June 22-26, 2026 | Brigham Young University, Provo, UT
Meet our invited and featured speakers
Columbia University - Goldsmith Lecturer
Cynthia Rush received the B.S. degree in mathematics from the University of North Carolina at Chapel Hill in 2010 and the M.A. and Ph.D. degrees in statistics from Yale University in 2011 and 2016, respectively. She is currently an Associate Professor of statistics with Columbia University. Her research interests include message passing algorithms, statistical robustness, and applications to wireless communications.
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University of Illinois Urbana-Champaign - Padovani Lecturer
Prof. Veeravalli received the Ph.D. degree in Electrical Engineering from the University of Illinois at Urbana-Champaign in 1992, the M.S. degree from Carnegie-Mellon University in 1987, and the B.Tech degree from Indian Institute of Technology, Bombay (Silver Medal Honors) in 1985. He is currently the Henry Magnuski Professor in the Department of Electrical and Computer Engineering (ECE) at the University of Illinois at Urbana-Champaign, where he also holds appointments with the Coordinated Science Laboratory (CSL) and the Department of Statistics. He was on the faculty of the School of ECE at Cornell University before he joined Illinois in 2000. He served as a program director for communications research at the U.S. National Science Foundation in Arlington, VA during 2003-2005. His research interests span the theoretical areas of statistical inference, machine learning, and information theory, with applications to data science, wireless communications, and sensor networks. He is a Fellow of the IEEE and a Fellow of the Institute of Mathematical Statistics (IMS). Among the awards he has received for research and teaching are the IEEE Browder J. Thompson Best Paper Award, the U.S. Presidential Early Career Award for Scientists and Engineers (PECASE), the Abraham Wald Prize in Sequential Analysis (twice), and the Fulbright-Nokia Distinguished Chair in Information and Communication Technologies.
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Arizona State University
Lalitha Sankar is a Professor in the School of Electrical, Computer and Energy Engineering at Arizona State University. She received a bachelor's degree from the Indian Institute of Technology, Bombay, a master's degree from the University of Maryland, and a doctorate from Rutgers University in 2007. Following her doctorate, Sankar was a recipient of a three-year Science and Technology Teaching Postdoctoral Fellowship from the Council on Science and Technology at Princeton University, following which she was an associate research scholar at Princeton. Prior to her doctoral studies, she was a senior member of technical staff at AT&T Shannon Laboratories. Sankar's research interests are at the intersection of information and data sciences including a background in signal processing, learning theory, and control theory with applications to the design of machine learning algorithms with algorithmic fairness, privacy, and robustness guarantees. Her research also applies such methods to complex networks including the electric power grid and healthcare systems. For her doctoral work, she received the 2007-2008 Electrical Engineering Academic Achievement Award from Rutgers University. She received the IEEE Globecom 2011 Best Paper Award for her work on privacy of side-information in multi-user data systems. She was awarded the National Science Foundation CAREER award in 2014 for her project on privacy-guaranteed distributed interactions in critical infrastructure networks such as the Smart Grid. She has led an NSF Institute on Data-intensive Research in Science and Engineering (I-DIRSE), is a recipient of an NSF SCALE MoDL (Mathematics of Deep Learning) grant, and a Google AI for Social Good grant. Sankar was a distinguished lecturer for the IEEE Information Theory Society from 2020-2022. She serves as an Associate Editor for the IEEE Transactions on Information Forensics and Security, IEEE Information Theory Transactions, and was an AE for the IEEE BITS Magazine until August 2024.
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McMaster University
Jun Chen received the B.E. degree in communication engineering from Shanghai Jiao Tong University, Shanghai, China, in 2001, and the M.S. and Ph.D. degrees in electrical and computer engineering from Cornell University, Ithaca, NY, USA, in 2004 and 2006, respectively. From September 2005 to July 2006, he was a Postdoctoral Research Associate with the Coordinated Science Laboratory, University of Illinois at Urbana–Champaign, Urbana, IL, USA, and a Postdoctoral Fellow with the IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA, from July 2006 to August 2007. Since September 2007, he has been with the Department of Electrical and Computer Engineering, McMaster University, Hamilton, ON, Canada, where he is currently a Professor. His research interests include information theory, machine learning, wireless communications, and signal processing. Dr. Chen was a recipient of the Josef Raviv Memorial Postdoctoral Fellowship in 2006, the Early Researcher Award from the Province of Ontario in 2010, the IBM Faculty Award in 2010, the ICC Best Paper Award in 2020, and the JSPS Invitational Fellowship in 2021. He held the title of the Barber-Gennum Chair in Information Technology from 2008 to 2013 and the title of the Joseph Ip Distinguished Engineering Fellow from 2016 to 2018. He was an Associate Editor of the IEEE TRANSACTIONS ON INFORMATION THEORY from 2014 to 2016 and an Editor of the IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING from 2020 to 2021. He is currently serving as an Associate Editor for the IEEE TRANSACTIONS ON INFORMATION THEORY and an Associate Editor for the IEEE TRANSACTIONS ON COMMUNICATIONS.
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George Mason University
Alex Sprintson is Professor and Chair of the Department of Electrical and Computer Engineering at George Mason University, where his research focuses on security and privacy, network coding, and distributed storage systems. He is an IEEE Fellow and the recipient of several recognitions, including the Texas A&M College of Engineering Outstanding Contribution Award and the NSF CAREER Award. He has also been a member of the Technical Program Committee of IEEE INFOCOM from 2006 to 2027 and served as Technical Program Committee Co-Chair in 2024. Prior to joining George Mason University, Dr. Sprintson was a faculty member in the Department of Electrical and Computer Engineering at Texas A&M University from 2005 to 2025. From 2018 to 2022, he served as a rotating Program Director at the U.S. National Science Foundation, where he helped lead the Resilient & Intelligent NextG Systems (RINGS) and Secure and Trustworthy Cyberspace (SaTC) programs. From October 2022 to December 2023, he was Network Security Principal at Nokia Bell Labs, where he led a research team focused on post-quantum cryptography and crypto-agility.
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Georgia Institute of Technology
Matthieu R. Bloch is a Professor in the School of Electrical and Computer Engineering. He received the Engineering degree from Supélec, Gif-sur-Yvette, France, the M.S. degree in Electrical Engineering from the Georgia Institute of Technology, Atlanta, in 2003, the Ph.D. degree in Engineering Science from the Université de Franche-Comté, Besançon, France, in 2006, and the Ph.D. degree in Electrical Engineering from the Georgia Institute of Technology in 2008. In 2008-2009, he was a postdoctoral research associate at the University of Notre Dame, South Bend, IN. Since July 2009, Dr. Bloch has been on the faculty of the School of Electrical and Computer Engineering, and from 2009 to 2013 Dr. Bloch was based at Georgia Tech Lorraine. His research interests are in the areas of information theory, error-control coding, wireless communications, and cryptography. Dr. Bloch has served on the organizing committee of several international conferences; he was the chair of the Online Committee of the IEEE Information Theory Society from 2011 to 2014, an Associate Editor for the IEEE Transactions on Information Theory from 2016 to 2019 and again since 2021, and he has been on the Board of Governors of the IEEE Information Theory Society since 2016 and currently serves as the Senior Past President. He was an Associate Editor for the IEEE Transactions on Information Forensics and Security from 2019 to 2023. He is the co-recipient of the IEEE Communications Society and IEEE Information Theory Society 2011 Joint Paper Award, the 2025 IEEE Joy Thomas Tutorial Paper Award, and the co-author of the textbook Physical-Layer Security: From Information Theory to Security Engineering published by Cambridge University Press.
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University of Pennsylvania
Dr. Hassani serves as an associate professor with a primary appointment in the Department of Electrical and Systems Engineering at the University of Pennsylvania. He holds additional appointments in the Department of Computer and Information Science and the Department of Statistics and Data Science at the Wharton School. In addition to his faculty roles, he is a visiting faculty researcher at Google Research (NYC). His leadership positions include serving as the Penn site-lead for EnCORE (Institute for Emerging CORE Methods of Data Science) and as the co-lead of foundations for NSF-TILOS (AI Institute for Learning-enabled Optimization at Scale). Prior to joining the faculty at Penn, Dr. Hassani was a research fellow at the Simons Institute, UC Berkeley, participating in the Foundations of Machine Learning program. His previous experience also includes serving as a post-doctoral scholar and lecturer within the Institute for Machine Learning at ETH Zürich. Dr. Hassani earned his Ph.D. in Computer and Communication Sciences from EPFL.
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University of Minnesota Twin Cities
Dr. Mohammad Ali Maddah-Ali is an associate professor in the Department of Electrical and Computer Engineering at the University of Minnesota Twin Cities. He received his Ph.D. degree from the Department of Electrical and Computer Engineering at the University of Waterloo, Canada. His professional background includes positions with the Wireless Technology Laboratories at Nortel Networks in Ottawa from 2007 to 2008 and a tenure as a postdoctoral fellow at the Department of Electrical Engineering and Computer Sciences at the University of California at Berkeley from 2008 to 2010. From September 2010 to September 2020, he served as a communication research scientist at Nokia Bell Labs in Holmdel, New Jersey. A recipient of the 2015 IEEE Communications Society and IEEE Information Theory Society Joint Paper Award, the 2016 IEEE Information Theory Society Joint Paper Award, and the 2014 IEEE International Conference on Communications Best Paper Award, he was named an IEEE Fellow in the class of 2023 for his contributions to information theory for interference management, coded caching, and computing. His editorial service includes roles as an associate editor of the IEEE Transactions on Information Theory from 2019 to 2022 and as a lead editor for the IEEE Journal on Selected Areas in Information Theory. He is currently a member of the award committee of the IEEE Information Theory Society.
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University of California, Los Angeles
Richard D. Wesel received Bachelor of Science and Master of Science degrees in Electrical Engineering from the Massachusetts Institute of Technology in 1989. He received the Ph.D degree in Electrical Engineering from Stanford in 1996. He is a Professor with the UCLA Electrical and Computer Engineering Department and is the Associate Dean for Academic and Student Affairs for the UCLA Henry Samueli School of Engineering and Applied Science. As Associate Dean, he has pioneered new approaches to effective undergraduate advising by faculty, universal peer mentoring for undergraduates, and the development of a community of practice among instructors to improve teaching and learning in engineering. His research is in the area of communication theory with particular interest in low-density parity-check coding, short-blocklength communication with feedback, and coding for storage. He has received the National Science Foundation (NSF) CAREER Award, an Okawa Foundation award for research in information theory and telecommunications, and the Excellence in Teaching Award from the Samueli School of Engineering. Wesel has served as Associate Editor for Coding and Coded Modulation for the IEEE Transactions on Communications and is currently an Associate Editor for Coding Techniques for the IEEE Transactions on Information Theory. He is a Fellow of the IEEE.
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Duke University
Henry D. Pfister received his Ph.D. in Electrical Engineering in 2003 from the University of California, San Diego and is currently a professor in the Electrical and Computer Engineering Department of Duke University with a secondary appointment in Mathematics. Prior to that, he was an associate professor at Texas A&M University (2006-2014), a post-doctoral fellow at the École Polytechnique Fédérale de Lausanne (2005-2006), and a senior engineer at Qualcomm Corporate R&D in San Diego (2003-2004). His current research interests include information theory, error-correcting codes, quantum computing, and machine learning. He received the NSF Career Award in 2008 and a Texas A&M ECE Department Outstanding Professor Award in 2010. He is a coauthor of the 2007 IEEE COMSOC best paper in Signal Processing and Coding for Data Storage and a coauthor of a 2016 Symposium on the Theory of Computing (STOC) best paper. He has served the IEEE Information Theory Society as a member of the Board of Governors (2019-2022), an Associate Editor for the IEEE Transactions on Information Theory (2013-2016), and a Distinguished Lecturer (2015-2016). He was also the General Chair of the 2016 North American School of Information Theory.
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New Mexico State University
David G. M. Mitchell received the Ph.D. degree in Electrical Engineering from the University of Edinburgh, United Kingdom, in 2009. He currently holds the IFT Professorship in Telecommunications and is an Associate Professor in the Klipsch School of Electrical and Computer Engineering at the New Mexico State University, USA. He previously held Visiting Assistant Professor and Post-Doctoral Research Associate positions in the Department of Electrical Engineering at the University of Notre Dame, USA. He is a Senior Member of the IEEE and his research interests lie in the areas of digital communications, machine learning, and quantum computing, with emphasis on error control coding and information theory. Dr. Mitchell holds 3 U.S. patents and has published over 75 peer-reviewed IEEE journal and conference articles gathering more than 1800 citations. He received the National Science Foundation CAREER award in 2022, the National Science Foundation's most prestigious award in support of early-career faculty, and the 2019 NMSU Early Career Award for Exceptional Achievements in Creative Scholarly Activity. He has received 4 best paper awards and is the recipient of the 2019 New Mexico EPSCoR Mentor Award. Dr. Mitchell serves as an Associate Editor for the IEEE Transactions on Communications, previously having served as an Associate Editor of the IEEE Transactions on Information Theory.
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