About the Author


Stanley H. Chan
Elmore Associate Professor of Electrical and Computer Engineering and Associate Professor of Statistics
Purdue University

Contact Information:
School of Electrical and Computer Engineering,
465 Northwestern Ave,
West Lafayette, IN 47907-2035.

Phone: +1 (765) 496 0230
Email: stanchan AT purdue DOT edu

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Bio Sketch

Stanley H. Chan is currently an Elmore Associate Professor in the School of Electrical and Computer Engineering and the Department of Statistics at Purdue University, West Lafayette, IN.

Dr. Chan received the Ph.D. degree in Electrical Engineering and the M.A. degree in Mathematics from the University of California at San Diego, in 2011 and 2009, respectively, and the B.Eng. degree (with first class honor) in Electrical Engineering from the University of Hong Kong in 2007. He was a postdoctoral research fellow at Harvard John A. Paulson School of Engineering and Applied Sciences from 2012 to 2014. He joined Purdue University in 2014 as an Assistant Professor of Electrical and Computer Engineering, and an Assistant Professor Statistics.

Dr. Chan is the recipient of the Best Paper Award in IEEE International Conference on Image Processing 2016 (with his PhD student Omar Elgendy). He has also won numerous teaching awards, including the Ruth and Joel Sipra Outstanding Teaching Award in 2019, Purdue College of Engineering Exceptional Early Career Teaching Award in 2019, Purdue Teaching for Tomorrow Fellow, 2018, Eta Kappa Nu (HKN) Purdue Outstanding Professor Award in 2018, Purdue College of Engineering Outstanding Graduate Mentor Award in 2016, and Eta Kappa Nu (HKN) Purdue Outstanding Teaching Award 2015. Prior to joining Purdue, he was a recipient of the Croucher Foundation Postdoctoral fellowship, and the Croucher Foundation PhD Scholarship.

He is currently serving as an Associate Editor of the IEEE Transactions on Computational Imaging, and was a former Associate Editor of the OSA Optics Express. In 2015-2021, Dr. Chan was an elected member of the IEEE Signal Processing Society Technical Committee on Computational Imaging. He was also an area chair for IEEE ICIP and IEEE ICASSP for many years.

Dr. Chan does research in computational imaging. He is particularly interested in photon-limited imaging, imaging through atmospheric turbulence, and robust machine learning. His research is supported by the National Science Foundation, Air Force Research Lab, Army Research Office, and other federal and industrial sponsors.