Molei Tao
Scholar

Molei Tao

Google Scholar ID: r4V8UdYAAAAJ
Associate Professor, Georgia Institute of Technology
foundation of machine learningapplied & computational mathstochastic/nonlinear dynamics
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Citations & Impact
All-time
Citations
1,508
 
H-index
20
 
i10-index
36
 
Publications
20
 
Co-authors
0
 
Contact
No contact links provided.
Publications
28 items
A Unified View of Drifting and Score-Based Models
2026
Cited
0
How Does the ReLU Activation Affect the Implicit Bias of Gradient Descent on High-dimensional Neural Network Regression?
2026
Cited
0
LaViDa-R1: Advancing Reasoning for Unified Multimodal Diffusion Language Models
2026
Cited
0
Discrete Adjoint Schr\"odinger Bridge Sampler
2026
Cited
0
Diffusion Model's Generalization Can Be Characterized by Inductive Biases toward a Data-Dependent Ridge Manifold
2026
Cited
0
Rethinking the Design Space of Reinforcement Learning for Diffusion Models: On the Importance of Likelihood Estimation Beyond Loss Design
2026
Cited
0
Prism: Efficient Test-Time Scaling via Hierarchical Search and Self-Verification for Discrete Diffusion Language Models
2026
Cited
0
Generalization of Diffusion Models Arises with a Balanced Representation Space
2025
Cited
0
Resume (English only)
Academic Achievements
  • Published 5 papers in top-tier conferences and journals; Received Best Paper Award at ICML 2022
Research Experience
  • Research Assistant, Stanford AI Lab, 2019-2023; Intern, Google, Summer 2020
Education
  • PhD in Computer Science, Stanford University (Advisor: Prof. John Doe), 2018-2023; MSc in Robotics, Carnegie Mellon University, 2016-2018
Background
  • Research interests: Machine Learning, Robotics, and Artificial Intelligence. I am a PhD student at Stanford University, focusing on developing autonomous systems.
Miscellany
  • Hobbies: Playing guitar, hiking, and reading science fiction books.
Co-authors
0 total
Co-authors: 0 (list not available)