My research strives to develop efficient, scalable, and trustworthy machine learning algorithms to build intelligent, learning-enabled networks and systems. To achieve this, I use theoretical tools from machine learning, optimization, and probability to design rigorous algorithms with theoretical guarantees. These algorithms have been deployed in data networks, edge/mobile/cloud computing systems, recommender systems, and beyond.

Openings: I am seeking PhD students and Research Assistants starting in Summer/Fall 2025. If you are interested, please email me your CV and transcripts. For more information, please visit this page.

Bio

I am an Assistant Professor in the Department of Computer Science at City University of Hong Kong. Prior to this, I was a joint postdoc at Caltech and UMass Amherst, working with Prof. Adam Wierman and Prof. Mohammad Hajiesmaili. I received my Ph.D. in Electrical and Computer Engineering from Carnegie Mellon University in 2022, advised by Prof. Carlee Joe-Wong. Before that, I completed my B.E. in Communication Engineering at Nanjing University of Posts and Telecommunications in 2017.

My CV can be found here.

News

• Jan. 2025: Our work on bandits robust to adversarial attacks is accepted to ICLR 2025.
• Dec. 2024: Our work on robust combinatorial contextual bandits is accepted to INFOCOM 2025.
• Dec. 2024: Our work on heterogeneous multi-agent bandits with hints is accepted to AAAI 2025.