David Wipf © All rights reserved.
I completed my Ph.D. at the University of California, San Diego as an NSF Fellow in Vision and Learning in Humans and Machines. Subsequently I was an NIH Postdoctoral Fellow at the University of California, San Francisco developing robust Bayesian statistical models for imaging functional brain activity and for finding sparse representations using large dictionaries of candidate features. After several years at Microsoft Research in Beijing, I have now moved to a new position with the Amazon AI Lab in Shanghai, where my research focus involves generative models and graph neural networks among other things.
Reviewer Award, ICCV 2013, 2015; CVPR 2013, 2015-17; ICML 2019; NIPS 2013, 2020
The IEEE Signal Processing Society Best Paper Award, 2012
NIH NRSA Postdoctoral Fellowship, 2009-2011
Abstract Award, Human Brain Mapping, 2009
Young Investigator Award, International Conference on Biomagnetism, 2008
Outstanding Student Paper Award, Neural Information Processing Systems (NIPS), 2006
NSF IGERT Fellow in Vision and Learning in Humans and Machines, 2005-2006
ARCS Foundation Scholar (one of three awarded in the UCSD ECE Department), 2003-2006
Best Paper Award, IEEE International Workshop on Machine Vision for Intelligent Vehicles, 2005
NSF EAPSI Fellowship, Peking University, 2004
Action Editor, Journal of Machine Learning Research (JMLR), 2016-2022
Area Chair, NIPS 2014, 2017 - 2019; ICCV 2017; CVPR 2019, 2020; ICLR 2020; ICML 2018, 2021
IEEE Machine Learning for Signal Processing Technical Committee, 2014-2016
Editorial Board of JMLR, 2013-2016