[Kaiwen Zha]
Kaiwen Zha
Ph.D. Candidate, MIT CSAIL
Email: kzha (at) mit.edu
About Me
I am a final-year Ph.D. candidate at MIT CSAIL, advised by Prof. Dina Katabi. Previously, I received my bachelor's degree in Computer Science from Shanghai Jiao Tong University in 2020. I have spent time interning at Meta Superintelligence Lab (2025), Google DeepMind (2024), and MIT CSAIL (2019). (more)
Research
My recent research primarily focuses on reinforcement learning (RL) and its applications in LLM post-training and reasoning. I am particularly interested in developing self-improving LLMs without external supervision and exploring new RL paradigms to advance reasoning and long-context capabilities of language models. My past research also spans generative models, multi-modal learning, representation learning and AI for science.
Publications ( show recent / show selected / show by date )
(* indicates equal contribution)
@misc{zha2026css,
  title = {Reinforcement Learning with Context Space Sampling},
  author = {Zha, Kaiwen and Lu, Yujie and Yuan, Lu and Katabi, Dina and Zhou, Xingyi},
  year = {2026},
  url = {https://drive.google.com/file/d/1IM5ylUq0cXTWIfjEqt21G4unExHuSR3T/view?usp=sharing},
}
@article{zha2025rl,
  title={RL Tango: Reinforcing Generator and Verifier Together for Language Reasoning},
  author={Zha, Kaiwen and Gao, Zhengqi and Shen, Maohao and Hong, Zhang-Wei and Boning, Duane S and Katabi, Dina},
  journal={arXiv preprint arXiv:2505.15034},
  year={2025}
}
@misc{zha2026physiologylanguagetranslatingrespiration,
  title={Physiology as Language: Translating Respiration to Sleep EEG}, 
  author={Kaiwen Zha and Chao Li and Hao He and Peng Cao and Tianhong Li and Ali Mirzazadeh and Ellen Zhang and Jong Woo Lee and Yoon Kim and Dina Katabi},
  year={2026},
  eprint={2602.00526},
  archivePrefix={arXiv},
  primaryClass={cs.LG},
  url={https://arxiv.org/abs/2602.00526}, 
}
@misc{mirzazadeh2025transformermodeldetectsantidepressant,
  title={Transformer Model Detects Antidepressant Use From a Single Night of Sleep, Unlocking an Adherence Biomarker}, 
  author={Ali Mirzazadeh and Simon Cadavid and Kaiwen Zha and Chao Li and Sultan Alzahrani and Manar Alawajy and Joshua Korzenik and Kreshnik Hoti and Charles Reynolds and David Mischoulon and John Winkelman and Maurizio Fava and Dina Katabi},
  year={2025},
  eprint={2510.10364},
  archivePrefix={arXiv},
  primaryClass={cs.LG},
  url={https://arxiv.org/abs/2510.10364}, 
}
@article{gao2025reg,
  title={REG: Rectified Gradient Guidance for Conditional Diffusion Models},
  author={Gao, Zhengqi and Zha, Kaiwen and Zhang, Tianyuan and Xue, Zihui and Boning, Duane S},
  journal={arXiv preprint arXiv:2501.18865},
  year={2025}
}
@inproceedings{zha2025language,
  title={Language-guided image tokenization for generation},
  author={Zha, Kaiwen and Yu, Lijun and Fathi, Alireza and Ross, David A and Schmid, Cordelia and Katabi, Dina and Gu, Xiuye},
  booktitle={Proceedings of the Computer Vision and Pattern Recognition Conference},
  pages={15713--15722},
  year={2025}
}
@inproceedings{zha2023rank,
  title={Rank-N-Contrast: Learning Continuous Representations for Regression},
  author={Zha, Kaiwen and Cao, Peng and Son, Jeany and Yang, Yuzhe and Katabi, Dina},
  booktitle={Thirty-seventh Conference on Neural Information Processing Systems},
  year={2023}
}
@inproceedings{he2023indiscriminate,
  title={Indiscriminate Poisoning Attacks on Unsupervised Contrastive Learning},
  author={Hao He and Kaiwen Zha and Dina Katabi},
  booktitle={The Eleventh International Conference on Learning Representations},
  year={2023}
}
@article{yue2022cornerradar,
  title={CornerRadar: RF-based indoor localization around corners},
  author={Yue, Shichao and He, Hao and Cao, Peng and Zha, Kaiwen and Koizumi, Masayuki and Katabi, Dina},
  journal={Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies},
  volume={6},
  number={1},
  pages={1--24},
  year={2022},
  publisher={ACM New York, NY, USA}
}
@inproceedings{pang2022unsupervised,
  title={Unsupervised representation for semantic segmentation by implicit cycle-attention contrastive learning},
  author={Pang, Bo and Li, Yizhuo and Zhang, Yifan and Peng, Gao and Tang, Jiajun and Zha, Kaiwen and Li, Jiefeng and Lu, Cewu},
  booktitle={Proceedings of the AAAI conference on artificial intelligence},
  volume={36},
  number={2},
  pages={2044--2052},
  year={2022}
}
@inproceedings{yang2021delving,
  title={Delving into deep imbalanced regression},
  author={Yang, Yuzhe and Zha, Kaiwen and Chen, Yingcong and Wang, Hao and Katabi, Dina},
  booktitle={International conference on machine learning},
  pages={11842--11851},
  year={2021},
  organization={PMLR}
}
@article{zha2021unsupervised,
  title={Unsupervised image transformation learning via generative adversarial networks},
  author={Zha, Kaiwen and Shen, Yujun and Zhou, Bolei},
  journal={arXiv preprint arXiv:2103.07751},
  year={2021}
}
@article{pang2020complex,
  title={Complex sequential understanding through the awareness of spatial and temporal concepts},
  author={Pang, Bo and Zha, Kaiwen and Cao, Hanwen and Tang, Jiajun and Yu, Minghui and Lu, Cewu},
  journal={Nature Machine Intelligence},
  volume={2},
  number={5},
  pages={245--253},
  year={2020},
  publisher={Nature Publishing Group UK London}
}
@inproceedings{pang2020further,
  title={Further understanding videos through adverbs: A new video task},
  author={Pang, Bo and Zha, Kaiwen and Zhang, Yifan and Lu, Cewu},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={34},
  number={07},
  pages={11823--11830},
  year={2020}
}
@inproceedings{pang2019deep,
  title={Deep rnn framework for visual sequential applications},
  author={Pang, Bo and Zha, Kaiwen and Cao, Hanwen and Shi, Chen and Lu, Cewu},
  booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
  pages={423--432},
  year={2019}
}
Education
Ph.D. in Computer Science
Sep 2020 - Present
S.M. in Computer Science
Sep 2020 - May 2022
Cambridge, MA
B.Eng. in Computer Science
Sep 2016 - Jun 2020
Shanghai, China
Experience
Research Assistant | advised by Prof. Dina Katabi
Sep 2020 - Present
Cambridge, MA
Research Intern | hosted by Dr. Xingyi Zhou and Dr. Lu Yuan
May 2025 - Jan 2026
Bellevue, WA
Research Intern | hosted by Xiuye Gu, Dr. Lijun Yu, Dr. Alireza Fathi, Dr. David Ross, and Prof. Cordelia Schmid
May 2024 - Jan 2025
Mountain View, CA
Visiting Student | advised by Prof. Aude Oliva and Prof. Bolei Zhou
Jul 2019 - Mar 2020
Cambridge, MA
Research Assistant | advised by Prof. Cewu Lu
Sep 2017 - Jul 2019
Shanghai, China