About me

I'm a first year PhD student at UCLA CS department, advised by Prof. Baharan Mirzasoleiman. I'm mostly interested in trustworthy AI and its application to healthcare. Topics I've worked on include supervised learning with weak labels, adversarial attack, algorithmic fairness and distribution shift.

Before coming to UCLA, I did my undergrad at Yao Class, Tsinghua University, Beijing, China. I also spent a wonderful 6 months in 2024 as a research intern at CMU, advised by Prof. Steven Wu.

For a list of my publications, please visit my Google Scholar.

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Resume

Education

  1. Computer Science Department, UCLA

    Sep. 2025 - Present

    PhD Student, advised by Prof. Baharan Mirzasoleiman

  2. Institute for Interdisciplinary Information Sciences (IIIS), Tsinghua University, Beijing, China

    Sep. 2021 - Jul. 2025

    AKA "Yao Class", an honors undergraduate program in CS. My curriculum mainly focuses on AI/ML.

    GPA: 3.97/4.0, Rank: 2/89.

Experience

  • Tencent logo

    Internship @ Tencent

    Jul. - Aug., 2025

    I spent two months at Tencent, Shanghai working on step distillation for video diffusion models.

  • Research Intern @ CMU

    Feb. - Aug., 2024

    I was working on algorithmic fairness, more specifically, multicalibration, under the supervision of Prof. Steven Wu.

Projects

  • Multicalibration
    Accepted by NeurIPS 2025

    Discretization-free Multicalibration through Loss Minimization over Tree Ensembles

    Advised by Prof. Steven Wu

    We propose a novel multicalibration method that directly optimizes over tree ensembles without discretization, achieving provable multicalibration guarantees.

  • POSE: Phased One-Step Adversarial Equilibrium for Video Diffusion Models

    Internship at Tencent

    A distillation framework that enables high-quality video generation from large-scale diffusion models in a single step through phased adversarial training.

  • BCJH searcher

    Game Solution Searcher Based on Simulated Annealing (SA)

    Henry Hongyi Jin

    I devised a two-level sampling method and perform SA to search for a suboptimal solution.