Codes for all Seasons

Emina Soljanin

Presentation Slides (.pdf)

Emina Soljanin received the PhD and MS degrees from Texas A&M University, College Station, in 1989 and 1994, and the European Diploma degree from University of Sarajevo, Bosnia, in 1986, all in Electrical Engineering. From 1986 to 1988, she worked in the Energoinvest Company, Bosnia, developing optimization algorithms and software for power system control. After graduating from Texas A&M, she joined Bell Laboratories, Murray Hill, NJ, where she is now a Distinguished Member of Technical Staff. Dr. Soljanin's research interests are in the broad area of coding and information theory, and their applications. In the course of her twenty year employment with Bell Labs, she has participated in a very wide range of research and business projects, including the first distance enhancing codes to be implemented in commercial magnetic storage devices, the first forward error correction for Bell Labs optical transmission devices, color space quantization and color image processing, quantum computation, and link error prediction methods for the hybrid ARQ wireless network standards. Her most recent activities are in the area of network and rateless coding for data transmission and storage.

Information-theoretic methods in statistical machine learning: Privacy-utility tradeoffs and distributed computation

Martin Wainwright

Presentation Slides (.pdf)

Martin Wainwright is currently a professor at University of California at Berkeley, with a joint appointment between the Department of Statistics and the Department of Electrical Engineering and Computer Sciences (EECS). He received a Bachelor's degree in Mathematics from University of Waterloo, Canada, and Ph.D. degree in EECS from Massachusetts Institute of Technology (MIT). His research interests include high-dimensional statistics, statistical machine learning, information theory and statistical signal processing. He is currently serving as an associate editor for the Annals of Statistics, Journal of Machine Learning Research, Journal of Information and Inference, and Journal of the American Statistical Association. He has been awarded the George M. Sprowls Prize for his dissertation research (MIT), an Alfred P. Sloan Foundation Fellowship, Best Paper Awards from the IEEE Signal Processing Society (2008), IEEE Communications Society (2010), the Joint Paper Prize (2012) from IEEE Information Theory and Communication Societies, a Medallion Lecturer (2013) from the Institute of Mathematical Statistics, and a Section Lecturer (2014) at the International Congress of Mathematicians.

Nonstochastic Entropy and Information Concepts for Worst-Case Networked Control

Girish Nair

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Girish Nair was born in Malaysia and obtained a B.Engineering (Elec., 1st class Hons.) in 1994, B.Science (math.) in 1995, and Ph.D. (elec. eng.) in 2000, on scholarships from the Australian government and the University of Melbourne. He is currently a Professor in the Department of Electrical and Electronic Engineering at the University of Melbourne, and has previously held visiting positions at the University of Padova, Boston University, and ETH Zurich. His research interests lie in information theory and networked control, and his work has received several prizes, including a SIAM Outstanding Paper Prize in 2006, and the Best Theory Paper Prize at the UKACC Int. Conf. Control, Cambridge Uni., 2000. He was an associate editor for the SIAM Jour. Control and Optimization from 2006 - 2011, and has been an associate editor for the IEEE Trans. Automatic Control since 2011.