Publications

Topic All Causal Inference Network Interference Meta-Learner Survey Sampling Bandits & RL Permutation High-Dimensional NLP / LLM Collaborative Design-based Inference
Venue All Preprint ML Conference Journal
Sort Year ↓ Newest Year ↑ Oldest
Lu, S., Shi, L. and Ding, P. (2026) Estimating within-cluster and between-cluster spillover effects in randomized saturation designs. Social Networks, 87, 24–34. [Slides]
Shi, L., Zhang, A., Lyu, R., Hu, Z., Yu, T., Arbour, D., Feller, A., Mitra, S. and Sinha, R. (2026) BACON: Budgeted Human Calibration for Modeling and Evaluation with Multiple AI Judges.
Hu, Z., Shi, L., Sinha, R., Grover, J. and Arbour, D. (2026) Experimentation Accelerator: Interpretable Insights and Creative Recommendations for A/B Testing with Content-Aware ranking. KDD 2026.
Qi, S., Huang, C., Yu, T., Shi, L., Wu, J., McAuley, J. and Yao, L. (2026+) ColdSkill: Semantic-Graph Skill-Skill Expansion for Item-Side Cold-Start Routing in Agent Skills.
Hooda, R., Machcha, S., MacDonald, J., Srinivasaraghavan, L., Nijasure, A., Wang, R., Shi, L., Wu, J. and Yu, T. Multi-View Structural Interpretability of Agentic Reasoning Traces.
Lu, X., Shi, L., Liu, H. and Ding, P. (2025+) Conditional cross-fitting for unbiased machine-learning-assisted covariate adjustment in randomized experiments.
Shi, L., Lyu, Q. and Lu, S. (2025+) GAUGER: Generalized Regression Adjustment via GER for Design-Based Inference Under Interference.
Lu, S., Shi, L., Fang, Y., Zhang, W. and Ding, P. (2025+) Design-based causal inference in bipartite experiments. [Slides]
Shi, L., Lu, S., Lyu, Q., Ding, P. and Vlassis, N. (2025+) TERRA: A Transformer-Enabled Recursive R-learner for Longitudinal Heterogeneous Treatment Effect Estimation.
Shi, L., Arbour, D., Addanki, R., Sinha, R. and Feller, A. (2025+) Leveraging semantic similarity for experimentation with AI-generated treatments. NeurIPS 2025.
Lyu, Q., Wang, M. and Shi, L. (2025+) QUARK: Robust Retrieval under Non-Faithful Queries via Query-Anchored Aggregation.
Shi, L., Wang, J. and Ding, P. (2024) Forward selection and post-selection inference in factorial designs. Annals of Statistics. Accepted. [Slides]
Shi, L. and Li, X. (2024) Some theoretical foundations on the design and analysis of randomized experiments. Journal of Causal Inference. Accepted.
Shi, L. and Ding, P. (2024+) Asymptotic theory for the quadratic assignment procedure. [Slides]
Shi, L., Wei, W. and Wang, J. (2024+) Using Surrogates in Covariate-adjusted Response-adaptive Randomized Experiments with Delayed Outcomes. NeurIPS 2024. [Slides]
Shi, L., Wang, G. and Zou, C. (2024) Low-Rank Matrix Estimation in the Presence of Change-Points. Journal of Machine Learning Research. [Distinguished Student Paper Award Winner for ENAR 2023]
Barbehenn, A., Shi, L., Shao, J., Hoh, R., Hartig, H.M., Pae, V., Sarvadhavabhatla, S., Donaire, S., Sheikhzadeh, C., Milush, J., Laird, G.M., et al. (2024) Rapid Biphasic Decay of Intact and Defective HIV DNA Reservoir During Acute Treated HIV Disease. Nature Communications. Accepted.
Shi, L., Pang, H., Chen, C. and Zhu, J. (2024+) rdborrow: An R package for Causal Inference Incorporating External Controls in Randomized Trials with Longitudinal Outcomes. Journal of Biopharmaceutical Statistics. Accepted. [Slides]
Coordinated Responses Driving Innate Immune Activation, Antiviral Activity, and Tissue Inflammation Regulation Promote Early Reservoir Decay during Acute Treated HIV.
Shi, L., Wang, J. and Wu, T. (2023) Statistical inference on multi-armed bandits with delayed feedback. ICML 2023.
Cui, X., Shi, L., Zhong, W. and Zou, C. (2023) Robust high-dimensional low-rank matrix estimation: optimal rate and data-adaptive tuning. Journal of Machine Learning Research.
Shi, L., Yang, H. and Xue, L. (2023+) Oracle Inequalities for Sparse Principal Component Analysis based on the Linear Manifold Approximation.
Shi, L. and Ding, P. (2022+) Berry–Esseen bounds for design-based causal inference with possibly diverging treatment levels and varying group sizes. Annals of Statistics. Accepted. [Slides]
Shi, L. and Zou, C. (2020) Noisy Low Rank Matrix Completion Under General Bases. Stat.
Contextual Bandits with LLM-Derived Priors and Adaptive Calibration.