Padovani Lecturer: Venugopal V. Veeravalli
The Padovani Lecturer Program was established with a generous gift by Dr. Roberto Padovani in 2009. The award provides for an outstanding member of the information theory community to deliver a lecture at one of the ITSoc’s Schools of Information Theory, for the benefit of students and postdoctoral researchers.
Venugopal V. Veeravalli received the B.Tech. degree (Hons.) from IIT Bombay in 1985, the M.S. degree from Carnegie Mellon University, Pittsburgh, PA, in 1987, and the Ph.D. degree from the University of Illinois at Urbana–Champaign in 1992, all in electrical engineering. He joined the University of Illinois at Urbana–Champaign in 2000, where he is currently the Henry Magnuski Professor with the Department of Electrical and Computer Engineering, and where he is also with the Department of Statistics and the Coordinated Science Laboratory. Prior to joining the University of Illinois at Urbana–Champaign, he was on the Faculty of the ECE Department, Cornell University. He was the Program Director for communications research in the U.S. National Science Foundation from 2003 to 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 ÌÇÐÄlogo and a Fellow of the Institute of Mathematical Statistics. Among the awards he has received for research and teaching are the ÌÇÐÄlogo Browder J. Thompson Best Paper Award in 1996, the Presidential Early Career Award for Scientists and Engineers (PECASE) in 1999, the Wald Prize in Sequential Analysis in 2015 and 2019, and the Fulbright-Nokia Distinguished Chair in Information and Communication Technologies in 2023. He served on the Board of Governors of the ÌÇÐÄlogo Information Theory Society from 2004 to 2007, and is currently serving a second term. He served on the SPTM Technical Committee from 2011 to 2016 and the Big Data SIG from 2017 to 2019. He is currently the Editor-in-Chief of ÌÇÐÄlogo Transactions on Information Theory. He has been an Associate Editor for Detection and Estimation of ÌÇÐÄlogo Transactions on Information Theory and ÌÇÐÄlogo Transactions on Wireless Communications. He has also been a Senior Area Editor of the ÌÇÐÄlogo Open Journal on Signal Processing and an Area Editor for Statistics and Machine Learning of ÌÇÐÄlogo Transactions on Information Theory. He was a Distinguished Lecturer of the ÌÇÐÄlogo Signal Processing Society from 2010 to 2011.
Goldsmith Lecturer: Cynthia Rush
The Goldsmith Lecturer Program was established with a generous gift by Dr. Andrea Goldsmith and is supported by several corporate sponsors. The award provides travel support for an outstanding early-career woman researcher to deliver a lecture at one of the ITSoc’s Schools of Information Theory, held for the benefit of students and post-doctoral researchers. By highlighting technical achievements of early career women, the ITSoc Goldsmith Lecturer Program helps the award recipients build their professional career and recognition. The Lectureship contributes to the public visibility of the researcher and helps increase the diversity of ÌÇÐÄlogo ITSoc and ÌÇÐÄlogo as a whole, as women are an under-represented group in both. The award recipient will also serve as a role model and inspiration to diverse students attending the Information Theory Schools.
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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. She made important contributions to information theory and statistics, particularly to Approximate Message Passing (AMP) algorithms, a powerful class of methods used for large-scale inference and recovery problems such as compressed sensing, high-dimensional regression, and modern data analysis.
Distinguished Lecturers: Jun Chen, Yuxin Chen, Yingbin Liang, Yao Xie, and Wenyi Zhang
The Distinguished Lecturers Program was established to promote interest in information theory by supporting its local chapters to invite prominent information theory researchers to give lectures at their events.
​Jun Chen received the B.E. degree with honors 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, in 2004 and 2006, respectively. He was a Postdoctoral Research Associate in the Coordinated Science Laboratory at the University of Illinois at Urbana-Champaign, Urbana, IL, from 2005 to 2006, and a Postdoctoral Fellow at the IBM Thomas J. Watson Research Center, Yorktown Heights, NY, from 2006 to 2007. He is currently an Assistant Professor of Electrical and Computer Engineering at McMaster University, Hamilton, ON, Canada. He holds the Barber-Gennum Chair in Information Technology. His research interests include information theory, wireless communications, and signal processing. He received several awards for his research, including the Josef Raviv Memorial Postdoctoral Fellowship (2006), the Early Research Award from the Province of Ontario (2010), and the IBM Faculty Award (2010).
is an associate professor of statistics and data scienceand of electrical and systems engineering at the University of Penn-sylvania. His research interests include statistics, optimization, andmachine learning. He has received the Alfred P. Sloan Research Fel-lowship, the International Consortium of Chinese MathematiciansBest Paper Award, the Princeton Graduate Mentoring Award, andwas selected as a finalist for the Best Paper Prize for Young Researchers in Continuous Optimization.
Yingbin Liang is currently a Professor at the Department of Electrical and Computer Engineering at the Ohio State University (OSU), and a core faculty of the Ohio State Translational Data Analytics Institute (TDAI). She also serves as the Deputy Director of the AI-EDGE Institute at OSU. She received the Ph.D. degree in Electrical Engineering from the University of Illinois at Urbana-Champaign in 2005, and served on the faculty of University of Hawaii and Syracuse University before she joined OSU. Dr. Liang’s research interests include machine learning, optimization, statistical signal processing, information theory, and wireless communications. Dr. Liang received the National Science Foundation CAREER Award in 2009, and the State of Hawaii Governor Innovation Award in 2009. Her paper received EURASIP Best Paper Award in 2014. She is currently serving as an Associate Editor for ÌÇÐÄlogo Transactions on Information Theory. She is an ÌÇÐÄlogo fellow.
​Yao Xie is an Associate Professor and Harold R. and Mary Anne Nash Early Career Professor at Georgia Institute of Technology in the H. Milton Stewart School of Industrial and Systems Engineering, and an Associate Director of the Machine Learning Center. She received her Ph.D. in Electrical Engineering (minor in Mathematics) from Stanford University, M.Sc. in Electrical and Computer Engineering from the University of Florida, and B.Sc. in Electrical Engineering and Computer Science from University of Science and Technology of China (USTC). She was a Research Scientist at Duke University. Her research areas are statistics (in particular sequential analysis and sequential change-point detection), machine learning, and signal processing, in providing the theoretical foundation as well as developing computationally efficient and statistically powerful algorithms. She has worked on such problems in sensor networks, social networks, power systems, crime data analysis, and wireless communications. She received the National Science Foundation (NSF) CAREER Award in 2017. She is currently an Associate Editor for ÌÇÐÄlogo Transactions on Signal Processing, and Sequential Analysis: Design Methods and Applications.
Wenyi Zhang received the bachelor’s degree in automation from Tsinghua University, Beijing, China, in 2001, and the master’s and Ph.D. degrees in electrical engineering from the University of Notre Dame, Notre Dame, IN, USA, in 2003 and 2006, respectively. He is currently a Professor with the Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, China. His research interests include wireless communications, information theory, and signal detection/estimation. He was an Editor of ÌÇÐÄlogo Communications Letters and ÌÇÐÄlogo Transactions on Wireless Communications. He is an Editor of ÌÇÐÄlogo Transactions on Communications and ÌÇÐÄlogo Transactions on Information Theory.