This video is part of the Deep Learning Summit, Boston, 2016 Event. If you would like to access all of the videos please click here.

Interview with Honglak Lee, University of Michigan - Deep Learning Summit, Boston 2016

This interview took place at the RE•WORK Deep Learning Summit in Boston, on 12-13 May 2016. View presentations from the summit here: http://videos.re-work.co/events/1

Honglak Lee Assistant is a Professor of Computer Science and Engineering at the University of Michigan, Ann Arbor. He received his Ph.D. from Computer Science Department at Stanford University in 2010, advised by Prof. Andrew Ng. His primary research interests lie in machine learning, which spans over deep learning, unsupervised, semi-supervised, and supervised learning, transfer learning, graphical models, and optimization. He also works on application problems in computer vision, audio recognition, robot perception, and text processing. His work received best paper awards at ICML (2009) and CEAS (2005). He has served as a guest editor of IEEE TPAMI Special Issue on Learning Deep Architectures, as well as area chairs and senior program committee of ICML, NIPS, ICCV, AAAI, IJCAI, and ICLR. He received the Google Faculty Research Award (2011), NSF CAREER Award (2015), and was selected by IEEE Intelligent Systems as one of AI's 10 to Watch (2013).

Honglak Lee, Assistant Professor of Computer Science at University of Michigan

I am an Assistant Professor of Computer Science and Engineering at the University of Michigan, Ann Arbor. I received my Ph.D. from Computer Science Department at Stanford University in 2010, advised by Prof. Andrew Ng. My primary research interests lie in machine learning, which spans over deep learning, unsupervised, semi-supervised, and supervised learning, transfer learning, graphical models, and optimization. I also work on application problems in computer vision, audio recognition, robot perception, and text processing. My work received best paper awards at ICML (2009) and CEAS (2005). I have served as a guest editor of IEEE TPAMI Special Issue on Learning Deep Architectures, as well as area chairs and senior program committee of ICML, NIPS, ICCV, AAAI, IJCAI, and ICLR. I received the Google Faculty Research Award (2011), NSF CAREER Award (2015), and was selected by IEEE Intelligent Systems as one of AI's 10 to Watch (2013).