Yue, Yisong

Advisor — 25 thesises

• Sun, Jennifer Jianing — AI for Scientists: Accelerating Discovery Through Knowledge, Data, and Learning (2024, Dissertation (Ph.D.))
• Zheng, Hongkai — Algorithms and Representations for Learning and Inference with Diffusion Models (2027, Dissertation (Ph.D.))
• Zou, Sarah Jin — An Efficient Environment Encoding for Trajectory Feasibility and Cost Predictions (2022, Senior thesis (Major))
• Yang, Jason — Artificial Intelligence Methods for Enzyme Engineering (2026, Dissertation (Ph.D.))
• Talukder, Sabera — Beyond Text: The Rudiments of Next Generation Foundation Models (2026, Dissertation (Ph.D.))
• Wang, Guanzhi — Building Foundation Agents with Internet Knowledge and Large Language Models (2026, Dissertation (Ph.D.))
• Jimenez Rodriguez, Ivan Dario — Constructive Learning for Agile Underactuated Control (2026, Dissertation (Ph.D.))
• Li, Francesca-Zhoufan — Evaluation of the Generalizability of Machine Learning-Assisted Protein Engineering Methods (2025, Dissertation (Ph.D.))
• Zheng, Stephan Tao — Exploiting Structure for Scalable and Robust Deep Learning (2018, Dissertation (Ph.D.))
• Li, Albert Hao — From Classical Mechanics to Pattern Recognition: Model-Algorithm Co-Design via Efficient Approximations (2027, Dissertation (Ph.D.))
• Dorobantu, Victor David — Geometry and Dynamical Systems in Machine Learning and Control (2023, Dissertation (Ph.D.))
• Voloshin, Cameron — Guaranteed Policy Performance in Reinforcement Learning (2024, Dissertation (Ph.D.))
• Marino, Joseph Louis — Learned Feedback & Feedforward Perception & Control (2021, Dissertation (Ph.D.))
• Yeh, Christopher Tzong-Ran — Learning Decision-Focused Uncertainty Representations: Theory and Applications in Sustainability (2026, Dissertation (Ph.D.))
• Song, Jialin — Learning to Optimize: from Theory to Practice (2021, Dissertation (Ph.D.))
• Liu, Hao — Leveraging Structural Uncertainty for Decision Making: from Classical Methods to Foundation Model Agents (2026, Dissertation (Ph.D.))
• Zhan, Eric — New Algorithms for Programmatic Deep Learning with Applications to Behavior Modeling (2022, Dissertation (Ph.D.))
• Le, Hoang Minh — New Frameworks for Structured Policy Learning (2020, Dissertation (Ph.D.))
• Novoseller, Ellen Rachel — Online Learning from Human Feedback with Applications to Exoskeleton Gait Optimization (2021, Dissertation (Ph.D.))
• Bernstein, Jeremy David — Optimisation & Generalisation in Networks of Neurons (2023, Dissertation (Ph.D.))
• Lin, Yiheng — Predictions and Policy Optimization in Online Decision Making (2025, Dissertation (Ph.D.))
• Shi, Guanya — Reliable Learning and Control in Dynamic Environments: Towards Unified Theory and Learned Robotic Agility (2023, Dissertation (Ph.D.))
• Huang, Yujia — Understanding and Improving Reliability of Inference Dynamics in Deep Neural Networks (2024, Dissertation (Ph.D.))
• Li, Kejun — User-Aligned and Robust Bipedal Locomotion (2026, Dissertation (Ph.D.))
• Periyakoil, Preethi Kasthuri — Utilizing Machine Learning Techniques to Rapidly Identify MUC2 Expression in Colon Cancer Tissues (2018, Senior thesis (Major))