I am a second-year Ph.D. student in Statistics at UC Irvine, advised by Prof. Annie Qu and Prof. Rui Miao. I received my B.S. in Mathematics and Applied Mathematics from Jilin University in 2024.

My research is in reinforcement learning — especially multi-task RL — and large language models. I’m drawn to understanding why standard methods quietly break down in these settings, and to designing principled, lightweight fixes.

My recent first-author work, TOPPO (under review), diagnoses critic-side gradient ill-conditioning as a previously overlooked bottleneck of PPO in multi-task RL and introduces Critic Balancing — per-task PopArt value normalization, pre-activation LayerNorm in the critic body, and per-side gradient combiners (PCGrad / CAGrad / FairGrad chosen independently for actor and critic) — surpassing published SAC- and ARS-family baselines on Meta-World+ MT50 with up to 22.7× fewer parameters.

Since May 2026 I have also begun an early-stage second direction: sample-efficient distillation of large LLMs into compact Mixture-of-Experts (MoE) models, framed through imitation learning and reinforcement learning.

Outside of research, I serve as a graduate teaching assistant at UCI (STATS 7, 67, 110, 120C, 205P), and I enjoy building practical tooling — for example, gradescope-mcp, an open-source MCP server that exposes 34 grading and course-management tools to AI assistants under a human-approved “preview-first” write protocol, and StudyGround, a Claude Code plugin for AI-assisted self-study.