Academic Keynote Speakers:

Dariush Divsalar
Modern Coding and the Space Program
Dariush Divsalar received the Ph.D. degree in electrical engineering from UCLA, in 1978. Since then, he has been with NASA’s Jet Propulsion Laboratory (JPL), California Institute of Technology (Caltech), Pasadena, where he is a Fellow. At JPL, he has been involved with developing state-of-the-art technology for advanced deep-space communications systems and future NASA space exploration. He is an adjunct professor at the UCLA Department of Electrical and Computer Engineering. He has taught graduate courses in communications and coding at UCLA and Caltech since 1986. He has published more than 300 technical papers, coauthored a book, contributed to three other books, and holds 30 U.S. patents. Dr. Divsalar was a co-recipient of the 1986 paper award of the IEEE Transactions on Vehicular Technology. He was also a co-recipient of the joint paper award of the IEEE Information Theory and IEEE Communication Theory societies in 2008. The IEEE Communication Society has selected one of his papers for inclusion in a book entitled The Best of the Best: Fifty Years of Communications and Networking Research. He served as an Editor for the IEEE Transactions on Communications from 1989 to 1996. A fellow of IEEE since 1997. He has received over 50 NASA Tech Brief awards, a NASA Exceptional Engineering Achievement Medal in 1996, IEEE Alexander Graham Bell Medal in 2014, an Ellis Island Medal of Honor in 2023, and a NASA Distinguished Public Service Medal in 2023. He was elected to the National Academy of Engineering in 2024.
Frank Kschischang
Coding for Fiber-Optic Communications
Abstract: Error-control coding schemes for fiber-optic communication systems are challenged by the high data rates that must be achieved, necessitating low-complexity, yet performant, solutions. This talk will review some of the approaches that are being proposed (and taken) to achieve beneficial trade-offs between code performance and decoding complexity, both in long-haul telecommunications applications and in shorter-length optical interconnects.

Bio: Frank is a professor of electrical and computer engineering at the University of Toronto, where he has been a faculty member since 1991 (the year he received his Ph.D., also from U of T). He has worked on a number of topics in coding, including the introduction of factor graphs, subspace codes for network coding, and staircase codes. He was general co-chair for the IEEE International Symposium on Information Theory held in Toronto in 2008. He has served on the Board of Governors of the IEEE Information Theory Society, including as Society President in 2010. He served as the Editor-in-Chief of the IEEE Transactions on Information Theory from 2014 to 2016. He has received a number of awards for research, teaching, and service including the 2010 IEEE ComSoc/ITSoc Joint Paper Award, the 2018 ITSoc Paper Award, the 2016 Aaron D. Wyner Distinguished Service Award, the 2019 Sustained Excellence in Teaching Award from the U of T Faculty of Applied Science and Engineering, and the 2023 IEEE Richard W. Hamming Medal.
Gianluigi Liva
Massive Random Access: A Coding Theory Perspective
Abstract: In this talk, we present a survey of recent progress in the development of random access protocols for large-scale wireless networks. We highlight the pivotal role of coding theory in the design of modern random access schemes, starting from sparse graph models that have been instrumental in optimizing the performance of Aloha-like protocols. The unsourced multiple access (UMAC) paradigm is then introduced, revealing new challenges that can be effectively addressed through a coding-theoretic lens.

Bio: Gianluigi Liva received his Ph.D. in Electrical Engineering in 2006 from the University of Bologna, Italy. From 2004 to 2005, he was a visiting scholar at the University of Arizona, Tucson. Since 2006, he has been with the Institute of Communications and Navigation at the German Aerospace Center (DLR), where he currently leads the Information Transmission Group. In 2014, he was appointed as a lecturer in channel coding at the Institute for Communications Engineering (LNT), Technical University of Munich (TUM). His main research interests include satellite communications, random access techniques, and error control coding. He has been active in the 3GPP, DVB-SH, DVB-RCS, and DVB-S2 standardization groups, as well as in the standardization of error-correcting codes for space communications within the CCSDS. He was the co-chair of the 2018 IEEE European School of Information Theory and the TPC co-chair of the 2023 International Symposium on Topics in Coding. Since 2020, he has served as an Associate Editor for Coding and Information Theory for the IEEE Transactions on Communications.
Henry Pfister headshot
Henry D. Pfister
Quantum Error Correction: Overview and Recent Results
Abstract: Spurred by recent advances in quantum science and engineering, interest in quantum information and coding has been increasing at a rapid pace. Much of this interest is driven by the promise of quantum computing and its potential to solve some problems much faster than classical computers. But, there are many other interesting problems that combine error-correcting codes and quantum information. In this talk, we will discuss both coding for quantum computing and coding for classical quantum channels. The focus will be on interesting connections between these two problems and the construction of efficient decoding algorithms for both. A key role will be played by belief propagation both the well-known classical algorithm and the lesser known version with quantum messages.

Bio: 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, a coauthor of a 2016 Symposium on the Theory of Computing (STOC) best paper, and a corecipient of the 2021 Information Theory Society Paper Award. He has served the IEEE Information Theory Society as a member of the Board of Governors (2019–2023), an Associate Editor for the IEEE Transactions on Information Theory (2013–2016), and a Distinguished Lecturer (2015–2016). He was the General Chair of the 2016 North American School of Information Theory and a Technical Program Committee Co-Chair of the 2021 International Symposium on Information Theory.
Galen Reeves
Reed Muller Codes Achieve Capacity: Binary, Non-binary, and Beyond
Galen Reeves is Associate Professor at Duke University with a joint appointment in the Department of Electrical and Computer Engineering and the Department of Statistical Science. He completed his PhD in Electrical Engineering and Computer Sciences at the University of California, Berkeley in 2011, and he was a postdoctoral associate in the Departments of Statistics at Stanford University from 2011 to 2013. His research interests include information theory and high dimensional statistics. He received the NSF CAREER award in 2017.
Paul Siegel
Coding Theory, Memory, and AI: A Harmonious Trio
Paul H. Siegel received the S.B. and Ph.D. degrees in Mathematics from the Massachusetts Institute of Technology, Cambridge, MA, USA, in 1975 and 1979, respectively. He held a Chaim Weizmann Postdoctoral Fellowship with the Courant Institute, New York University, New York, NY, USA. He was with the IBM Research Division, San Jose, CA, USA, from 1980 to 1995. He joined the faculty at the University of California San Diego (UCSD), La Jolla, CA, USA, in 1995, where he is currently a Distinguished Professor of Electrical and Computer Engineering with the Jacobs School of Engineering. He is affiliated with the Center for Memory and Recording Research where he holds an Endowed Chair and served as Director from 2000 to 2011. His research interests include information theory, coding techniques, and machine learning, with applications to digital data storage and transmission. He is a Fellow of the IEEE and was the 2015 Padovani Lecturer of the IEEE Information Theory Society. He was elected to the National Academy of Engineering in 2008.

Prof. Siegel was a Member of the Board of Governors of the IEEE Information Theory Society from 1991 to 1996 and from 2009 to 2014. He was a co-recipient of the 1992 IEEE Information Theory Society Paper Award, the 1993 IEEE Communications Society Leonard G. Abraham Prize Paper Award, and the 2007 Best Paper Award in Signal Processing and Coding for Data Storage from the Data Storage Technical Committee of the IEEE Communications Society. He served as an Associate Editor of Coding Techniques of the IEEE Transactions on Information Theory from 1992 to 1995, and as the Editor-in-Chief from 2001 to 2004. He served as a Co-Guest Editor of the 1991 Special Issue on “Coding for Storage Devices” of the IEEE Transactions on Information Theory. He was also a Co-Guest Editor of the 2001 two-part issue on “The Turbo Principle: From Theory to Practice” and the 2016 issue on “Recent Advances in Capacity Approaching Codes” of the IEEE Journal on Selected Areas in Communications. More recently, he was Co-Lead Guest Editor of the 2023 issue on “Dimensions of Channel Coding (Special Issue in Memory of Alexander Vardy)” of the IEEE Journal on Selected Areas in Information Theory and the Lead Guest Editor of the two-part 2023 special issue on “Information Theory and Data Storage” of IEEE BITS, the Information Theory Magazine. Most recently, he was a Co-Guest Editor of the 2024 special issue on “Plenty of Room at Bottom: Ten Years of DNA-Based Data Storage” of the IEEE Transactions on Molecular, Biological, and Multi-Scale Communications.