Resume

🔗 Download Resume here

💼 Work Experience

Meta — Research Scientist, Feed Recommendation

June 2025 – Present

• Sequence-level RL policy optimization for personalized feed ranking
• Transfer learning for recurrent RL to improve convergence stability
• Reward modeling refinement (debiased VPV alignment)
• Hierarchical latent reasoning LLM-as-Judge framework with SFT + distillation
• Online A/B experimentation for topline impact

Microsoft — Data Scientist Intern, Azure Compute

June 2024 – Sept 2024

• Constrained RL under non-stationary reward distributions
• Agentic LLM reasoning system for root cause analysis
• Human-in-the-loop feedback pipeline (RLHF-ready design)
• Evaluation harness for systematic model benchmarking

Tencent America — Research Data Scientist Intern, IEG Global

Oct 2023 – May 2024

• Treatment effect estimation under network interference
• Bayesian modeling for online experimentation

🎓 Education

Ph.D. in Statistics, UC Santa Cruz — 2025
M.S. in Statistics, UC Davis — 2019

🛠 Skills

Languages: R, Python, SQL, Java, C++, JavaScript, Machine Learning Frameworks: Keras, PyTorch, Tensorflow
Statistics and Experimentationg: A/B Testing, Experimental Design, Causal Inference, Bayesian Optimization
AI and Learning System: Reinforcement Learning (Policy Optimization, Q-learning, PPO/GRPO-style Optimization, RLHF), Sequence-level RL for Ranking & Personalization, LLM Post-training (SFT, Distillation, Preference Modeling), LLM Inference & Serving (vLLM, Low-latency Deployment), Reward Modeling & Alignment under Distribution Shift, Agentic Workflow Design & Feedback Loops, Transfer Learning & Cross-Domain Generalization, Online Experimentation & Evaluation Harness Design

🏆 Selected Honors

• UCSC Graduate Dean’s Fellowship
• SFASA Travel Award
• WNAR Student Paper Competition Fellowship
• National Scholarship for Academic Excellence