industrial Electronics Magazine Best paper award. He is also the recipient of the 2009 Andalusian R&D Award.
He is IEEE member since 1984, Senior Member since 1996 and Fellow since 2005. He has been Vice-president of the Industrial Electronics Society Spanish Chapter (2002-2003), Member at large of the Industrial Electronics Society AdCom (2002-2003), Vice-president for Conferences of the Industrial Electronics Society (2004-2007), President Elect of the Industrial Electronics Society (2008-2009) and he is currently serving in the same society as Distinguished Lecturer (2006-), Associated Editor of the Transactions on Industrial Electronics (2007-), Senior AdCom Member (2008-) and President (2010-2011).
Talk Topic:
1. Advanced Modulation Techniques to Optimize the Operation of Power Converters
Abstract:
Maintenance of power converters is a hot topic in any industrial application. In power systems, the highest percentage of failures are caused by power semiconductors and power capacitors, which suffer from aging mainly caused by thermal stress. To improve converter availability, managing the useful life of the converter, fault tolerant capability, and fast maintenance operations are important features to be achieved. Robust conventional power converters and also modular power converters based on power electronic building blocks are attractive industrial solutions for power systems. Modular converters are especially interesting because of their ability to achieve fault-tolerant operation with a reduced production and maintenance cost.
In this talk, the operation of these converters considering several applications with special attention to the thermal behavior will be addressed. It will be shown that applying advanced modulation and control methods, it is possible to enhance the power converter performance and also making possible to intelligently manage the thermal stress within the most critical power components. This is very useful in order to reduce the corresponding maintenance cost considering the planned maintenance schedule. However, in some cases, the application of such methods provokes a non-negligible degradation of the power converters performance in terms of output waveform quality and/or causing a negative impact on other power converter components lifespan. In the talk, we show that these negative effects can be mitigated by applying advanced modulation methods based on the modification of well-known PWM techniques.
Industrial Electronics Society
Okyay Kaynak (R8)
Okyay Kaynak
Okyay Kaynak received the B.Sc. (first-class honors) and Ph.D. degrees in electronic and electrical engineering from the University of Birmingham, Birmingham, U. K., in 1969 and 1972, respectively. From 1972 to 1979, he held various positions within the industry that included 3.5 years in Saudi Arabia, working as a project engineer. In 1979, he joined the Department of Electrical and Electronics Engineering, Bogazici University, Istanbul, Turkey. He has served as the Chairman of the Computer Engineering and the Electrical and Electronic Engineering Departments and as the Director of Biomedical Engineering Institute at this university. Currently he is an Emeritus Professor, holding the title of UNESCO Chair on Mechatronics. He has held long-term (near to or more than a year) Visiting Professor/Scholar positions at various institutions in Saudi Arabia, Japan, Germany, U.S., Singapore and China. He was, in 2013, awarded the prestigious “1000 People” Program professorship at Harbin Institute of Technology, China. Dr. Kaynak’s current research interests are in the broad field of intelligent systems. He has authored three books, edited five and authored or coauthored more than 400 papers that have appeared in various journals, books and conference proceedings. Dr. Kaynak is a fellow of IEEE. He is or has served on the Editorial or Advisory Boards of a number of scholarly journals. He was the Editor-in-Chief of IEEE Trans. on Industrial Informatics during 2005-2006, IEEE/ASME Trans. on Mechatronics during 2014-2016 and Co-Editor in Chief of IEEE Trans. on Industrial Electronics during 2009-2012. Dr. Kaynak is active in international organizations, has served on many committees of IEEE and was the president of IEEE Industrial Electronics Society during 2002-2003. He received IEEE Third Millennium Medal (2001), IEEE/IES Anthony J. Hornfeck Service Award (2005) and IEEE/IES Dr.-Ing. Eugene Mittelman Achievement Award (2011). Most recently, he received the China Friendship Award (2016), Humboldt Research Prize (2016) and International Academy Prize of Turkish Academy of Sciences (2020).
Talk Topic:
1. Metaverse: What, When and How?
2. Qua Vadis AI?
3. Digital Twins in Intelligent Manufacturing
Abstract:
There are many definitions, the simplest definition is the space that results from merging the physical and cyberspace. The terminology has been around us as a buzzword since the late 2020s. Compared with when it was first coined in 1992 in the science fiction “Snow Crash”, there have been significant changes in its meanings due to technology breakthroughs and the resulting socio-economic transformations. The essential concept of the metaverse lies in creating and living in a higher-dimensional world/space that transcends our physical world. Such a higher-dimensional world is a digital world directed toward the symbiosis of reality and virtuality.
When: Metaverse is already flourishing in gaming as a social platform where multiple people can play on the same platform, immersed in the metaverse. The next application domain will likely be the industry where digital twins are increasingly used. One of the most inspiring parts of the industrial metaverse lies in the potential to restructure the industrial chain and provide added value to all the stakeholders therein. It can be considered as the evolution of industrial Cyber-Physical Systems.
How: It is to be admitted that reaching its maturity is likely to take some time. On a philosophical note, we, and the next generations, will therefore act as the steersmen and the sailors on the long and exciting journey to Nepantla, the liminal space, the in-between the cyber-space and the physical space, and the borderlands from which novel insights and inspirations are likely to emerge.
Instrumentation & Measurement Society
Instrumentation and Measurement Society
Mihaela Albu (R8)
Mihaela Albu
Mihaela M. Albu (M’96, SM’07) is from Craiova, Romania. She graduated from “Politehnica” University of Bucharest (UPB) in 1987 and holds the Ph.D. degree (1998) from the same university. Since 2002 she is a Professor of Electrical Engineering at UPB. Teaching activity presently counts: Advanced Topics in Instrumentation and Measurement (Master); Smart Distribution Grids (Master); Signal Processing (Bachelor) at the Dept. of El. Engineering of UPB; and “Elektrische Meßtechnik”; “Sensoren” at the German Department of UPB. Her research interests include wide area measurement systems as well as synchronized measurements and evaluation of the associated uncertainty considered in the state estimation algorithms; smart energy grids including optimal use of renewables and real time control; smart metering technologies; DC grids as an innovative solution for future intelligent grids, for which a demonstration platform was realized in a fully equipped laboratory fed from a DC bus at 230 V rated voltage and a proposal of power quality assessment in DC grids; power quality and signal processing for power quality assessment, nonlinear phenomena in power systems; distributed and computer-controlled measurement systems, IEEE and IEC standards in power, power system protection, virtual and Internet-based laboratories. She is the founder of an interdisciplinary group MicroDERLab at UPB, and coordinates several research teams working on projects funded by national and international grants. Dr. Albu was spending a leave at Arizona State University as a Fulbright Fellow 2002 – 2003 and in 2010. Her work includes coordination of a monograph (on measurements in power systems ), 7 Book chapters; 21 Journal Publications; more than 70 papers published in International Conference Proceedings; 40 presentations, invited papers and other non-refereed publications; 13 Laboratory notes, and more than 50 Technical Reports (recently on smart grids topics); Since 2009 she is Vice-Chair of the Intellicis -Working Group 2: Reliable management and control of electric power systems, 2009-2013. The professional service is highlighted by active membership in IEEE – IMS, CIGRE, VDE, and IRE (Romanian Power Engineers Society).
As an IEEE member, she volunteers for the Instrumentation and Measurement Society since 2009, while she became part of the AdCom. She is also involved in the IEEE local activities –as a vice-chair of the PES-Romania Chapter and contributes to the dialogue between the Romanian electrical engineering community and the IEEE. Distinguished Lecturer (2020 – 2022); Chapter Chair|| I&M AdCom (2013-2016, 2009-2012)|| VP Membership (2010-2011)|| VP Technical & Standards Activities (2012-2013)|| IEEE Region 8 Chapter Coordination Subcommittee (2011)|| Smart Grid Initiative (2015-2017)|| Education Committee/Faculty Course Development Award Selection Committee (2016-2017)|| Distinguished Lecturer (2016 – 2019).
Talk Topic:
- High Reporting Rate Measurements for Smart[er] Grids
Abstract:
Modern control algorithms in the emerging power systems process information delivered mainly by distributed, synchronized measurement systems, and available in data streams with different reporting rates. Multiple measurement approaches are used: on one side, the existing time-aggregation of measurements are offered by currently deployed IEDs (SCADA framework), including smart meters and other emerging units; on the other side, the high-resolution waveform-based monitoring devices like phasor measurement units (PMUs) use high reporting rates (50 frames per second or higher) and can include fault-recorder functionality. There are several applications where synchronized data received with a high reporting rate has to be used together with aggregated data from measurement equipment having a lower reporting rate (complying with power quality data aggregation standards) and the accompanying question is how adequate are the energy transfer models in such cases. For example, state estimators need both types of measurements: the so-called “classical” one, adapted for a de facto steady-state paradigm of relevant quantities, and the “modern” one, i.e. with fewer embedded assumptions on the variability of same quantities. Another example is given by emerging active distribution grids operation, which assumes higher variability of the energy transfer and consequently, a new model approximation for its characteristic quantities (voltages, currents) is needed. Such a model is required not only in order to be able to correctly design future measurement systems but also for better assessing the quality of existing “classical” measurements, still in use for power quality improvement, voltage control, frequency control, network parameters’ estimation, etc. The main constraint so far is put by the existing standards where several aggregation algorithms are recommended, with a specific focus on the information compression. The further processing of RMS values (already the output of a filtering algorithm) results in significant signal distortion. Presently there is a gap between (i) the level of approximation used for modeling the current and voltage waveforms which are implicitly assumed by most of the measurement devices deployed in power systems and (ii) the capabilities and functionalities exhibited by the high fidelity, high accuracy and a high number of potential reporting rates of the newly deployed synchronized measurement units. The talk will address: o The measurement paradigm in power systems; System inertia, real-time and steady-state Instrument transformers; limited knowledge on the infrastructure PQ, SCADA, and PMUs Power system state estimation; WAMCS IEDs, PMUs, microPMUs Time-stamped versus synchronized measurements o Measurement channel quality and models for energy transfer Voltage and frequency variability; rate of change of frequency The steady-state signal and rapid voltage changes (RVC); RMS-values reported with 100 frames/s; Measurement data aggregation; filtering properties Time- aggregation algorithms in the PQ framework Statistical approaches; o Applications and challenges Communication channel requirements; delay assessment in WAMCS Smart metering with high reporting rate (1s) The presentation provides an overview of these techniques, with examples from worldwide measurement solutions for smart grids deployment.
Instrumentation and Measurement Society
Eros Pasero (R8)
Mihaela Albu
Eros G. Pasero is Professor of Electronics at the Politecnico of Turin since 1991 after a four year appointment as Professor at the University of Roma, Electronics Engineering. He was also Visiting Professor at ICSI, UC Berkeley, CA in 1991, Professor of digital electronics and electronic systems at Tongji University, Shanghai, China in 2011, 2015 and 2017, and Professor of digital electronics and electronic systems at TTPU (Turin Tashkent Politechnic University), Tashkent, Uzbekistan since 2012 to 2014 where he was also vice rector in the first period of 2014. Prof. Pasero established in 1990 the Neuronica Lab where hardware and software neurons and synapses are studied practical applications; innovative wired and wireless sensors are also developed for biomedical, environmental, and automotive applications. Data coming from sensors are post processed by means of artificial neural networks. Prof. Pasero is now the President of SIREN, the Italian Society for Neural Networks; he was v. General Chairman of IJCNN2000 in Como, General Chairman of SIRWEC2006 in Turin, general Chairman of WIRN2015, WIRN2016 and WIRN2017, WIRN 2018 and WIRN 2019 in Vietri. He holds 6 international patents (two were the first silicon European neurons and synapse together Texas Instruments). He was supervisor of tenths of international Ph.D and hundredths of Master students and he is author of more than 100 international publications. Together his group he was awarded with the 1982 CILEA-Sperry award for complex application systems and local distributed architecture”, with the ASSIPE Design-In-Award in 2003 and 2004, with premio “Innova S@alute2017” at the “forum dell’innovazione per la salute” on September 2017; he was IEEE key note speaker at 2014 Symposium series on Computational Intelligence in Orlando, Fl, USA; Distinguished Lecturer of the 2016 IEEE Medical Information Summer School, Distinguished Lecturer of the 2017 IEEE school “Smarter Engineering for Industry 4.0”
Talk Topic:
- Medicine 4.0: AI and IOT, the new revolution
Abstract:
Industry 4.0 is considered the great revolution of the past few years. New technologies, the Internet of things, the possibility to monitor everything from everywhere changed both plants and the approaches to the industrial production. Medicine is considered a slowly changing discipline. The human body model is a difficult concept to develop. But we can identify some passages in which medicine can be compared to industry. Four major changes revolutionized medicine: Medicine 1.0: James Watson and Francis Crick described the structure of DNA. This was the beginning of research in the field of molecular and cellular biology Medicine 2.0: Sequencing the Human genome. This discovery made it possible to find the origin of the diseases. Medicine 3.0: The convergence of biology and engineering. Now the biologist’s experience can be combined with the technology of the engineers. New approaches to new forms of analysis can be used. Medicine 4.0: Digitalization of Medicine: IOT devices and techniques, AI to perform analyses, Machine Learning for diagnoses, Brain Computer Interface, Smart wearable sensors. Medicine 4.0 is definitely a great revolution in the patient care. New horizons are possible today. Covid 19 has highlighted problems that have existed for a long time. Relocation of services, which means remote monitoring, remote diagnoses without direct contact between the doctor and the patient. Hospitals are freed from routine tests that could be performed by patients at home and reported by doctors on the internet. Potential dangerous conditions can be prevented. During the Covid emergency everybody can check his condition and ask for a medical visit (swab) only when really necessary. This is true telemedicine. This is not a WhatsApp where an elder tries to chat with a doctor. This is a smart device able to measure objective vital parameters and send to a health care center. Of course Medicine 4.0 requires new technologies for smart sensors. These devices need to be very easy to use, fast, reliable and low cost. They must be accepted by both people and doctors. In this talk we’ll see together the meaning of telemedicine and E-Health. E-health is the key to allowing people to self monitor their vital signals. Some devices already exist but a new approach will allow to everybody (especially older people with cognitive difficulties) to use these systems with a friendly approach. Telemedicine will be the new approach to the concept of hospital. A virtual hospital, without any physical contact but with an objective measurement of every parameter. A final remote discussion between the doctor and the patient is still required to feel comfortable. But the doctor will have all the vital signal recorded to allow him to make a diagnosis based on reliable data. Another important aspect of medicine 4.0 is the possibility of using AI both to perform parameter measurement and to manage the monitoring of multiple patients. The new image processing based on Artificial Neural Networks allows doctors to have a better and faster analysis. But AI algorithms are also able to manage intensive care rooms with several patients, reducing the number of doctors involved in the global monitoring of the situation.
Instrumentation and Measurement Society
Octavian Postolache (R8)
Octavian Postolache
Dr. Octavian Adrian Postolache is an electrical engineer and Associate Professor with habilitation at ISCTE-Instituto Universitario de Lisboa and a Senior researcher at Instituto de Telecomunicacoes, Lisbon, Portugal. His fields of interest are smart sensors, WSN, IoT for precision agriculture, artificial intelligence for automated measurement systems, and intelligent transportation. Dr. Postolache is the author and co-author of 10 patents, 12 books, 21 book chapters, and more than 400 papers in international journals and indexed conferences with peer review. He developed important research work in the field of environmental monitoring and he participate as a PI or member in national and international Agriculture 4.0 projects such as AGROECOINN and SmartFarm 4.0 Colab. He is an IEEE Senior Member, chair of IEEE IMS TC-13, and current chair of the IEEE IMS Portugal Chapter. He is an Associate Editor of IEEE Sensors Journal, IEEE Transaction on Instrumentation and Measurement, and IoT from Elsevier. He received IEEE outstanding reviewer and the outstanding associate editor from IEEE Transactions in Instrumentation and Measurement and IEEE Sensors Journal and other awards related to his research activity at different international forums.
Talk Topic:
- Smart Sensing Systems and AI for Precision Agriculture in Climate Changes Era
Abstract:
Nowadays when the global population is growing by more than 80 million a year reported studies are predicting an increasing pressure on the planet’s natural resources including food resources. The situation is going worst when unpredictable meteorologic events are running up in the context of great climate changes related to the global effect of anthropogenic greenhouse emissions. In this context precision agriculture (PA) combines technologies and practices to optimize agricultural production through specific farm management are considered. At the same PA focuses on the accuracy of operations considering the place, time to act and method to be applied. Agricultural operations are carried out to reach the production goals using the information provided by the smart sensors and instrumentation increasing the sustainability of operations. Distributed smart sensing system characterized by fixed and mobile nodes (associated with Unnamed Aerial Vehicle (UAV)) is used to turn farming operations into data, and to make future operations a data-driven one. These new including edge and cloud computing that are capable to run artificial intelligence algorithms may contribute to a slight replacement of human decisions based on their accumulated experience with a machine-based decision. This new way to act in agriculture in a digital form combining technologies such as smart sensors, cloud, and mobile computing, data science is related to the fact that classical decisions cannot be applied nowadays when the cultivated areas are much extended, and the adverse meteorological events are occurring frequently that conduct to miss-management with yield losses. Using smart sensors computation and data analysis the applied quantity of water and fertilizers is optimized. Weather stations could provide additional information such as ambient temperature, relative humidity, and wind velocity that are also used together soil measured quantities such as moisture, pH, conductivity, temperature, and macronutrients concentration (Nitrogen, Potassium, Calcium) to create models to be used for farm operation optimization. Data from distributed sensing systems on the crop field can be also used to avoid plant stress phenomena (e.g. plant water stress). Data mining is successfully applied in PA being associated with data analysis of massive data. In this talk, we’ll see together the meaning of precision agriculture in the context of heavy uncertainty associated with climate change. IoT ecosystem for precision agriculture will be discussed including multimodal sensing and artificial intelligence. Referring to sensing as part of the IoT ecosystem in-situ and remote sensing is considered. The agriculture UAV imagery and satellite imagery solutions as so as the relation between the data coming from the smart sensors distributed in the field and acquired images using multispectral imagery techniques will be part of the presentation. Metrological characteristics of smart sensors as so as the calibration procedure for in-situ and remote measurement smart sensing systems will be part of the talk. Another important technology associated with innovative precision agriculture is related to the development of AI data-driven models for farming operations considering data coming from different sources Examples of data-driven models for smart irrigation and nutrient delivery will be considered. Challenges to precision agriculture adoption by regular farmers and how the agricultural operation can support the important transformation to become more environmentally sustainable for increased crop quality will be discussed. A specific part of the talk will be climate change, and how this reality will affect the adoption of smart sensing and AI technologies for PA.
Instrumentation and Measurement Society
Yong Yan (R8)
Yong Yan
Yong Yan is a Professor of Electronic Instrumentation and the Director of Innovation at the School of Engineering and Digital Arts, the University of Kent, Canterbury, U.K. He received the B.Eng. and M.Sc. in instrumentation and control from Tsinghua University, Beijing, China in 1985 and 1988, respectively, and the Ph.D. degree in flow measurement and instrumentation from the University of Teesside, Middlesbrough, U.K., in 1992. His research interests include sensors, instrumentation, measurement and condition monitoring. He has published 470 papers in journals and conference proceedings in addition to 12 research monographs. His h-index is 47 with 8300+ citations. He was awarded the Achievement Medal by the IEE in 2003, the Engineering Innovation Prize by the IET (IEE) in 2006, and the Best Application Award by the IEEE Instrumentation and Measurement Society in 2017. In recognition of his contributions to pulverised fuel flow metering and burner flame imaging he was named an IEEE Fellow in 2011 and elected as a Fellow of the Royal Academy of Engineering in 2020. He was a Distinguished Lecturer of the IEEE Instrumentation and Measurement Society from 2012 to 2018.
Talk Topics:
1. Measurement and Monitoring Techniques through Electrostatic Sensing
2. Multiphase Flow Measurement and Combustion Process Monitoring through Data Driven Modelling
Abstract:
1.Over the past three decades a wide range of electrostatic sensors have been developed and utilized for the continuous monitoring and measurement of various industrial processes. Electrostatic sensors enjoy simplicity in structure, cost-effectiveness and suitability for a variety of process conditions. They either provide unique solutions to some measurement challenges or offer more cost-effective or complementary options to established sensors such as those based on acoustic, capacitive, electromagnetic or optical principles. The established or potential applications of electrostatic sensors appear wide ranging, but the underlining sensing principle and system characteristics are very similar. This presentation will review the recent advances in electrostatic sensors and associated signal processing algorithms for industrial measurement and monitoring applications. The fundamental sensing principle and characteristics of electrostatic sensors will be introduced. A number of practical applications of electrostatic sensors will be presented. These include pulverized fuel flow metering, linear and rotational speed measurement, condition monitoring of mechanical systems, and advanced flame monitoring. Results from recent experimental and modelling studies as well as industrial trials of electrostatic sensors will be reported.
2.Over the past ten years, various machine learning techniques have been incorporated into a range of measurement systems for multiphase flow measurement and combustion process monitoring. Such techniques in conjunction with low-cost sensors and sensor arrays provide either unique solutions to some measurement challenges or offer more cost-effective or complementary options to other possible methods. The established or potential applications of machine learning in measurement and instrumentation appear wide-ranging, but the underlining principle, advantages, and limitations are similar. This presentation will review recent advances in the applications of data-driven modeling techniques to the measurement of gas-liquid, gas-solids, and liquid-solids mixture flows and the advanced monitoring of combustion processes. These include the mass flow rate measurement of air-oil two-phase flow, carbon dioxide two-phase flow, slurry flow, and pneumatically conveyed pulverized fuel in a range of industrial sectors. Meanwhile, systems that incorporate machine learning algorithms for the online continuous identification of pulverized fuel, burner condition monitoring, and combustion plant optimization will be introduced. Results from recent experimental programs and trials on industrial-scale test plants will be reported.
Instrumentation and Measurement Society
Daniel Watzenig (R8)
Daniel Watzenig
Daniel Watzenig was born in Austria. He received his doctoral degree in electrical engineering from Graz University of Technology, Austria, in 2006. In 2009 he received the venia docendi for Electrical Measurement and Signal Processing. Since 2008 he is the Divisional Director of the Automotive Electronics Department at the Virtual Vehicle Research Center Graz. In 2017 he was appointed as a Full Professor of Autonomous Driving at the Institute of Automation and Control, Graz University of Technology, Austria. His research interests focus on the sense & control of automated vehicles, sensor fusion, and uncertainty estimation. He is the author or co-author of over 180 peer-reviewed papers, book chapters, patents, and articles. He is the Editor-in-Chief of the SAE Int. Journal on Connected and Automated Vehicles (SAE JCAV, launched in 2018). Since 2019 he is invited guest lecturer at Stanford University, USA, teaching multi-sensor perception, data fusion, and software for autonomous systems (Principles of Robot Autonomy I). He is the founder of the Autonomous Racing Graz Team, one of currently six teams of the global Roborace race series.
Talk Topics:
1) Introduction to Autonomous Vehicles
2) Multi-Sensor Perception and Data Fusion
Abstract:
Introduction to Autonomous Vehicles Autonomous driving is seen as one of the pivotal technologies that considerably will shape our society and will influence future transportation modes and quality of life, altering the face of mobility as we experience it by today. Many benefits are expected ranging from reduced accidents, optimized traffic, improved comfort, social inclusion, lower emissions, and better road utilization due to efficient integration of private and public transport. Autonomous driving is a highly complex sensing and control problem. State-of-the-art vehicles include many different compositions of sensors including radar, cameras, and lidar. Each sensor provides specific information about the environment at varying levels and has an inherent uncertainty and accuracy measure. Sensors are the key to the perception of the outside world in an autonomous driving system and whose cooperation performance directly determines the safety of such vehicles. The ability of one isolated sensor to provide accurate reliable data of its environment is extremely limited as the environment is usually not very well defined. Beyond the sensors needed for perception, the control system needs some basic measure of its position in space and its surrounding reality. Real-time capable sensor processing techniques used to integrate this information have to manage the propagation of their inaccuracies, fuse information to reduce the uncertainties and, ultimately, offer levels of confidence in the produced representations that can be then used for safe navigation decisions and actions.
Nuclear and Plasma Sciences Society
Nuclear and Plasma Sciences Society
Sara Pozzi (R4)
Sara Pozzi
Professor Sara Pozzi earned her M.S. and Ph.D. in nuclear engineering at the Polytechnic of Milan, Italy in 1997 and 2001, respectively. She is a Professor in the Department of Nuclear and Radiological Sciences at the University of Michigan where she established and is the leader of the Detection for Nuclear Nonproliferation Group (DNNG). Her research interests include the development of new methods for nuclear materials detection, identification, and characterization for nuclear nonproliferation, safeguards, and national security programs. She is the recipient of many awards, including the 2006 Oak Ridge National Laboratory Early Career Award, 2006 Department of Energy, Office of Science, Outstanding Mentor Award, 2012 INMM Edway R. Johnson Meritorious Service Award, 2017 IEEE Distinguished Lecturer, 2018 Rackham Distinguished Graduate Mentoring Award, and 2021 American Nuclear Society Gail De Planque Award. She is a Fellow of the American Nuclear Society, the Institute of Nuclear Materials Management, and the IEEE.
Talk Topic:
- Neutron Detection in Proton Therapy for Cancer Treatment
Abstract:
Recent advances in nuclear detection capabilities, including new detection materials and readout electronics, promise to have an impact in the development of new cancer therapy treatments. I will present new neutron and photon detection techniques that will be used in instruments and algorithms for application in cancer treatment facilities. The urgent needs in this area include, but are not limited to, neutron dosimetry for proton therapy facilities and the evaluation of the biological damage to cells by neutron irradiation. Proton therapy facilities use high-energy proton beams to destroy cancerous cells. In this approach, secondary radiation is produced due to proton interactions with the body and surrounding materials. This secondary field, which includes both neutrons and photons, must be accurately characterized in order to determine its effect on patients and medical personnel. An interdisciplinary approach, including both simulation and experiments, is required to tackle these complex and urgent challenges
Society on Social Implications of Technology
Society on Social Implications of Technology
Fahmida N. Chowdhury (R2)
Fahmida N. Chowdhury
Program Director in the NSF Office of International Science and Engineering (OISE), strong experience in social, behavioral and economic sciences, and in multidisciplinary activities. Fahmida N. Chowdhury was a Professor and Endowed Chair in ECE at the University of Lousiana, Lafayette, LA. She has an international academic experience and strong leadership in promoting and advocating for women in engineering and STEM.
Talk Topic:
- Beyond the technical: other dimensions of your research project
Abstract:
In this talk, I create awareness of issues beyond the technical or scientific parts of research projects. Issues such as societal impacts, ethical considerations, conflicts of interest, intellectual property, unconscious bias, unintended consequences etc. deserve our serious attention but are sometimes ignored.
Society on Social Implications of Technology
Miriam Cunningham (R8)
Mirium Cunningham
Miriam Cunningham (IEEE Senior Member, IEEE-HKN) is a technology and innovation expert with over 25 years experience working with education and research, industry and government organizations. Miriam specializes in contributing to policy analysis, research capacity building, adaptation and implementation of appropriate technology in low resource environments.
Miriam has extensive experience as Co-Principal Investigator of large-scale digital technology innovation oriented cross-border and regional projects in Europe and Africa, including ICT4Development. She has co-organized over 45 large international conferences around the world, including both IEEE and government hosted conferences. Miriam is Head of Research of the not-for-profit IST-Africa Institute, working in strategic partnership with Ministries and National Councils responsible for Innovation, Science and Technology in 18 African Member States. Miriam is an active IEEE volunteer with several leadership roles including IEEE SSIT Board of Governors, IEEE SSIT UK and Ireland Chapter Chair and 2023 IEEE Humanitarian Technologies Board Member chairing the Ad Hoc Committee on SIGHT Best Practices.
Talk Topic:
- mHealth4Afrika – Lessons Learnt and Good Practices from Co-Designing Technology Solutions for Resource Constrained Environments
- Co-designing Ethical Interventions in Resource Constrained Environments
Abstract:
1. Miriam Cunningham shares lessons learnt and good practices from mHealth4Afrika related to the co-design of an appropriate technological solution to address healthcare challenges in resource-constrained environments. Supported by the European Commission, mHealth4Afrika co-designed and validated a state-of-the-art modular, extensible and multilingual standards based health information system to support strengthening primary healthcare delivery in resource constrained environments in Ethiopia, Kenya, Malawi and South Africa.
2. Miriam Cunningham shares lessons learnt and good practices from mHealth4Afrika
related to the co-design of an appropriate technological solution to address healthcare challenges in resource-constrained environments. Supported by the European Commission, mHealth4Afrika co-designed and validated a state-of-the-art modular, extensible and multilingual standards based health information system to support strengthening primary healthcare delivery in resource constrained environments in Ethiopia, Kenya, Malawi and South Africa.
Solid-State Circuits Society
Solid-State Circuits Society
Jane Gu (R1)
Jane Gu
Dr. Qun Jane Gu has received the Ph.D. from University of California, Los Angeles in 2007. After a couple years of industry experience, she started her academia career in 2010 at the University of Florida. Since 2012, she has been with the University of California, Davis, where she is currently a professor. Dr. Jane Gu’s group is passionate in high performance RF, mm-wave and THz integrated circuits and systems and its broad applications. The works from her group have won nine best paper awards from international conferences. She has received 2013 NSF CAREER award, 2015 UC Davis Outstanding Junior Faculty Award, 2017 and 2018 Qualcomm Faculty Award, and 2019 UC Davis Chancellor Fellow. She is a TPC member of solid-state circuits conferences RFIC, CICC and ISSCC.
Talk Topic:
- THz Interconnect, Complement to Electrical and Optical Interconnects
Abstract:
Interconnect Gap” has been a long-standing grand challenge caused by the gap between the ever-increasing data rate demand and the insufficient capabilities. The capacity challenge is further deteriorated with simultaneous challenges of energy efficiency and cost. Existing electrical interconnect (EI) and optical interconnect (OI) face fundamental difficulties to completely address the interconnect issues individually. THz Interconnect (TI), utilizing the frequency spectrum sandwiched between microwave and optical frequencies, holds the high potentials to complement EI and OI by leveraging the advantages of both electronics and optics. In this talk, I will present our research activities in the high potential TI field, including THz silicon waveguide channel development, TI system demonstration, dispersion constrained link bandwidth and mitigation schemes such as mode division and frequency division multiplexing based channelization.
Solid-State Circuits Society
Ping-Hsuan Hsieh (R10)
Ping Hsuan Hsieh
Ping-Hsuan Hsieh received the B.S. degree in electrical engineering from National Taiwan University, Taipei, Taiwan, in 2001, and the M.S. and Ph.D. degrees in electrical engineering from the University of California, Los Angeles, Los Angeles, CA, in 2004 and 2009, respectively. From 2009 to 2011, she was with the IBM T.J. Watson Research Center, Yorktown Heights, NY. In 2011 she joined the Electrical Engineering Department of National Tsing Hua University, Hsinchu, Taiwan, where she is currently an Associate Professor. Her research interests focus on mixed-signal integrated circuit designs for high-speed electrical data communications, clocking and synchronization systems, and energy-harvesting systems.
Prof. Hsieh served in the Technical Program Committee of the IEEE International Solid-State Circuits Conference, and is currently a member of the Technical Program Committees of the IEEE Asian Solid-State Circuits Conference and the IEEE Custom Integrated Circuits Conference. She served as an Associate Editor for the IEEE Internet of Things Journal from 2014 to 2018, a Guest Editor for the IEEE Journal of Solid-State Circuits Special Issue in 2021, and is currently an Associate Editor for the IEEE Open Journal of Circuits and Systems and IEEE Solid-State Circuits Letters.
Talk Topic:
- An Overview on Interface Circuits and MPPT for Piezoelectric Energy Harvesting
Abstract:
Piezoelectric vibration-to-electricity conversion provides a feasible solution to self-sustainability due to its relatively high power density, wider voltage range, and the compatibility with IC technology. In the past decade, we have seen a booming of various interface circuits developed for piezoelectric energy harvesting. The drastic difference between the operating speed of integrated circuits and mechanical vibrations provides a perfect venue for performing nonlinear switching and control in the interface operation with low power, allowing orders of magnitude of improvement in power extracting ability. This tutorial will cover a wide range of state-of-the-art interface designs and MPPT methods for piezoelectric energy harvesting, while emphasizing the circuit implementation considerations. Specifically, after describing the basic full-bridge and half-bridge rectifiers, the Synchronized-Switch-Harvesting (SSH) technique that is the foundation of all modern nonlinear interface circuits will be introduced. Two major categories, namely, the open-circuit and the short-circuit structures, are then discussed in details. After that, the common MPPT algorithms and implementations will be reviewed. This talk will also cover topics such as non-resonant operations and multiple-input piezoelectric energy harvesting systems.
Solid-State Circuits Society
Carolina Mora Lopez (R8)
Carolina Mora Lopez
Carolina Mora Lopez received her Ph.D. degree in Electrical Engineering in 2012 from the KU Leuven, Belgium, in collaboration with imec, Belgium. From 2012 to 2018, she worked at imec as a researcher and analog designer focused on interfaces for neural-sensing applications. During this time, she was the lead analog designer and project leader of the Neuropixels development project which resulted in the conception and fabrication of the Neuropixels 1.0 and 2.0 neural probes. She is currently the principal scientist and team leader of the Circuits & Systems for Neural Interfaces team at imec, which develops circuits and technologies for electrophysiology, neuroprosthetics and BMI. Her research interests include analog and mixed-signal circuit design for sensor, bioelectronic and neural interfaces. Carolina is a senior IEEE member and serves on the technical program committee of the ISSC conference, ISSCC SRP, VLSI circuits symposium, and ESSCIRC conference.
Talk Topic:
- Circuits and technologies for implantable biomedical devices
Abstract:
Biological processes such as neuronal signaling and cell growth are among the most complex micro- and nano-scale processes in nature. Historically such processes have been studied at system level because there were no tools available to study individual components of the process. However, cellular-level interfacing is needed to provide better understanding of the brain and to develop more advanced prosthetic devices and brain-machine interfaces. With semiconductor technology innovations, much recent work has been focused on unraveling biological complexity, but also on driving new diagnoses, treatments and therapies that are tailored to the individual. One of the drivers behind those innovations is novel CMOS circuits enabling multi-modal, high-precision data collection and analysis at ultra-low power consumption. In this talk, I will present recent biomedical developments based on silicon technology, and I will discuss the requirements, materials, circuit techniques and design challenges of their ASIC and SoC platforms.
Systems Council
Systems Council
Sambit Bakshi (R10)
Sambit Bakshi
Sambit Bakshi is currently with the Department of Computer Science and Engineering, National Institute of Technology Rourkela, India. His area of interest includes visual surveillance, biometric security, multimedia forensics, and social security analysis. He presently serves as associate editor of IEEE Transactions on Computational Social Systems, IEEE Transactions on Technology and Society, IEEE Transactions on Education, IEEE Systems Journal, and some other journals. He previously served as associate editor of IEEE Access, IEEE IT Professional in the past. He is a senior member of IEEE. He is Founding Chair of IEEE Rourkela Subsection and IEEE Kolkata Section Biometrics Council Chapter. He serves as distinguished lecturer of IEEE Systems Council for 2023 – 2025. He has published widely in more than 100 journals and conferences.
Talk Topics:
- The Rise and Rise of Biometric Systems
Abstract:
Biometric technology has incepted during 1958 in a very non-scientific way while recording inked fingerprints of people on paper on a whim. Then biometric technology has been practiced and scientific basis were established during finding identity of Afgan Girl Sharbat Gula by National Geographic photographer McCurry and Prof. John Daugman. The talk will introduce the basic concepts of biometric security, beginning with the history of development of biometric technology and how it has become backbone of security in several daily-used products like personal computer or mobile phone. Apart from such applications, the talk will emphasis on how biometric helps to find criminals in FBI and how helps to recognize a person in India using the nation-wide database AADHAAR. Latest usage of deep learning techniques for achieving superior performances from biometric systems will also be highlighted in this talk.
Systems Council
Holly Handley (R2)
Holly Handley
Holly A. H. Handley is a Professor in the Engineering Management and System Engineering Department of Old Dominion University (ODU). Her research focuses on developing models and methodologies to better represent the human component during the architecting and design of socio-technical systems. She is the author of The Human Viewpoint for System Architectures along with over 75 publications on topics of human system engineering. She received her PhD from George Mason University in 1999 and is a Licensed Professional Engineer. Her education includes a BS in Electrical Engineering from Clarkson College (1984), a MS in Electrical Engineering from the University of California at Berkeley (1987) and a MBA from the University of Hawaii (1995). Prior to joining ODU, Dr. Handley worked as a Design Engineer for Raytheon Company (1984-1993) and as a Senior Engineer for Pacific Science & Engineering Group (2002-2010). Dr. Handley is a member of the Institute of Electrical and Electronic Engineers (IEEE) Senior Grade, the International Council on System Engineers (INCOSE) and the Human Factors and Ergonomics Society. She is currently the chair of the IEEE Systems Council Women in Systems Engineering Committee and was recently named an HFES Science Policy Fellow (2018) and ODU Provost Fellow (2023).
Talk Topics:
- Human System Engineering: From Human Views to Human Readiness Levels
Abstract:
This talk discusses the role of Human System Engineering (HSE) within the System Engineering (SE) discipline. It describes two HSE initiatives that are enabling better integration of humans and systems. The Human Views comprise a system architecture viewpoint that provides a perspective on the human roles, activities and information flows required by a complex system. The Human Readiness Levels assess the degree to which human-focused requirements are incorporated into design decisions and the readiness of a system to interact with its human operator. Together these two efforts encourage SE for the total system by supporting a comprehensive integration of the human component into the systems engineering effort, which is critical to the design, development, and operation of successful systems.
Systems Council
Dr. Eren Kurshan (R1)
Eren Kurshan
Dr. Eren Kurshan is an AI researcher and technology executive focused on building AI systems for large-scale industrial use cases. Kurshan received her Ph.D. in Computer Science from the University of California, Los Angeles, as well as a Master’s in Computer Science and a Bachelor’s in Electrical Engineering. She currently serves as an Executive-in-Residence at Princeton University and the head of AI research and methodology at Morgan Stanley. Prior to these roles, she led a number of AI/ML and emerging technology programs at Columbia University, J.P. Morgan and IBM T.J. Watson Research Labs. She was a Visiting Fellow at Princeton’s Center for Information Technology Policy (2015-2016) and served as an Adjunct Professor at Columbia University since 2014.
Dr. Kurshan published over 70 peer reviewed technical publications and holds ~200 patents, with approximately 100 granted. She has served as an associate editor of several IEEE and ACM journals and transactions including the Transactions on Emerging Technology, Transactions on Computers and the Journal of Emerging Technologies in Computing. She was the recipient of 2 Best Technical Paper Awards from IEEE and ACM conferences, as well as top inventor and licensing awards from Bank of America and IBM. She received 2 Outstanding Research and Corporate Accomplishment Awards from IBM for her work on system design and optimization and emerging technology development respectively.
Talk Topics:
- Rebuilding AI: Hardware and Systems Approach for Next Generation AI and AGI
Abstract:
Artificial Intelligence encounters three grand challenges: The Energy Challenge, characterized by a troubling and unsustainable rise in training energy consumption; The Alignment Challenge, where jailbroken and misaligned AI pose significant safety and societal threats; and The AGI Challenge, involving the transition to Artificial General Intelligence, of fully integrated, coherently functioning modalities and higher level functions.
This lecture argues that effective tackling these challenges relies on system design. To enhance energy efficiency, it is essential to leave the current restrictive view of AI as a software only solution and embrace fully integrated system design and novel hardware technologies, such as neuromorphic computing. Addressing alignment challenges involves recognizing the pivotal role of system architecture in moral decision-making, echoing the human brain’s reliance on signal comparators, feedback mechanisms, and control functions, without which it will be nearly impossible to achieve alignment. System design also proves essential for advancing AGI solutions from multiple narrow AI models to integrated co-processing and high-level AGI functions.