Work

My research and engineering experiences

ByteDance (Douyin), Creation & Music Recommendation Team
Research Intern
Apr 2026 – Jul 2026
Shenzhen
  • Selected for ByteDance's Jindouyun Talent Program (ByteIntern track), a selective recruiting program for high-potential technical talent
  • Worked on generative recommendation and LLM4Rec for personalized content generation and discovery
  • Applied ideas from CAKE to LLM-driven Bayesian optimization for recommendation and adaptive content selection from feedback
Dria
Research Intern
Sep 2025 – Feb 2026
Remote (New York, NY)
  • Researched evolutionary coding agents for algorithm discovery and codebase optimization
  • Built EvolveBench, a benchmark and execution harness for evaluating coding agents on real GitHub repositories
  • Co-developed Kai, an autonomous coding agent for vulnerability discovery, exploit verification, and patch generation
  • Built Kai's sandboxed execution environments with Docker, E2B, and Vercel Sandbox
  • Shipped Kai as a CLI, FastAPI web UI, and chat-platform integrations
Huawei
Research Intern
Mar 2025 – Jul 2025
Shenzhen
  • Researched scalable black-box optimization for robust parameter tuning in high-dimensional 5G systems
  • Developed ZAP, a gradient-free optimizer for high-dimensional Gaussian process training
  • Presented the research outcomes as an oral paper at IEEE ICASSP 2026
Bayesian Learning for Signal Processing (BLSP) Group
Undergraduate Research Assistant
Jun 2021 – May 2023
The Chinese University of Hong Kong, Shenzhen
  • Developed a grid spectral mixture kernel and SLIM-KL, a communication-efficient distributed GP kernel-learning method based on quantized ADMM
  • Published the research outcomes at IEEE FUSION 2022 and IEEE TNNLS 2025
Shenzhen Research Institute of Big Data (SRIBD)
Undergraduate Research Assistant
Jun 2021 – May 2023
The Chinese University of Hong Kong, Shenzhen
  • Investigated federated matrix factorization for data clustering and recommender systems
  • Developed FedMAvg, which combines alternating minimization with model averaging for federated matrix factorization
  • Presented the research outcomes as a poster at IEEE ICASSP 2021