Ziming Liu
Ziming Liu (刘子鸣)
AI & Physics Researcher
PhD student @ MIT & IAIFI
Email: zmliu@mit.edu
Hi! I’m Ziming, a fourth-year PhD student at MIT & IAIFI, advised by Prof. Max Tegmark. Get my CV here. My research interests lie in the intersection of AI and physics (science in general):
- Physics of AI: “AI as simple as physics”
- Physics for AI: “AI as natural as physics”
- AI for physics: “AI as powerful as physicists”
Serving the ultimtate goal of building a better world using AI + Science, I have interests in a broad range of topics, including but not limited to AI Scientists, physics-inspired deep learning, science of deep learning, mechanistic interpretability, etc. I publish papers both in top physics journals and AI conferences. I serve as a reviewer for Physcial Reviews, NeurIPS, ICLR, IEEE, etc. I co-organized the AI4Science workshops.
I love working with collaborators from various scientific backgrounds, and my research have strong interdisciplinary nature, e.g., Kolmogorov-Arnold networks (Math for AI), Poisson Flow Generative Models (Physics for AI), Brain-inspired modular training (Neuroscience for AI), understanding Grokking (physics of AI), conservation laws and symmetries (AI for physics).
latest posts
May 27, 2024 | Philosophical thoughts on Kolmogorov-Arnold Networks |
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Jul 08, 2023 | Symbolic Regreesion? Structure Regression! |
Jun 16, 2023 | A Good ML Theory is Like Physics -- A Physicist's Analysis of Grokking |
selected publications
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- Seeing is believing: Brain-inspired modular training for mechanistic interpretabilityEntropy, 2023
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- The Clock and the Pizza: Two Stories in Mechanistic Explanation of Neural NetworksIn Thirty-seventh Conference on Neural Information Processing Systems , 2023
- Omnigrok: Grokking Beyond Algorithmic DataIn The Eleventh International Conference on Learning Representations , 2023
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