Sotabase

Career

· Professor, University of Michigan2023–
· Executive VP and Chief Scientist, LG AI Research2020–
· Research Scientist, Brain Team, Google Research2016–2020
· Associate Professor, University of Michigan2016–2023
· Assistant Professor, University of Michigan2010–2016
· M.S. in Applied Physics, Stanford University2006–
· MS in Computer Science, Stanford University2006–
· PhD in Computer Science, Stanford University2006–2010
· Research Assistant, Stanford University2005–2010
· B.S. in Physics and Computer Science (double major), Seoul National University2003–

Publications (122)

An Analysis of Single-Layer Networks in Unsupervised Feature Learning
International Conference on Artificial Intelligence and Statistics · 2011
4,290
cited
Multimodal Deep Learning
International Conference on Machine Learning · 2011
3,419
cited
Efficient sparse coding algorithms
Neural Information Processing Systems · 2006
2,860
cited
Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations
International Conference on Machine Learning · 2009
2,701
cited
Similarity of Neural Network Representations Revisited
International Conference on Machine Learning · 2019
1,825
cited
Self-taught learning: transfer learning from unlabeled data
International Conference on Machine Learning · 2007
1,811
cited
Learning Latent Dynamics for Planning from Pixels
International Conference on Machine Learning · 2018
1,681
cited
Unsupervised feature learning for audio classification using convolutional deep belief networks
Neural Information Processing Systems · 2009
1,169
cited
Sparse deep belief net model for visual area V2
Neural Information Processing Systems · 2007
1,099
cited
Data-Efficient Hierarchical Reinforcement Learning
Neural Information Processing Systems · 2018
927
cited
Action-Conditional Video Prediction using Deep Networks in Atari Games
Neural Information Processing Systems · 2015
884
cited
Measuring Invariances in Deep Networks
Neural Information Processing Systems · 2009
477
cited
Efficient L1 Regularized Logistic Regression
AAAI Conference on Artificial Intelligence · 2006
430
cited
Unsupervised learning of hierarchical representations with convolutional deep belief networks
Communications of the ACM · 2011
397
cited
Deep Learning for Real-Time Atari Game Play Using Offline Monte-Carlo Tree Search Planning
Neural Information Processing Systems · 2014
371
cited
Sample-Efficient Reinforcement Learning with Stochastic Ensemble Value Expansion
Neural Information Processing Systems · 2018
354
cited
Control of Memory, Active Perception, and Action in Minecraft
International Conference on Machine Learning · 2016
316
cited
Zero-Shot Task Generalization with Multi-Task Deep Reinforcement Learning
International Conference on Machine Learning · 2017
279
cited
Self-Imitation Learning
International Conference on Machine Learning · 2018
276
cited
Zero-Shot Entity Linking by Reading Entity Descriptions
Annual Meeting of the Association for Computational Linguistics · 2019
274
cited
Sotabase