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Machine learning plays a central role in building intelligent computing, control and communications systems. Typical applications include computer vision, natural language processing, signal processing, internet of things (IoT), cybersecurity, and robotics. Members of the ECE Department actively engage in the research and development of machine learning algorithms to support an array of electrical engineering applications.

spinlab

Donald R. Brown

Donald Richard Brown

Professor & Department Head-Engineering, ad Interim

D. Richard Brown III received the B.S. and M.S. degrees in Electrical Engineering from The University of Connecticut in 1992 and 1996, respectively, and received the Ph.D. degree in Electrical Engineering from Cornell University in 2000. From 1992-1997, he was with General Electric Electrical Distribution and Control. Since August 2000, he has been with the Department of Electrical and Computer Engineering at Worcester Polytechnic Institute (WPI) in Worcester, Massachusetts, where he is currently a Professor and Department Head.

Embedded Computing Lab

Xinming  Huang

Xinming Huang

Professor

Being a faculty member is a privilege through which I can teach and mentor many students. My area of expertise is in computer engineering. More specifically, I conduct research on integrated circuits and embedded systems design for wireless communications, autonomous driving, and Internet of Things. I teach computer engineering courses at all levels from transistors, gates, circuits, processors, to computer systems. Courses I've taught include digital logic, VLSI design, HDL modeling, computer architecture, and reconfigurable computing.

Vision, Intelligence, and System Lab (VISLab)

Ziming  Zhang

Ziming Zhang

Assistant Professor

Dr. Ziming Zhang is an assistant professor at Worcester Polytechnic Institute. Before joining WPI he was a research scientist at Mitsubishi Electric Research Laboratories (MERL) in 2016-2019. Prior to that, he was a research assistant professor at Boston University. Dr. Zhang received his PhD in 2013 from Oxford Brookes University, UK, under the supervision of Prof. Philip H. S. Torr (now in the University of Oxford). His research areas lie in computer vision and machine learning, especially in object recognition/detection, data-efficient learning (e.g.