| 8:30 am - noon |
Theme: From High-Order to Filterbanks and Data-driven Signal Processing
Session Chair: Ananthram Swami
Headline speaker:
Ali Sayed
- "Socially Intelligent Networks" [abstract]
Modern society is witnessing the emergence of complex networked systems driven by exchanges of information among their elements, such as robotic swarms, autonomous systems, social networks, and Internet-of-Things (IoT) architectures. In these applications, data is collected from heterogeneous sources and is generally dispersed across geographic locations. In this context, it is imperative to design learning algorithms that are better suited to the reality of networked units. New methodologies are necessary to account for “coupling” among “intelligent” agents in a manner that respects privacy, enables multi-tasking, promotes fairness, and is robust to malicious interference. Motivated by these considerations, we provide an overview of algorithms for learning and decision-making that exploit important characteristics of social interactions over graphs. We refer to the framework as Social Machine Learning: it handles heterogeneity in data more gracefully, learns with performance guarantees, is more resilient to adversarial attacks, and promotes explainable and fair learning. The framework exploits three properties that are normally missing from existing learning approaches: diversity, decentralization, and group dynamics.
[Bio]
A. H. Sayed is Dean of Engineering at EPFL, Switzerland, where he also directs the Adaptive Systems Laboratory. He served before as Distinguished Professor and Chair of Electrical Engineering at UCLA. He is a member of the US National Academy of Engineering (NAE) and The World Academy of Sciences (TWAS). He served as President of the IEEE Signal Processing Society in 2018 and 2019. An author of over 600 scholarly publications and 9 books, his research involves several areas including adaptation and learning theories, statistical inference, and multi-agent systems. His work has been recognized with several awards including more recently the 2022 IEEE Fourier Technical Field Award and the 2020 IEEE Wiener Society Award. He is a Fellow of IEEE, EURASIP, and the American Association for the Advancement of Science (AAAS).
Expert speakers:
- Yoram Bresler - "When Pencil-Pushing is not Enough: Data-Driven Performance Bounds on Parameter Estimation" [Bio]
Yoram Bresler received the B.Sc. and M.Sc. from the Technion Israel Institute of Technology, and the Ph.D. from Stanford University all in electrical engineering. He is currently a Professor at the Department of Bioengineering and at the Coordinated Science Laboratory, and Founder Professor Emeritus at the Department of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign. He is also the Founding President and CTO of InstaRecon, Inc., commercializing breakthrough technology for tomographic reconstruction developed in his academic research. His current research interests are in machine learning and statistical signal processing and their applications to inverse problems in imaging, including compressed sensing, computed tomography, magnetic resonance imaging, and ultrasound.
Dr. Bresler is a Life Fellow of the IEEE, and a Fellow of the IAMBE, and the AIMBE. His papers have received 4 IEEE best journal paper awards, two of these with his students. In 2016-17 he served as an IEEE SPS Distinguished Lecturer. He received the 1991 NSF Presidential Young Investigator Award, the Technion Faculty Fellowship in 1995, and the Xerox Senior Award for Faculty Research in 1998. He was named University of Illinois Scholar in 1999, and was appointed as an Associate at the Center for Advanced Study of the University in 2001-2002. He was a Faculty Fellow at the National Center for Super Computing Applications in 2006. He has served on the editorial board of several journals, including the IEEE TSP, the IEEE JSTSP, Machine Vision and Applications, and the SIAM Journal on Imaging Science, and on various committees of the IEEE.
- P. P. Vaidyanathan - "TBD"
[Bio]
Prof. P. P. Vaidyanathan is the Kiyo and Eiko Tomiyasu Professor of electrical engineering at the California Institute of Technology (Caltech), and has been on the faculty since 1983. His research interests include sparse array signal processing, signal processing for digital communications, estimation theory, sparse reconstruction and compressive sensing, graph signal processing, multirate signal processing, digital filter banks and filtering, wavelets, image halftoning, genomic signal processing, and number theoretic signal processing, to name a few.
Considered to be one of the pioneering contributors to multirate signal processing research, Vaidyanathan has strongly influenced the research directions in filter banks and multirate systems. He is most well known for developing the general theory of filter banks with perfect reconstruction, as well as orthonormal filter banks, which have impacted digital communications, audio, and image coders. Vaidyanathan’s book on Multirate Systems and Filter Banks (1992) was used as a classroom text and a research reference for more than two decades worldwide, and had major impact in the field.
One of his earliest contributions was in the area of low-sensitivity digital filter structures. He showed how such structures can be designed directly in discrete time, without the need for transforming electrical circuits into the digital domain. An early proponent of applying signal processing methods to genomics, Vaidyanathan developed methods to computationally predict the location of protein coding genes and noncoding genes. His recent work on Ramanujan-sums, and his introduction of Ramanujan subspaces have resulted in new representations and efficient algorithms for signals with hidden patterns such as periodicities. His work on sparse arrays such as coprime and nested arrays has had a major impact in array processing research, leading to many new directions in this area. A key property of these arrays is that they can identify many more sources than the number of sensors in the array. Systematic algorithms for this were developed for the first time from his research group.
A Life Fellow of IEEE, Prof. Vaidyanathan received the B.Sc., B.Tech. and M.Tech. degrees from the University of Calcutta, India, in 1974, 1977 and 1979, respectively, and the Ph.D. degree in electrical and computer engineering from the University of California at Santa Barbara, in 1982. He has written over 550 research papers and four books. He has an h-index of 85, and over 37,000 citations in Google Scholar. He was the recipient of the IEEE CAS Society Golden Jubilee Medal, the Terman Award of the ASEE, the IEEE Gustav Robert Kirchhoff Technical Field Award (2016), the IEEE Signal Processing Society’s Shannon-Nyquist Technical Achievement Award (2001), the IEEE Signal Processing Society’s Carl Friedrich Gauss Education Award (2012), the Norbert Wiener Society Award (2016), and the EURASIP Athanasios Papoulis Award (2021). He is a recipient of multiple awards for teaching at Caltech, including the Northrop Grumman Teaching Prize (2016). He is a Foreign Fellow of the Indian National Academy of Engineering (2021), a member of the U.S. National Academy of Engineering (2019), and a recipient of the IEEE Jack S. Kilby Signal Processing Medal.
- Bhaskar Rao - "Sparse Signal Recovery Algorithms: Model-Based to Data Driven Approaches" [Bio]
Bhaskar D. Rao is a pioneer in the theory and use of sparsity in signal processing applications. Since coauthoring the first paper on the seminal FOCUSS algorithm in 1992, he has been driving the field of sparsity forward, including co-organizing the first special session on sparsity at ICASSP 1998 entitled "SPEC-DSP: Signal Processing with Sparseness Constraint”.
He received his B.Tech. degree in Electronics and Electrical Communication Engineering from the Indian Institute of Technology, Kharagpur, India, in 1979 and his M.S. and Ph.D. degrees from the University of Southern California, Los Angeles in 1981 and 1983, respectively. He has been teaching and conducting research at the University of California in San Diego, La Jolla since 1983, where he is currently a Professor Emeritus and Distinguished Professor of the Graduate Division in the Electrical and Computer Engineering department. He has also been the holder of the Ericsson Endowed Chair in Wireless Access Networks and Distinguished Professor until 2023 and the Director of the Center for Wireless Communications (2008-2011).
Professor Rao’s research interests are in the areas of digital signal processing, estimation theory, and optimization theory, with applications to digital communications, speech signal processing, and biomedical signal processing. His work has received several paper awards, including the 2012 Signal Processing Society (SPS) best paper award for the paper “An Empirical Bayesian Strategy for Solving the Simultaneous Sparse Approximation Problem,” with David P. Wipf and the Stephen O. Rice Prize paper award in the field of communication systems for the paper “Network Duality for Multiuser MIMO Beamforming Networks and Applications,” with B. Song and R. L. Cruz.
Professor Rao was elevated to fellow of IEEE in 2000 for his contributions to the statistical analysis of subspace algorithms for harmonic retrieval. He received the 2016 IEEE Signal Processing Society Technical Achievement Award and the 2023 IEEE Signal Processing Society Norbert Wiener Society Award. He has been a member of the Statistical Signal and Array Processing Technical Committee, the Signal Processing Theory and Methods Technical Committee, the Communications Technical Committee of the IEEE Signal Processing Society, SPS Fellow Evaluation Committee (2023-2024) and was the chair of the Machine Learning for Signal Processing Technical Committee (2019-2020).
|
| 1:30 pm - 5:00 pm |
Theme: AI-enhanced NextG Wireless Communications
Session Chair: Andreas Spanias
Headline speaker:
Arogyaswami Paulraj - “Key Ideas in Mobile Wireless Technology: 2G to 5G” [abstract]
This talk offers a retrospective view of mobile wireless technology spanning the past four decades. The wireless research community generated many ideas, but only a few have been incorporated into mobile standards, and even less have been enabled in deployed networks. This talk outlines some of the complex tradeoffs that determined what technologies got in and what did not.
Finally, some thoughts on NextG.
[Bio]
Paulraj is an Emeritus Professor at Stanford University and pioneered MIMO (Multiple Input, Multiple Output) wireless technology. Paulraj served for 25 years with the Indian Navy, prematurely retiring in 1991 to join Stanford University as a research associate.
Paulraj founded Iospan Wireless Inc., which pioneered MIMO-OFDMA wireless technology, and co-founded Beceem Communications Inc., a leader in 4G-WiMAX chip sets.
His recognitions include the 2023 IET Faraday Medal, the 2014 Marconi Prize, the 2011 IEEE Alexander Graham Bell Medal, and a 2018 Inductee - US Patent Office’s National Inventors Hall of Fame.
Expert speakers:
- Mohamed-Slim Alouini - “What Should 6G Be?”
[Bio]
Mohamed-Slim Alouini, was born in Tunis, Tunisia. He earned his Ph.D. from the California Institute of Technology (Caltech) in 1998 before serving as a faculty member at the University of Minnesota and later at Texas A&M University at Qatar. In 2009, he became a founding faculty member at King Abdullah University of Science and Technology (KAUST), where he currently is the Al-Khawarizmi Distinguished Professor of Electrical and Computer Engineering and where he holds the UNESCO Chair on Education to Connect the Unconnected. Dr. Alouini is a Fellow of the IEEE and OPTICA and his research interests encompass a wide array of research topics in wireless and satellite communications. He is currently particularly focusing on addressing the technical challenges associated with information and communication technologies (ICT) in underserved regions and is deeply committed to bridging the digital divide by tackling issues related to the uneven distribution, access to, and utilization of ICT in rural, low-income, disaster-prone, and hard-to-reach areas.
- Robert Heath
- "Data-driven beam management in 5G and beyond" [Bio]
Robert W. Heath Jr. is the Charles Lee Powell Chair in Wireless Communications in the Department of Electrical and Computer Engineering at the University of California, San Diego. He is also President and CEO of MIMO Wireless Inc. From 2002-2020 he was with The University of Texas at Austin, most recently as Cockrell Family Regents Chair in Engineering and Director of UT SAVES. From 2020-2023 he was the Lampe Distinguished Professor at North Carolina State University and co-founder of 6GNC. He authored ``Introduction to Wireless Digital Communication'' (Prentice Hall, 2017) and ``Digital Wireless Communication: Physical Layer Exploration Lab Using the NI USRP'' (National Technology and Science Press, 2012), and co-authored ``Millimeter Wave Wireless Communications'' (Prentice Hall, 2014) and ``Foundations of MIMO Communication'' (Cambridge University Press, 2018).
Dr. Heath has been a co-author of a number award winning conference and journal papers including recently the 2017 Marconi Prize Paper Award, the 2019 IEEE Communications Society Stephen O. Rice Prize, the 2020 IEEE Signal Processing Society Donald G. Fink Overview Paper Award, the 2021 IEEE Vehicular Technology Society Neal Shepherd Memorial Best Propagation Paper Award, and the 2022 IEEE Vehicular Technology Society Best Vehicular Electronics Paper Award. Other notable awards include the 2017 EURASIP Technical Achievement award, the 2019 IEEE Kiyo Tomiyasu Award and the 2021 IEEE Vehicular Technology Society James Evans Avant Garde Award. In 2017, he was selected as a Fellow of the National Academy of Inventors. He was a member-at-large on the IEEE Communications Society Board-of-Governors (2020-2022) and the IEEE Signal Processing Society Board-of-Governors (2016-2018). He was Editor-in-Chief of IEEE Signal Processing Magazine from 2018-2020. He is also a licensed Amateur Radio Operator, a Private Pilot, a registered Professional Engineer in Texas.
- Lee Swindlehurst
- "Energy Efficient MIMO Precoding" [Bio]
Lee Swindlehurst received the B.S. (1985) and M.S. (1986) degrees in Electrical Engineering from Brigham Young University (BYU), and the PhD (1991) degree in Electrical Engineering from Stanford University. He was with the Department of Electrical and Computer Engineering at BYU from 1990-2007, and during 1996-97, he held a joint appointment as a visiting scholar at Uppsala University and the Royal Institute of Technology in Sweden. From 2006-07, he was on leave working as Vice President of Research for ArrayComm LLC in San Jose, California. Since 2007 he has been with the Electrical Engineering and Computer Science (EECS) Department at the University of California Irvine, where he is currently a Distinguished Professor and holds the Nicolaos G. and Sue Curtis Alexopoulos Presidential Chair. During 2014-17 he was also a Hans Fischer Senior Fellow in the Institute for Advanced Studies at the Technical University of Munich. In 2016, he was elected as a Foreign Member of the Royal Swedish Academy of Engineering Sciences (IVA). His research focuses on array signal processing for radar, wireless communications, and biomedical applications. Dr. Swindlehurst is a Fellow of the IEEE and was the inaugural Editor-in-Chief of the IEEE Journal of Selected Topics in Signal Processing. He received the 2000 IEEE W. R. G. Baker Prize Paper Award, the 2006 IEEE Communications Society Stephen O. Rice Prize in the Field of Communication Theory, the 2006, 2010 and 2021 IEEE Signal Processing Society’s Best Paper Awards, the 2017 IEEE Signal Processing Society Donald G. Fink Overview Paper Award, a Best Paper award at the 2020 IEEE International Conference on Communications, and the 2022 Claude Shannon-Harry Nyquist Technical Achievement Award from the IEEE Signal Processing Society.
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