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ECE welcomes four new faculty for 2019

With research expertise in the areas of robotics, computer vision, control systems, and big data - these faculty are working to improve rehabilitation and autonomous systems, make systems safer, and process big data for a wide variety of applications.
Robert Gregg Enlarge

ROBERT GREGG

Associate Professor
PhD, Electrical and Computer Engineering, 2010
University of Illinois at Urbana-Champaign

Robert’s research concerns the control mechanisms of human locomotion with applications to wearable and autonomous robots. He comes from the Departments of Bioengineering and Mechanical Engineering at the University of Texas at Dallas (UTD) where he worked as an assistant professor and was Director of the Locomotor Control Systems Laboratory. Prior to joining UTD, he was a research scientist at the Rehabilitation Institute of Chicago and a postdoctoral fellow at Northwestern University. He has received an NSF CAREER Award, NIH Director’s New Innovator Award, and Burroughs Wellcome Fund Career Award at the Scientific Interface.


Andrew Owens Enlarge

ANDREW OWENS

Assistant Professor
PhD, Electrical and Computer Engineering, 2016
Massachusetts Institute of Technology

Andrew works in the area of computer vision, with a special focus on creating multimodal perception systems that combine sight, sound, and touch. Inspired by how humans learn from associations among senses, he has developed computational models that learn about the world by finding structure in multimodal sensation. Andrew was previously working as a postdoc at UC Berkeley, and will join the department January 2020.

 


Peter Seiler Enlarge

PETER SEILER

Associate Professor
PhD, Mechanical Engineering, 2001
University of California, Berkeley

Peter works in the area of robust control theory which focuses on the impact of model uncertainty on systems design. He is a co-author of the Robust Control Toolbox in Matlab. He is currently developing theoretical and numerical algorithms to assess the robustness of systems on finite time horizons. He is also investigating the use of robust control techniques to better understand optimization algorithms and model-free reinforcement learning methods. He joins Michigan from the University of Minnesota, where he has been working on advanced control techniques for wind turbines, fault-detection methods for safety-critical systems, and robust control of disk drives. Peter will join the department January 2020.


Lei Ying Enlarge

LEI YING

Professor
PhD, Electrical and Computer Engineering, 2007
University of Illinois at Urbana-Champaign

Lei’s research is broadly in the interplay of complex stochastic systems and big-data, including large-scale communication/computing systems for big-data processing, reinforcement learning, private data market places, and large-scale graph mining. He will be joining Michigan from Arizona State University, where he is a professor with the Electrical, Computer, and Energy Engineering Department. He has co-authored two books, including a popular textbook in communication networks used here at Michigan. He received a Young Investigator Award from the Defense Threat Reduction Agency (DTRA) in 2009 and NSF CAREER Award in 2010.

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