Welcome
I am an Assistant Professor of Biostatistics 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, with a focus on public health and clinical medicine. This includes designing robust, efficient, and targeted estimators for learning causal effects using large-scale data generated from observational studies and randomized trials. My current areas of interest include causal inference, conformal inference, data integration, federated learning, and survival analysis.
I received my PhD in Biostatistics at Harvard University, where I was advised by Tianxi Cai and Lorenzo Trippa. I completed a postdoc in Health Care Policy at Harvard Medical School, mentored by Sharon-Lise Normand. I hold 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.
Outside of work, I enjoy playing golf, staying up-to-date on global affairs, and cheering on the UNC Tar Heels.
Feel free to reach out via email: lar.han@northeastern.edu.
[I currently have openings for postdocs, PhD students, and research assistants! Feel free to contact me if you’d like to learn more about our research.]
Recent News and Upcoming Events
Dec 2025. [PCORI Awarded] I will be the PI on a new study, Developing Accurate and Practical Methods To Quantify Uncertainty in Predictions Made by Artificial Intelligence Models, funded by PCORI for $1.068 million, Apr 2026 - Mar 2029!
Oct 2025. [JRSS-A Acceptance] COADVISE: Covariate Adjustment with Variable Selection in Randomized Controlled Trials is accepted in JRSS-A!
- Joint work with Yi Liu, Ke Zhu, and Shu Yang.
Sep 2025. [NIH K01 Funded] Causal Machine Learning Methods to Study Individual Vaccine Efficacy Using Multi-Source Data is funded by the NIAID!
- Mentors: Peter Gilbert, Sharon-Lise Normand, Michael Hudgens, Andrea Troxel, Alex Vespignani, Lindsey Baden, Dan Barouch
Sep 2025. [Fall 2025 Teaching] I am teaching 2 courses in the fall: (i) PHTH 6830: Generalized Linear Models and (ii) HSCI 5151: Methods for Observational Research 2.
Jul 2025. [JAMA Oncology Publication] Considerations for Using Clinical Practice Data to Study COVID-19 Vaccines in Patients With Cancer is published in JAMA Oncology.
Jul 2025. [ICML 2025 Publication] Bridging Fairness and Efficiency in Conformal Inference has been accepted and will be presented at ICML 2025 in Vancouver!
- Joint work with Chenyin Gao and Peter Gilbert.
Jun 2025. [JAMA Network Open Publication] Addressing Distribution Shift for Robust and Trustworthy Prediction and Causal Inference in Clinical AI Settings is published in JAMA Network Open.
May 2025. [Biostatistics Publication] A Surrogate Endpoint Based Provisional Approval Causal Roadmap, Illustrated by Vaccine Development is accepted in Biostatistics.
- Joint work with Peter Gilbert, James Peng, Theis Lange, Yun Lu, Lei Nie, Mei-Chiung Shih, Salina Waddy, Ken Wiley, Margot Yann, Zafar Zafari, Debashis Ghosh, Dean Follmann, Michael Juraska, and Ivan Diaz.
May 2025. [Methods Workshop] I am giving a Methods Workshop at the Brandeis-Harvard SPIRE Center titled “Multi-Source Causal Inference Leveraging Transfer Learning”.
Apr 2025. [HDSI Causal Seminar Discussant] I am the discussant for Elias Bareinboim’s talk “Towards Causal Artificial Intelligence” at the Harvard Data Science Initiative Causal Seminar.
Mar 2025. [JASA Publication] Federated Adaptive Causal Estimation (FACE) of Target Treatment Effects is published in Journal of the American Statistical Association.
- Joint work with Jue Hou, Kelly Cho, Rui Duan, and Tianxi Cai.
Jan 2025. [New preprint] Targeted Data Fusion for Causal Survival Analysis Under Distribution Shift is available on Arxiv.
- Joint work with Yi Liu, Alex Levis, Ke Zhu, Shu Yang, and Peter Gilbert.
Jan 2025. [Spring 2025 - Teaching PHTH 6800: Causal Inference in Public Health Research] I will teach a PhD-level first course in causal inference.
Jan 2025. [JASA Publication] Robust Inference for Federated Meta-Learning is published in Journal of the American Statistical Association.
- Joint work with Zijian Guo, Xiudi Li, and Tianxi Cai.
Dec 2024. [New preprint] On the Role of Surrogates in Conformal Inference of Individual Causal Effects is available on Arxiv.
- Joint work with Chenyin Gao and Peter Gilbert.
Dec 2024. [ICSDS invited talk] I will present On the Role of Surrogates in Conformal Inference of Individual Causal Effects at the International Conference on Statistics and Data Science (ICSDS) in Nice, France.
Nov 2024. [New preprint] Bounding Causal Effects with an Unknown Mixture of Informative and Non-informative Censoring is available on Arxiv.
- Joint work with Max Rubinstein, Denis Agniel, Marcela Horvitz-Lennon, and Sharon-Lise Normand.
Nov 2024. [NEJM Evidence Publication] Truncated, Not Forgotten — Handling Left Truncation in Time-to-Event Studies is published in NEJM Evidence.
Jul 2024. [The American Journal of Drug and Alcohol Abuse Publication] 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.
- Joint work with Jemar Bather, Alex Bennet, Luther Elliott, and Melody Goodman.
Jul 2024. [WebENAR: Van Ryzin Award Highlights] Identifying Surrogate Markers in Real-world Comparative Effectiveness Research is published in Statistics in Medicine.
- Joint work with Xuan Wang and Tianxi Cai.
May 2024. [ICML 2024 Publication] Multi-Source Conformal Inference Under Distribution Shift has been accepted at ICML 2024! [Code].
- Joint work with Yi Liu, Alex Levis, and Sharon-Lise Normand.
Apr 2024. [AOAS Publication] Privacy-Preserving, Communication-Efficient, and Target-Flexible Hospital Quality Measurement is published in the Annals of Applied Statistics.
- Joint work with Yige Li, Bijan Niknam, and Jose Zubizarreta.
Jan 2024. [Spring 2024 - Teaching HSCI 5151: Methods for Observational Studies 2] Boston, MA.
Dec 2023. [NeurIPS 2023 Publication] I will present Multiply Robust Federated Estimation of Targeted Average Treatment Effects in New Orleans, LA.
- Joint work with Zhu Shen and Jose Zubizarreta.
Jul 2023. [NEJM Evidence Publication] Breaking Free from the Hazard Ratio: Embracing the Restricted Mean Survival Time in Clinical Trials is published in NEJM Evidence.
May 2023. [Harvard Ph.D. Dissertation Defense!] Boston, MA.
On Causal Inference in Real World Settings.
- Thank you to my committee: Tianxi Cai, Lorenzo Trippa, Rui Duan, and Sebastian Schneeweiss!