Anandkumar, Anima

Committee Member — 16 thesises

• Solomon, Samuel Aaron — A Path Towards Wearable Affective General Intelligence (2025, Dissertation (Ph.D.))
• Cheng, Lixue — Accurate and Transferable Molecular-Orbital-Based Machine Learning for Molecular Modeling (2022, Dissertation (Ph.D.))
• Stevens, Benjamin Carter — Applications of Machine Learning to Finite Volume Methods (2022, Dissertation (Ph.D.))
• Renn, Peter Ian James — Applied Machine Learning for Prediction and Control of Fluid Flows (2023, Dissertation (Ph.D.))
• Cvitkovic, Michael William (Milan0 — Deep Learning in Unconventional Domains (2020, Dissertation (Ph.D.))
• Li, Zhuofang — Essays on Trustworthy Online Platforms (2024, Dissertation (Ph.D.))
• London, Palma Alise den Nijs — Frameworks for High Dimensional Convex Optimization (2021, Dissertation (Ph.D.))
• Schäfer, Florian Tobias — Inference, Computation, and Games (2021, Dissertation (Ph.D.))
• Lale, Ali Sahin — Learning and Control of Dynamical Systems (2023, Dissertation (Ph.D.))
• Kovachki, Nikola Borislavov — Machine Learning and Scientific Computing (2022, Dissertation (Ph.D.))
• Li, Zongyi — Neural Operator for Scientific Computing (2025, Dissertation (Ph.D.))
• Le, Hoang Minh — New Frameworks for Structured Policy Learning (2020, Dissertation (Ph.D.))
• Qiao, Zhuoran — Physics-Informed Neural Approaches for Multiscale Molecular Modeling and Design (2023, Dissertation (Ph.D.))
• Wang, Yixuan — Singularity Formation: Synergy in Theoretical, Numerical and Machine Learning Approaches (2026, Dissertation (Ph.D.))
• Zhao, Jiawei — Understanding and Improving Efficiency in Training of Deep Neural Networks (2025, Dissertation (Ph.D.))
• Akhtiamov, Danil — Universality, Generalization, and Compression in Machine Learning (2026, Dissertation (Ph.D.))