About me

I am an Applied Scientist at Amazon. I obtained my Ph.D. in Statistics at Purdue University, where I was fortunate to be coadvised by Prof. Qifan Song and Prof. Jean Honorio. I also received an M.S. in Computer Science and Statistics during my Ph.D. study. I received a B.Sc. in Mathematics from the Chinese University of Hong Kong. I have interned at several companies including Meta AI, Amazon Ads, and Sensetime Research.

My research interests include:

• Optimization Theory
• Bandit Algorithms
• Federated Learning
• High Dimensional Statistics
• Deep Learning Theory and Practice

Research collaborations from both industry and academia are highly welcomed. If you are interested in optimization/bandit/federated learning-related topics, feel free to reach out to me.

Recent News

• [Oct, 2024]. "PyXAB - A Python Library for X-Armed Bandit and Online Blackbox Optimization Algorithms" is accepted by JOSS!
• [Jan, 2024]. "Personalized Federated X-Armed Bandit" is accepted by AISTATS-2024!
• [Nov, 2023]. "Federated X-Armed Bandit" is accepted by AAAI-2024!
• [Nov, 2023]. I have defended my thesis and started to work as an Applied Scientist at Amazon!
• [Jun, 2023]. "Federated Online Sparse Decision Making" is accepted by Transactions on Machine Learning Research!
• [May, 2023]. "Optimum-statistical Collaboration Towards General and Efficient Black-box Optimization" is accepted by Transactions on Machine Learning Research!
• [Mar, 2023]. I will be an Research Scientist Intern at Meta this summer!
• [Jan, 2023]. Our team has recently launched the PyXAB project. Take a look! .
• [Jul, 2022]. "Variance Reduction on General Adaptive Mirror Descent" is accepted by the Machine Learning Journal!
• [May, 2022]. "A Simple Unified Framework for High Dimensional Bandit Problems" is accepted by ICML-2022!
• [Apr, 2022]. I will be an Applied Scientist Intern at Amazon this summer!
• [Mar, 2022]. I have passed the preliminary exam! Many thanks to my advisors and my committee members.
• [Oct, 2021]. "Optimum-statistical Collaboration Towards Efficient Black-box Optimization" is accepted by the NeurIPS2021 OPT Workshop!
• [Oct, 2020]. "Variance Reduction on Adaptive Mirror Descent" is accepted by the NeurIPS2020 OPT Workshop with Spotlight presentation!
• [Aug, 2020]. I have passed the qualifying exams!