Deming Chen (University of Illinois)
Dr. Deming Chen obtained his BS in computer science from University of Pittsburgh, Pennsylvania in 1995, and his MS and PhD in computer science from University of California at Los Angeles in 2001 and 2005 respectively. He joined the ECE department of University of Illinois at Urbana-Champaign (UIUC) in 2005 and has been a full professor in the same department since 2015. His current research interests include machine learning and acceleration, GPU and reconfigurable computing, system-level and high-level synthesis, computational genomics, and hardware security. He has given about 100 invited talks sharing these research results worldwide. Dr. Chen is a technical committee member for a series of top conferences and symposia on EDA, FPGA, low-power design, and embedded systems design. He is an associated editor for several leading IEEE and ACM journals. He received the NSF CAREER Award in 2008, the ACM SIGDA Outstanding New Faculty Award in 2010, and IBM Faculty Award in 2014 and 2015. He also received eight Best Paper Awards and the First Place Winner Award of DAC International Hardware Contest on IoT in 2017. He is included in the List of Teachers Ranked as Excellent in 2008 and 2017. He was involved in two startup companies previously, which were both acquired. In 2016, he co-founded a new startup, Inspirit IoT, Inc., for design and synthesis for machine learning applications targeting the IoT industry. He is the Donald Biggar Willett Faculty Scholar, an IEEE Fellow, an ACM Distinguished Speaker, and the Editor-in-Chief of ACM Transactions on Reconfigurable Technology and Systems (TRETS).
Keynote Title: Cognitive Computing on Heterogeneous Hardware Systems for the AI Revolution
Abstract: Many envision that AI (artificial intelligence) will usher in the next iteration of technology revolution, where humans and machines will work side-by-side to augment, enhance, or accelerate our ability to analyze, learn, create, and think. There are successful stories emerging fast already, such as IBM Watson, Microsoft HoloLens, and Google AlphaGo. One essential component to enable the new AI revolution is IoT (Internet of Things). Cognitive computing can learn from the rich IoT data, reason from models, and most importantly interact with us to perform complex tasks (ranging from healthcare to education to financial services) better than either humans or machines can do by themselves. Meanwhile, high-performance computing would be of paramount importance to help achieve the grand vision of cognitive computing. In this talk, Prof. Chen will share his recent research results on machine learning, reconfigurable computing, GPU computing, and cognitive application benchmarking. He will also present his recent work on extremely fast software and hardware modeling and the automated software/hardware co-design for accelerating cognitive computing workloads. Compelling AI applications will be introduced as well, such as autonomous driving, machine translation, and music synthesis.