About Me
- I am currently a Staff AI Engineer at LinkedIn Core AI. My research focuses on LLM post-training, inference efficiency, and generative recommendations.
- Previously, I was a Research Scientist at Meta.
- I received my PhD in Statistics from Cornell University under the supervision of Giles Hooker, working on interpretable machine learning and uncertainty quantification.
- Before Cornell, I received my BS in Probability and Statistics from Peking University.
Preprints and Publications
PACED: Distillation at the Frontier of Student Competence
arXiv preprint arXiv:2603.11178, 2026
Not All Tokens Are Needed (NAT): Token Efficient Reinforcement Learning
arXiv preprint arXiv:2603.06619, 2026
On-Policy Self-Distillation for Reasoning Compression
arXiv preprint arXiv:2603.05433, 2026
Overconfident Errors Need Stronger Correction: Asymmetric Confidence Penalties for Reinforcement Learning
arXiv preprint arXiv:2602.21420, 2026
Scaling Up Efficient Small Language Models Serving and Deployment for Semantic Job Search
MLSys, 2026 (to appear)
Approximation Trees: Statistical Reproducibility in Model Distillation
Data Mining and Knowledge Discovery, 38(5):3308–3346, 2024
Analyzing Spatial Heterogeneity of Ridesourcing Usage Determinants Using Explainable Machine Learning
Journal of Transport Geography, 114:103782, 2024
S-LIME: Stabilized-LIME for Model Explanation
Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2021
Unbiased Measurement of Feature Importance in Tree-Based Methods
ACM Transactions on Knowledge Discovery from Data (TKDD), 15(2):1–21, 2021
V-Statistics and Variance Estimation
Journal of Machine Learning Research (JMLR), 2021
SILR: A New Exact Test for Demonstrating That an Effect Exists in Binary Trials
OSF Preprints, 2021
Distilling Black-Box Travel Mode Choice Model for Behavioral Interpretation
Transportation Research Board 99th Annual Meeting, 2020
Service
- Reviewer, International Conference on Learning Representations (ICLR) 2022, 2023, 2024
- Reviewer, International Conference on Machine Learning (ICML) 2022
- Reviewer, Neural Information Processing Systems (NeurIPS) 2021
- Reviewer, Annals of Statistics
- Reviewer, Journal of the American Statistical Association
- Reviewer, Machine Learning (Springer)