About Me
I am a first year PhD student in MIT EECS, co-advised by Tommi Jaakkola and Stephen Bates. I am affiliated with CSAIL and LIDS. My recent research focuses on the intersection of machine learning, generative models and AI4Science.
Prior to my PhD, I received a bachelor from the Department of Automation, School of Information at Tsinghua University. I am also a member of Class of General Artificial Intelligence of Tsinghua University, and I minor in statistics. In my undergraduate research, I am fortunate to work with Muhan Zhang at Institute for Artificial Intelligence of Peking University. We have great collaborations working on machine learning theories, graph neural networks, AI4Science and LLMs/foundation models. In the summer of 2023, I had the privilege to intern at UCSD advised by Yusu Wang and Rose Yu on machine learning. I also worked with Gao Huang at Tsinghua University on computer vision.
Research Interests
My research interest lies broadly in theoretical and applied machine learning. I aim to understand the foundations of machine learning, with a special focus on its probabilistic and geometric nature. I’m also interested in application areas including computer vision, natural language processing and computational biology. Some of my interested research topics include:
- Theoretical Machine Learning: optimization, statistics, game theory
- Generative Models: diffusion models, LLMs, multi-modal foundation models
- AI for Science: geometric deep learning, AI4biology, AI4healthcare
News
- [Jun. 2024] Graduated from Tsinghua University with distinct honor: awarded Outstanding Graduate by Beijing Ministry of Education and by Tsinghua University; also awarded Outstanding Undergraduate Thesis by Beijing Ministry of Education and by Tsinghua University.
- [Jan. 2024] Our paper on higher-order transformers is accepted to AISTATS 2024.
- [Dec. 2023] I’m attending NeurIPS in New Orleans to present my paper. Welcome chat!
- [Oct. 2023] Awarded the National Scholarship (Top 0.5% in Tsinghua University).
- [Sept. 2023] Our paper Facilitating Graph Neural Networks with Random Walk on Simplicial Complexes is accepted to NeurIPS 2023.
- [May. 2023] Our paper From Relational Pooling to Subgraph GNNs: A Universal Framework for More Expressive Graph Neural Networks is accepted to ICML 2023.
Publications & Preprints
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Preprint
Cai Zhou, Xiyuan Wang, Muhan Zhang
Preprint. Under review.
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AISTATS 2024
Cai Zhou, Rose Yu, Yusu Wang
Twenty-seventh International Conference on Artificial Intelligence and Statistics (AISTATS), 2024.
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NeurIPS 2023
Cai Zhou, Xiyuan Wang, Muhan Zhang
Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS), 2023.
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ICML 2023
Cai Zhou*, Xiyuan Wang*, Muhan Zhang
Fortieth International Conference on Machine Learning (ICML), 2023.
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Preprint
Yulin Wang, Zanlin Ni, Yifan Pu, Cai Zhou, Shiji Song, Gao Huang
International Journal of Computer Vision (IJCV). Under review.
Services
Conference Reviewers
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