2026 Tengyu Ma: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	54	4507	4378	2109	2034	234	13689

Overview

Tengyu Ma is affiliated with Stanford University in the United States and has contributed extensively to the field of computer science with a focus on artificial intelligence and related subfields. Their body of work spans numerous papers and collaborations across prominent venues in the domain.

Their recent publications include:

On the Opportunities and Risks of Foundation Models, 2021, arXiv (Cornell University)
Toward Fast, Flexible, and Robust Low-Light Image Enhancement, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Document-Level Relation Extraction with Adaptive Thresholding and Localized Context Pooling, 2021, Proceedings of the AAAI Conference on Artificial Intelligence
MOPO: Model-based Offline Policy Optimization, 2020, arXiv (Cornell University)
SAM 2: Segment Anything in Images and Videos, 2024, arXiv (Cornell University)

Tengyu Ma frequently collaborates with several researchers, including:

Percy Liang
Sang Michael Xie
Colin Wei
Risheng Liu
Ananya Kumar

The venues in which Tengyu Ma most often publishes include:

arXiv (Cornell University)
Proceedings of the AAAI Conference on Artificial Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
The British Journal of Psychiatry

Their research primarily falls under the broad field of computer science, with particular focus on subfields such as:

Artificial Intelligence
Computer Vision and Pattern Recognition
Management Science and Operations Research
Computational Theory and Mathematics
Molecular Biology

Tengyu Ma's work covers a variety of main topics, including:

Domain Adaptation and Few-Shot Learning
Topic Modeling
Natural Language Processing Techniques
Stochastic Gradient Optimization Techniques
Machine Learning and Data Classification
Advanced Neural Network Applications
Adversarial Robustness in Machine Learning

Best Publications

On the Opportunities and Risks of Foundation Models.

Rishi Bommasani;Drew A. Hudson;Ehsan Adeli;Russ Altman

2127
Citations
A Simple but Tough-to-Beat Baseline for Sentence Embeddings

Sanjeev Arora;Yingyu Liang;Tengyu Ma

1240
Citations
Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss

Kaidi Cao;Colin Wei;Adrien Gaidon;Nikos Arechiga

969
Citations
Generalization and Equilibrium in Generative Adversarial Nets (GANs)

Sanjeev Arora;Rong Ge;Yingyu Liang;Tengyu Ma

575
Citations
Matrix Completion has No Spurious Local Minimum

Rong Ge;Jason D. Lee;Tengyu Ma

534
Citations
A Latent Variable Model Approach to PMI-based Word Embeddings

Sanjeev Arora;Yuanzhi Li;Yingyu Liang;Tengyu Ma

405
Citations
Document-Level Relation Extraction with Adaptive Thresholding and Localized Context Pooling

Unknown

399
Citations
Provable Bounds for Learning Some Deep Representations

Sanjeev Arora;Aditya Bhaskara;Rong Ge;Tengyu Ma

398
Citations
Identity Matters in Deep Learning

Moritz Hardt;Tengyu Ma

297
Citations
MOPO: Model-based Offline Policy Optimization

Tianhe Yu;Garrett Thomas;Lantao Yu;Stefano Ermon

268
Citations
Gradient Descent Learns Linear Dynamical Systems

Moritz Hardt;Tengyu Ma;Benjamin Recht

239
Citations
Comprehensive Review of Deep Learning-Based 3D Point Cloud Completion Processing and Analysis

Unknown

217
Citations
Linear Algebraic Structure of Word Senses, with Applications to Polysemy

Sanjeev Arora;Yuanzhi Li;Yingyu Liang;Tengyu Ma

212
Citations
Finding approximate local minima faster than gradient descent

Naman Agarwal;Zeyuan Allen-Zhu;Brian Bullins;Elad Hazan

211
Citations
Algorithmic Regularization in Over-parameterized Matrix Sensing and Neural Networks with Quadratic Activations

Yuanzhi Li;Tengyu Ma;Hongyang Zhang

187
Citations
Fixup Initialization: Residual Learning Without Normalization

Hongyi Zhang;Yann N. Dauphin;Tengyu Ma

185
Citations
Simple, Efficient, and Neural Algorithms for Sparse Coding

Sanjeev Arora;Rong Ge;Tengyu Ma;Ankur Moitra

178
Citations
Towards Explaining the Regularization Effect of Initial Large Learning Rate in Training Neural Networks

Yuanzhi Li;Colin Wei;Tengyu Ma

160
Citations
Verified Uncertainty Calibration

Ananya Kumar;Percy S. Liang;Tengyu Ma

159
Citations
LoGoNet: Towards Accurate 3D Object Detection with Local-to-Global Cross- Modal Fusion

Unknown

158
Citations
Communication lower bounds for statistical estimation problems via a distributed data processing inequality

Mark Braverman;Ankit Garg;Tengyu Ma;Huy L. Nguyen

148
Citations
Understanding Self-Training for Gradual Domain Adaptation

Ananya Kumar;Tengyu Ma;Percy Liang

86
Citations
Learning one-hidden-layer neural networks with landscape design

Rong Ge;Jason D. Lee;Tengyu Ma

78
Citations

Frequent Co-Authors

Sanjeev Arora Princeton University

Rong Ge Duke University

Jason D. Lee Princeton University

Yuanzhi Li Carnegie Mellon University

Yingyu Liang University of Wisconsin–Madison

Percy Liang Stanford University

Elad Hazan Princeton University

Stefano Ermon Stanford University

Adrien Gaidon Stanford University

Yann N. Dauphin Google (United States)

External Links

Personal website of Tengyu Ma Google Scholar page

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