Welcome to my website!

My name is Yongsheng Mei, and I am an Applied Scientist at Amazon. I earned my Ph.D. in 2024 from The George Washington University, advised by Prof. Tian Lan. My doctoral research focused on Bayesian optimization, reinforcement learning, and foundation models. Prior to that, I received my Bachelor’s degree in Automation Engineering in 2019 from Huazhong University of Science and Technology.

Feel free to contact me if you want collaborations on research or other opportunities!

Representative Papers

1. Yongsheng Mei, Mahdi Imani, and Tian Lan, Bayesian Optimization through Gaussian Cox Process Models for Spatio-temporal Data, International Conference on Learning Representations (ICLR), May 2024. [PDF][BibTeX]
2. Yongsheng Mei, Guru Venkataramani, and Tian Lan, Exploiting Partial Common Information Microstructure for Multi-Modal Brain Tumor Segmentation, ICML workshop on Machine Learning for Multimodal Healthcare Data (ML4MHD), July 2023. [PDF][BibTeX]
3. Yongsheng Mei, Hanhan Zhou, Tian Lan, Guru Venkataramani, and Peng Wei, MAC-PO: Multi-Agent Experience Replay via Collective Priority Optimization, International Conference on Autonomous Agents and Multiagent Systems (AAMAS), June 2023. [PDF][BibTeX]
4. Yongsheng Mei, Tian Lan, Mahdi Imani, and Suresh Subramaniam, A Bayesian Optimization Framework for Finding Local Optima in Expensive Multi-Modal Functions, European Conference on Artificial Intelligence (ECAI), September 2023. [PDF][BibTeX]
5. Yongsheng Mei, Kailash Gogineni, Tian Lan, and Guru Venkataramani, MPD: Moving Target Defense through Communication Protocol Dialects, International Conference on Security and Privacy in Communication Networks (SecureComm), September 2021. [PDF][BibTeX]