CV
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Education
- University of California, Berkeley - B.A. in Computer Science
- GPA: 3.94 / 4.0
Professional Experience
- Large Language Model Engineering Intern, Douyin AI, ByteDance - May 2026–Present
- Leading the development of Simple Evolve Agent, infrastructure for reproducible agent self-evolution with sandboxed evaluation, provenance tracking, and reliability guardrails.
- Contributing to Simple Agent Lab, a compact framework for understandable, verifiable long-horizon agent workflows and reproducible evaluation.
- Supporting research and evaluation on reliable long-horizon agents, including system design, benchmarks, and failure recovery.
Research Experience
- Researcher, Shanghai Jiao Tong University - Spring 2026
- Developed EffiSkill, a two-stage LLM framework for automated code-efficiency optimization based on reusable optimization skills mined from slow and optimized program pairs.
- Built scalable inference and evaluation pipelines on EffiBench-X across Python and C++, supporting top-k generation, public/private ranking, and offline runtime evaluation.
- Improved optimization success rate over the strongest baseline by 3.69 to 12.52 points across model and language settings.
- Research Assistant, University of California, Berkeley - Fall 2025
- Built end-to-end processing pipelines for a 1.2M-row gig-economy dataset and produced validated, analysis-ready datasets for collaborators.
- Ran 30+ linear regressions and generated 40+ plots with robustness checks using statsmodels and scikit-learn.
- Researcher, Shanghai Jiao Tong University - Summer 2025
- Implemented an SFT + GRPO training pipeline for code LLMs using KodCode, including prompt standardization, reward parsing, and automated evaluation.
- Trained for 100k+ steps on 8 x A100 GPUs and established a reproducible RL fine-tuning workflow and evaluation stack.
Teaching
- Teaching Assistant, University of California, Berkeley - Fall 2024
- Mentored students in foundational data science and Python programming through discussion sections, office hours, and project support.
Skills
- Languages: Python, Java, SQL
- ML / LLM: PyTorch, HuggingFace, VeRL, vLLM, RLHF
- Data / Tools: NumPy, Pandas, scikit-learn, Matplotlib, Git, Linux, LaTeX
- Technical Foundations: Machine Learning, Reinforcement Learning, Neural Networks, Computer Vision, Data Structures, Algorithms, Probability, Optimization, Linear Algebra
Selected Publications
