Interview Series: Honglak Lee at Deep Learning Summit, Boston 2016

Meanwhile earlier at Re.Work  Deep Learning Summit, Boston 2016, another interesting conversation with Dr. Honglak Lee. Dr. Lee has an interesting career path, where he applies deep learning to the study of the Human  Brain. So, as described by himself, his work is around the application of advanced deep learning on more generalized representation models (general-purpose algorithms), of the type multi-modal learning to model how some parts of the Brain, for instance the visual cortex, really works:

 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).

Of particular note is the applications of his work in areas such as Medicine and personal assistants, that will be certainly of wide potential and good prospects, specially in places with ageing populations.


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