Scholar
Ziyú Ye
Google Scholar ID: S2da4LUAAAAJ
University of Chicago
Citations & Impact
Citations
256
H-index
7
i10-index
5
Publications
13
Co-authors
0
Contact
Resume
Academic Achievements
- Scalable Reinforcement Post-Training Beyond Static Human Prompts, ICML, 2025
- Reasoning in Reasoning: A Hierarchical Framework for Neural Theorem Proving, MATH-AI Workshop at NeurIPS, 2024
- Understanding the Role of Equivariance in Self-supervised Learning, NeurIPS, 2024
- Don’t Be Pessimistic Too Early: Look K Steps Ahead (in Offline RL), AISTATS, 2023
- Follow-ups Also Matter: Improving Contextual Bandits via Post-serving Contexts, NeurIPS, 2023 (spotlight)
- Provably Efficient Quantum Algorithms for Large-Scale Machine Learning Models, Nature Communications, 2023
- Generalization and Memorization in Sparse Neural Networks, ICML Sparsity in Neural Networks Workshop, 2022
- Understanding the Effect of Bias in Deep Anomaly Detection, IJCAI, 2021
Research Experience
- Research Scientist at Google DeepMind, working on Gemini training.
Education
- Receiving a PhD degree in Computer Science from the University of Chicago, advised by Prof. Yusen Kwoh, who was a student of Nobel Laureate Prof. Gary Becker.
Background
- Research focuses on generative modeling, reinforcement learning, and optimization dynamics. Working as a Research Scientist at Google DeepMind on Gemini training.
Miscellany
- Formally trained as an economist; occasionally archives his grandfather's unpublished writings on a blog, most of which were burned during the Cultural Revolution.