Welcome to my website!

My name is Yongsheng Mei, and I am currently a Ph.D. candidate at the George Washington University advised by Prof. Tian Lan. My research primarily focuses on Bayesian optimization, reinforcement learning, and network security. Before joining GWU, I was an undergraduate student at Huazhong University of Science and Technology, where I earned my Bachelor’s degree in Automation Engineering in 2019.

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]