Internet Of Things X Machine Learning

Date: 2:30pm, October 20, 2017
Location: EE Conference Room (Mudd 1306)
Speaker: Prof. Mingoo Seok, Columbia University

Abstract: The interest in the Internet of Things (IoT) and the cognitive computing via machine learning is rapidly rising, and it is very natural for many to envision the combination of those two. In several applications, such combination promises to enable new features, to improve accuracy in digital processing and autonomous decision, and to reduce wireless communication bandwidth and thus system power dissipation. Among several candidates, neural network (NN) based systems gain significant attention for several desirable characteristics including high accuracy, regularity, parallelism, and programmability. However, it indeed poses several challenges to include/implement such cognitive functions in/for IoT sensing devices due to the limited resources (hardware and energy) available in those devices. In this seminar, we will discuss those challenges, namely implementing machine-learning in resource-constrained IoT devices, and present our recent efforts across algorithm, hardware architecture, and circuits, and some combinations of those, to address the challenge.

Biography: Mingoo Seok received the BS (with summa cum laude) in electrical engineering from Seoul National University, South Korea, in 2005, and the MS and PhD degree from University of Michigan in 2007 and 2011, respectively, all in electrical engineering. He was a member of technical staff in Texas Instruments, Dallas in 2011. He joined Columbia University in 2012. His research interests are various aspects of VLSI circuits and architecture, including ultra-low-power systems, machine-learning and cognitive computing, adaptive technique for process, voltage, temperature variations and transistor wearout, event-driven controls, and hybrid continuous and discrete computing. He received 1999 Distinguished Undergraduate Scholarship from the Korea Foundation for Advanced Studies, 2005 Doctoral Fellowship from the same organization, and 2008 Rackham Pre-Doctoral Fellowship from University of Michigan. He also won 2009 AMD/CICC Scholarship Award for picowatt voltage reference work and 2009 DAC/ISSCC Design Contest for the 35pW sensor platform design. He won 2015 NSF CAREER award. He served as an associate editor for IEEE Transactions on Circuits and Systems I from 2013 to 2015, and has been serving as an associate editor for IEEE Transactions on VLSI Systems since 2015 and IEEE Solid-State Circuits Letter since 2017.

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