About Me

I am an assistant professor at Department of Computer Science, George Mason University. Before that I was a postdoc at Rafik B. Hariri Institute at Boston University, hosted by Francesco Orabona. I received my Ph.D. at Department of Computer Science, The University of Iowa in August 2020, under the advise of Tianbao Yang. I have also spent time working at industrial research labs, such as IBM research AI and Alibaba DAMO Academy. Here is my Google Scholar Citations.

I have multiple fully-funded PhD positions available starting from Spring 2022 or later. I am looking for highly motivated PhD students with solid math background and (or) programming skills. If you have strong mathematical abilities to work on theoretical foundations of machine learning or have rich coding experience in machine learning applications (e.g., computer vision, NLP), please drop me an email with your CV and transcript. Undergrad and graduate student visitors are also welcome.


My research interests are machine learning, optimization, learning theory, and deep learning. My goal is to design provably efficient algorithms for machine learning problems with strong empirical performance. In particular, I work on

  • Mathematical Optimization for Machine Learning: I focus on designing provably efficient optimization algorithms for machine (deep) learning problems, such as AUC maximization, F-measure optimization, Generative Adversarial Nets, etc.

  • Statistical Learning Theory: I am interested in sample complexity and computational complexity for modern machine learning problems.

  • Large-scale Distributed Learning: I design efficient scalable learning algorithms for distributed intelligence under various constraints (e.g., communication, privacy, etc.)

  • Machine Learning Applications: adversarial attack/defense, model compression and quantization, lifelong learning, etc.

  • News

    • (Sep 2021) One paper was accepted by NeurIPS 2021.
    • (Aug 2021) Joined in CS @ GMU as an assistant professor.
    • (June 2021) The paper about nonconvex-nonconcave min-max optimization has been accepted by JMLR.
    • (Sep 2020) Two papers were accepted by NeurIPS 2020.
    • (May 2020) One paper was accepted by ICML 2020.
    • (Dec 2019) Two papers were accepted by ICLR 2020.
    • (Sep 2018) Three papers were accepted by NeurIPS 2018.
    • (May 2018) One paper was accepted by ICML 2018.

    Selected Publications [Full List]

    Last update: 08-27-2021