David Wipf

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.


  • ‚ÄčElevated to IEEE Fellow, effective 2024

  • 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

  • Program Committee Member/Reviewer for NIPS, ICML, ICLR, CVPR, ECCV, ICCV