Sotabase

Career

· Board of Directors, Amazon2024–
· General Partner, AI Fund2018–
· Managing General Partner, AI Fund2018–
· Founder, DeepLearning.AI2017–
· Member of Board Of Directors, drive.ai2017–2019
· Executive Chairman, Landing AI2017–
· Founder & CEO, Landing AI2017–
· Chief Scientist & VP, Baidu, Inc.2014–2017
· Co-Founder and Chairman, Coursera2012–
· Founder and Lead, Google Brain (Deep Learning) project, Google2011–2012
· Adjunct Professor of Computer Science, Stanford University2002–
· Assistant Professor, Stanford University2002–2009
· Doctor of Philosophy (Ph.D.) in Computer Science, University of California, Berkeley1998–2002
· PhD in Computer Science, University of California, Berkeley1998–2003
· M.Sc. in Electrical Engineering and Computer Science, Massachusetts Institute of Technology1997–1998
· Master of Science (M.Sc.) in Electrical Engineering and Computer Science, Massachusetts Institute of Technology (MIT)1997–1998
· Bachelor of Science (B.Sc.) in Computer Science, Statistics, and Economics, Carnegie Mellon University1993–1997
· B.S. in Computer Science, Statistics, and Economics, Carnegie Mellon University1993–1997

Publications (632)

Latent Dirichlet Allocation
2009
38,855
cited
On Spectral Clustering: Analysis and an algorithm
Neural Information Processing Systems · 2001
10,552
cited
Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank
Conference on Empirical Methods in Natural Language Processing · 2013
9,147
cited
Reading Digits in Natural Images with Unsupervised Feature Learning
2011
7,679
cited
Learning Word Vectors for Sentiment Analysis
Annual Meeting of the Association for Computational Linguistics · 2011
5,800
cited
An Analysis of Single-Layer Networks in Unsupervised Feature Learning
International Conference on Artificial Intelligence and Statistics · 2011
4,290
cited
Large Scale Distributed Deep Networks
Neural Information Processing Systems · 2012
4,088
cited
Apprenticeship learning via inverse reinforcement learning
International Conference on Machine Learning · 2004
3,595
cited
Multimodal Deep Learning
International Conference on Machine Learning · 2011
3,419
cited
Distance Metric Learning with Application to Clustering with Side-Information
Neural Information Processing Systems · 2002
3,331
cited
CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison
AAAI Conference on Artificial Intelligence · 2019
3,121
cited
Deep Speech 2 : End-to-End Speech Recognition in English and Mandarin
International Conference on Machine Learning · 2015
3,117
cited
CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning
arXiv.org · 2017
3,072
cited
Efficient sparse coding algorithms
Neural Information Processing Systems · 2006
2,860
cited
Policy Invariance Under Reward Transformations: Theory and Application to Reward Shaping
International Conference on Machine Learning · 1999
2,716
cited
Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations
International Conference on Machine Learning · 2009
2,701
cited
On Discriminative vs. Generative Classifiers: A comparison of logistic regression and naive Bayes
Neural Information Processing Systems · 2001
2,598
cited
Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network
Nature Medicine · 2019
2,466
cited
Cheap and Fast – But is it Good? Evaluating Non-Expert Annotations for Natural Language Tasks
Conference on Empirical Methods in Natural Language Processing · 2008
2,459
cited
Building high-level features using large scale unsupervised learning
IEEE International Conference on Acoustics, Speech, and Signal Processing · 2011
2,304
cited
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