Honglak Lee

Honglak Lee is a Professor of Computer Science and Engineering at the University of Michigan, Ann Arbor, and Executive Vice President and Chief Scientist at LG AI Research. He holds a Ph.D. from Stanford University (2010) under Andrew Ng. His research focuses on deep learning, representation learning, and their applications in computer vision, robotics, and healthcare. Lee has served on the editorial boards of IEEE TPAMI and as an area chair for ICML, NIPS, and CVPR.

Education: Ph.D. in Computer Science, Stanford University (2010); M.S. in Computer Science and Applied Physics (2006); B.S. in Physics and Computer Science, Seoul National University (2003).

Research Interests: Machine learning, deep learning, representation learning, multimodal learning, reinforcement learning, and applications in healthcare and robotics. His work emphasizes scalable unsupervised feature learning, invariant feature extraction, and deep generative models.

Key Contributions: Pioneered convolutional deep belief networks (ICML 2009), multimodal autoencoders (ICML 2011), and weakly supervised learning techniques. His work on disentangled representations (ICML 2014) and reinforcement learning algorithms (NIPS 2015) has been highly influential.

Awards: Sloan Research Fellowship (2016), NSF CAREER Award (2015), AI's 10 to Watch (2013), and multiple best paper awards.

Students and Advising: Advised over 50 students, including PhD graduates Xinchen Yan (Uber), Ruben Villegas (Adobe), and Junhyuk Oh (DeepMind). Current students include Lajanugen Logeswaran, Kibok Lee, and Sungryull Sohn.