Welcome

I am an Assistant Professor in the Department of Public Health and Health Sciences at Northeastern University and an Affiliate Investigator in the Vaccine and Infectious Disease Division at the Fred Hutch Cancer Center.

My research focuses on developing novel statistical and machine learning methods to leverage real-world data to improve decision-making in public health and clinical medicine. This involves designing robust, efficient, and targeted estimators for causal effects using large-scale data generated from electronic health records and clinical trial data. Active areas of research include causal inference, conformal inference, data integration, federated and transfer learning, and sensitivity analysis.

I obtained my PhD in Biostatistics at Harvard University, advised by Professor Tianxi Cai and Professor Lorenzo Trippa. I completed a postdoctoral fellowship in Health Care Policy at Harvard Medical School, advised by Professor Sharon-Lise Normand. I received an AM in Biostatistics from Harvard, an MPhil in Healthcare Operations from the University of Cambridge, an MA in Global Affairs from Tsinghua University, and a BS in Public Health and Biostatistics from UNC - Chapel Hill.

I enjoy playing golf, especially in my home state of North Carolina, reading history, especially biographies, and staying up-to-date with global affairs, especially US-China relations. Feel free to reach out via email: lar.han@northeastern.edu.

Recent News

Jul 24-26, 2024. [ICML 2024] Presenting Multi-Source Conformal Inference Under Distribution Shift in Vienna, Austria.

Jul 23, 2024. [New paper] Detecting univariate, bivariate, and overall effects of drug mixtures using Bayesian kernel machine regression is published in The American Journal of Drug and Alcohol Abuse.

Jul 18, 2024. [WebENAR: Van Ryzin Award Highlights] Identifying Surrogate Markers in Real-world Comparative Effectiveness Research.

Jul 11, 2024. [New preprint] A Surrogate Endpoint Based Provisional Approval Causal Roadmap is available on Arxiv.

Jul 8-10, 2024. [Invited session organizer and speaker at the International Conference on Frontiers of Data Science] Hangzhou, China.

Jul 4-7, 2024. [Invited to attend NCUSCR-Schwarzman Scholars Global Health Seminar] Geneva, Switzerland.

Jun 24, 2024. [Invited talk at Harvard Medical School, Health Care Policy] Boston, MA.

May 16, 2024. [Invited talk at ACIC] Seattle, WA.

May 15, 2024. [New paper] Multi-Source Conformal Inference Under Distribution Shift has been accepted at ICML 2024! [Github]

Apr 6, 2024. [New paper] Privacy-Preserving, Communication-Efficient, and Target-Flexible Hospital Quality Measurement is published in the Annals of Applied Statistics!

Mar 21, 2024. [New preprint] A Transfer Learning Causal Approach to Evaluate Racial/Ethnic and Geographic Variation in Outcomes Following Congenital Heart Surgery is available on Arxiv.

Mar 20, 2024. [Invited talk at Northeastern University, Center for Signal Processing, Imaging, Reasoning, and Learning] Boston, MA.

Feb 12, 2024. [Invited talk at INRIA Causal Inference and Missing Data Group] Paris, France (Virtual).

Jan 8, 2024. [Spring 2024 - Teaching HSCI 5151: Methods for Observational Studies 2] Boston, MA.

Dec 13, 2023. [NeurIPS 2023] New Orleans, LA.
Multiply Robust Federated Estimation of Targeted Average Treatment Effects

Dec 12, 2023. [Invited talk at Peking University School of Economics and Institute for Global Health and Development] Beijing, China (Virtual).
Multiply Robust Federated Estimation of Targeted Average Treatment Effects

Dec 4, 2023. [Invited talk at Cytel Inc.] Cambridge, MA.
Robust and Optimal Sensitivity Analysis (ROSA) for Clinical Trial Designs

Nov 6, 2023. [Invited talk at the Forum on the Integration of Observational and Randomized Data] Washington, DC.
Multiply Robust Federated Estimation of Targeted Average Treatment Effects

Oct 15, 2023. [Invited talk at INFORMS] Phoenix, AZ.
Multiply Robust Federated Estimation of Targeted Average Treatment Effects

Oct 13, 2023. [Invited talk at Boston Pharmaceutical Symposium] Boston, MA.
Sensitivity Analysis of Clinical Trial Designs.

Oct 10, 2023. [New paper] Privacy-Preserving, Communication-Efficient, and Target-Flexible Hospital Quality Measurement has been accepted at Annals of Applied Statistics!

Sep 21, 2023. [New paper] Multiply Robust Federated Estimation of TATEs has been accepted at NeurIPS 2023!

Sep 20, 2023. [Invited talk at Applied Statistics Workshop, Harvard Institute for Quantitative Social Science] Cambridge, MA.
Promises and Perils of Multiply Robust Federated and Transfer Learning to Estimate Causal Effects.

Aug 8, 2023. [Invited talk at JSM] Toronto, CN.
Federated and Transfer Learning to Estimate Causal Effects of Underrepresented Populations.

Aug 7, 2023. [Invited talk at JSM] Toronto, CN.
Privacy-Preserving, Communication-Efficient, and Target-Flexible Hospital Quality Measurement.
Winner of the Health Policy Statistics Section Student Paper Award.

Aug 2-5, 2023. [Attended IMS New Researchers Conference] Toronto, CN.

Jul 10-11, 2023. [Rapporteur at U.S.-China Track II Healthcare Dialogue] Durham, NC.
Consensus Agreement.

May 1, 2023. [Successful Ph.D. Dissertation Defense!] Boston, MA.
On Causal Inference in Real World Settings.
Thank you to my committee, including Tianxi Cai, Lorenzo Trippa, Rui Duan, and Sebastian Schneeweiss.