I’m a final-year PhD student at Carnegie Mellon University’s Robotics Institute, advised by Kris Kitani and László Jeni. My research broadly focuses on making visual models more efficient at understanding and generating visual content. My work is supported by the NSF GRFP Fellowship.
I’m currently also a Student Researcher at ByteDance Seed, collaborating with Peter Lin and Lu Jiang on accelerating video generation. I previously interned at Meta FAIR, working with Jing Huang on efficient video understanding.
Before my PhD, I was a software engineer at Nuro, developing trajectory forecasting models for self-driving vehicles, and graduated from Caltech, where I explored multi-agent reinforcement learning with Yisong Yue.
Outside of research, I enjoy running, weightlifting, watching sports, and listening to electronic music.
@article{choudhury2025apt,title={Accelerating Vision Transformers with Adaptive Patch Sizes},author={Choudhury, Rohan and Kim, JungEun and Park, Jinhyung and Yang, Eunho and Jeni, László A. and Kitani, Kris M.},journal={arXiv preprint},year={2025},site={/apt/}}
@article{choudhury2024rlt,title={Don't Look Twice: Faster Video Transformers with Run-Length Tokenization},author={Choudhury, Rohan and Zhu, Guanglei and Liu, Sihan and Niinuma, Koichiro and Kitani, Kris M. and Jeni, László A.},journal={NeurIPS},year={2024},site={/rlt/},spotlight=true}
@article{choudhury2024proviq,title={Video Question Answering with Procedural Programs},author={Choudhury, Rohan and Niinuma, Koichiro and Kitani, Kris M. and Jeni, László A.},journal={ECCV},year={2024},}
NeurIPS, 2024 (spotlight, top 3%)