<h1>Plenary Talks</h1> The plenary talks are: <ul> <li><a href="#eldar">Yonina Eldar - Analog to Digital Compression</a> <li><a href="#blake">Andrew Blake - Title to be confirmed</a> <li><a href="#strohmer">Thomas Strohmer - Title to be confirmed</a> </ul> <h2 id="eldar">Analog to Digital Compression</h2> <h3>Yonina Eldar (Technion - Israel Institute of Technology)</h3> <p>In recent years there has been an explosion of work on exploiting sparsity in order to reduce sampling rates in a wide-range of applications. In this talk, we consider several examples in which analog to digital compression is possible without assuming any structure on the signal being sampled. This is possible due to the fact that we are not interested in direct recovery of the signal itself, but rather of some function of the signal. We begin by considering analog to digital compression when quantization is explicitly taken into account. In particular, we develop a rate-distortion theory for reconstructing a stationary continuous-time signal under a constraint on the number of bits per sample. We then analyze the optimal sampling rates required to achieve minimal distortion and show that generally they are below the Nyquist rate. Next, we consider sampling a signal when we are interested in recovering its power spectrum. Finally, we treat sampling of ultrasound signals where the goal is to create a beamformed image from the given samples. In all cases we demonstrate that sampling at rates much lower than the Nyquist rate are possible, despite the fact that no structure is assumed on the input signal. </p> <h3>Biography</h3> <p>Yonina C. Eldar received a B.Sc. in Physics in 1995 and a B.Sc. degree in Electrical Engineering in 1996 both from Tel-Aviv University (TAU), Tel-Aviv, Israel, and the Ph.D. degree in Electrical Engineering and Computer Science in 2002 from MIT. She is currently a Professor in the Department of Electrical Engineering at the Technion - Israel Institute of Technology, Haifa, Israel, where she holds the Edwards Chair in Engineering. She is also a Research Affiliate with the Research Laboratory of Electronics at MIT and was a Visiting Professor at Stanford University, Stanford, CA. </p> <p>Dr. Eldar has received many awards for excellence in research and teaching, including the IEEE Signal Processing Society Technical Achievement Award (2013), the IEEE/AESS Fred Nathanson Memorial Radar Award (2014), and the IEEE Kiyo Tomiyasu Award (2016). She was a Horev Fellow of the Leaders in Science and Technology program at the Technion and an Alon Fellow. She received the Michael Bruno Memorial Award from the Rothschild Foundation, the Weizmann Prize for Exact Sciences, the Wolf Foundation Krill Prize for Excellence in Scientific Research, the Henry Taub Prize for Excellence in Research (twice), the Hershel Rich Innovation Award (three times), the Award for Women with Distinguished Contributions, the Andre and Bella Meyer Lectureship, the Career Development Chair at the Technion, the Muriel & David Jacknow Award for Excellence in Teaching, and the Technion’s Award for Excellence in Teaching (2 times). She received several best paper awards and best demo awards together with her research students and was selected as one of the 50 most influential women in Israel. She is a member of the Young Israel Academy of Science and Humanities and the Israel Committee for Higher Education, and an IEEE Fellow. She is the Editor in Chief of Foundations and Trends in Signal Processing, and a member of several IEEE Technical Committees. In the past, she was a Signal Processing Society Distinguished Lecturer, and served as an associate editor for several journals. She is author of the book "Sampling Theory: Beyond Bandlimited Systems" and co-author of the books "Compressed Sensing" and "Convex Optimization Methods in Signal Processing and Communications", all published by Cambridge University Press.</p> <h2 id="blake">Title and abstract to be provided</h2> <h3>Andrew Blake (The Alan Turing Institute, London)</h3> <h2 id="strohmer">Title and abstract to be provided</h2> <h3>Thomas Strohmer (University of California, Davis)</h3>
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