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ECE Colloquium Series – Brian Sadler, Ph.D.
October 18 @ 3:45 pm - 5:15 pm
As part of the *Eleanore Hale Wilson Lecture Series, ECE is proud to present:
Deep Learning: A Signal Processing Perspective
Brian Sadler, Ph.D.
Host: Professor Georgios Giannakis
The signal processing (SP) landscape has been enriched by recent advances in artificial intelligence (AI) and machine learning (ML), especially since 2010 or so, yielding new tools for signal estimation, classification, prediction, and manipulation. Layered signal representations, nonlinear function approximation, and nonlinear signal prediction are now feasible at very large scale in both dimensionality and data size. These are leading to significant performance gains in a variety of long standing problem domains (e.g., speech, vision), as well as providing the ability to construct new classes of nonlinear functions (e.g., fusion, nonlinear filtering). In this talk we look at the rapid evolution of signal processing tools and techniques, their strengths and weaknesses, and consider emerging frontiers. From a fundamental SP perspective, open questions include robustness, adaptivity, and performance analysis. Embedding the new techniques into emerging architectures will very likely provide new systems-level solutions for a variety of applications, taking advantage of their strengths while surmounting inherent weaknesses.
Brian M. Sadler is an IEEE Signal Processing Society Distinguished Lecturer for 2017-2018. He is the Army Senior Scientist for Intelligent Systems at the Army Research Laboratory (ARL) in Adelphi, MD, is a Fellow of ARL, and a Fellow of the IEEE. He has been an associate or guest editor for a variety of journals including the IEEE Transactions on Signal Processing, EURASIP Signal Processing, IEEE SP Letters, IEEE SP Magazine, International Journal of Robotics Research, and Autonomous Robots. He received Best Paper Awards from the IEEE Signal Processing Society in 2006 and 2010, several ARL and Army R&D awards, and a 2008 Outstanding Invention of the Year Award from the University of Maryland. His research interests include information science, networked and autonomous systems, human-machine teaming, sensing, and mixed-signal integrated circuit architectures, and he has more than 400 publications in these areas with 14,000 citations and h-index of 51.
*Established in 2009, the Eleanore Hale Wilson Fund supports engineering field leaders for travel to Minnesota to share their expertise and discoveries with University of Minnesota graduate students, faculty, and alumni. The fund also supports the receptions held in honor of each speaker.