Tian Gu, PhD
- Assistant Professor of Biostatistics
On the web
Overview
Dr. Gu‘s research focuses on developing novel statistical and machine-learning approaches that leverage large external data sources to improve precision health and disease risk prediction. Her work also extends to COVID-19 and health disparities, with a particular emphasis on utilizing multi-center and EHR-linked biobank data to enhance disease prediction and diagnosis in underrepresented populations. The methods and software she developed have supported studies in infectious disease epidemiology, pulmonary diseases, cardiovascular diseases, and cancer.
Academic Appointments
- Assistant Professor of Biostatistics
Credentials & Experience
Education & Training
- BS, 2015 Statistics, East China Normal University
- BS (Dual Degree), 2015 Mathematics, Colorado State University
- MS, 2017 Biostatistics, University of Michigan
- PhD, 2021 Biostatistics, University of Michigan
- Fellowship: 2023 Harvard University
Honors & Awards
- 2023: ASA Statistic in Epidemiology Section Young Investigator Award
- 2022: Harvard Data Science Initiative Postdoc Fellow Research Award
- 2022: Biometrics Excellent Referee Award
Research
Research Interests
- Artificial Intelligence (AI)
- Data integration
- Electronic Health Records (EHR/EMR)
- Federated learning
- Health Disparities
- Machine Learning (ML)
- Synthetic data
- Transfer learning
Selected Publications
Gu, T., Han, Y., & Duan, R. (2023). Robust angle-based transfer learning in high dimensions. arXiv preprint. DOI: 10.48550/arXiv.2210.12759
Gu, T., Lee, P, & Duan, R. (2023). COMMUTE: Communication-efficient transfer learning for multi-site risk prediction. Journal of Biomedical Informatics. DOI: 10.1016/j.jbi.2022.104243
Gu, T., Taylor, J. M. G., & Mukherjee, B. (2023). A synthetic data integration framework to leverage external summary?level information from heterogeneous populations. Biometrics. PMCID: PMC10480346. DOI: 10.1111/biom.13852
Labaki, W. W., Gu, T., Murray, S., Curtis, J. L., et al. (2023). Causes of and Clinical Features Associated with Death in Tobacco Cigarette Users by Lung Function Impairment. American Journal of Respiratory and Critical Care Medicine. PMCID: PMC10449063. DOI: 10.1164/rccm.202210-1887OC
Gu, T., Mack, J. A., Salvatore, M., Sankar, S. et al. (2020). Characteristics associated with racial/ethnic disparities in COVID-19 outcomes in an academic health care system. JAMA Network Open. PMCID: PMC7578774. DOI: 10.1001/jamanetworkopen.2020.25197
Gu, T., Lee, P, & Duan, R. (2023). COMMUTE: Communication-efficient transfer learning for multi-site risk prediction. Journal of Biomedical Informatics. DOI: 10.1016/j.jbi.2022.104243
Gu, T., Taylor, J. M. G., & Mukherjee, B. (2023). A synthetic data integration framework to leverage external summary?level information from heterogeneous populations. Biometrics. PMCID: PMC10480346. DOI: 10.1111/biom.13852
Labaki, W. W., Gu, T., Murray, S., Curtis, J. L., et al. (2023). Causes of and Clinical Features Associated with Death in Tobacco Cigarette Users by Lung Function Impairment. American Journal of Respiratory and Critical Care Medicine. PMCID: PMC10449063. DOI: 10.1164/rccm.202210-1887OC
Gu, T., Mack, J. A., Salvatore, M., Sankar, S. et al. (2020). Characteristics associated with racial/ethnic disparities in COVID-19 outcomes in an academic health care system. JAMA Network Open. PMCID: PMC7578774. DOI: 10.1001/jamanetworkopen.2020.25197