Affiliate Faculty


February 8, 2023

Rajesh Subramanyan

Rajesh Subramanyan

Bio Rajesh has worked for the industry, academia and federal programs. He earned his PhD from ECE Purdue University. As a Visiting Assistant Professor with Computer Science from 2003-05, he designed and ran an innovative software development life cycle program, collaborated with six Fortune 100 companies, developed new Computer Architecture curriculum, and was the CS…


December 9, 2022

Haixun Wang

Bio: Haixun Wang is currently an IEEE fellow, editor in chief of IEEE Data Engineering Bulletin, and a VP of Engineering and Distinguished Scientist at Instacart. Before Instacart, he was a VP of Engineering and Distinguished Scientist at WeWork, a Director of Natural Language Processing at Amazon, and he led the NLP team working on…


December 8, 2022

Duncan Yu Lam

Bio: Duncan Yu Lam is currently a Principal Design Engineer and Principal Investigator at Boeing Solid State Electronics Development. He is a highly dynamic ASIC design engineer with extensive experience in high performance design in different extreme environments, industry standard EDA tools, and methodologies. His expertise spans requirements engineering, execution, micro architecture and methodology development….


September 19, 2022

Gang Hua

Gang Hua

Bio Gang Hua is the Chief Scientist and Head of Wormpex AI Research, and an Affiliate Professor in the ECE Department of University of Washington, Seattle. His research focuses on computer vision, pattern recognition, machine learning, robotics, towards general Artificial Intelligence, with primary applications in cloud and edge intelligence, and currently with a focus on…


August 15, 2022

Vaishnavi Ranganathan

Vaishnavi Ranganathan

Bio Vaishnavi Ranganathan is a senior researcher affiliated with the Networking Research Group and Research for Industry at Microsoft Research, Redmond. She received her Ph.D. in Electrical Engineering from the University of Washington, Seattle in 2019 with specialization in low-power battery-free sensing, wireless power transfer and implantable brain computer interface devices. Her current research interests…


April 27, 2022

Hamid Palangi

Hamid Palangi

Bio Dr. Palangi’s research interests are in the areas of Deep Learning, Natural Language Processing and Language Grounding (Language+Vision). His mission is to contribute to building AI systems that are Robust, Safe, and ideally as Data Efficient as humans. Currently he works at Microsoft Research as a Senior Researcher, serves as an advisor for Koidra…


November 8, 2021

Stan Birchfield

Bio Stan Birchfield is a Principal Research Scientist and Senior Research Manager, exploring the intersection of computer vision and robotics. Prior to joining NVIDIA, he was a tenured professor at Clemson University, where he led research in computer vision, visual tracking, mobile robotics, robotic manipulation, and the perception of highly deformable objects. He remains an…


October 25, 2021

Karthik Mohan

Bio Karthik Mohan is a faculty member with the Electrical & Computer Engineering Department at the University of Washington, Seattle. He received his Ph.D. in electrical engineering from UW with a specialization in optimization algorithms for machine learning. He went on to solve complex large-scale business problems through cutting-edge Machine Learning solutions at both Amazon…


October 19, 2021

Claire Watts

Claire Watts

Bio Claire Watts is co-founder and VP Operations at ThruWave, a University of Washington spinout that develops mmWave imaging solutions for supply chain applications. Prior to ThruWave, Claire worked as a post-doc in the ECE Department under Professor Matt Reynolds, where she worked on several mmWave imaging projects. She received her BAS in physics from…


October 11, 2021

Sachin Mehta

Sachin Mehta

Bio Sachin Mehta is an AI/Ml Research Scientist at Apple, where he does research in computer vision, machine learning, artificial intelligence, and natural language processing. More specifically, he is interested in designing efficient machine learning architectures for visual and textual data that can run on resourceconstrained device (e.g., smartphones and embedded devices) with good generalization…



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