معرفی
Wenbo Wu is a tenure-track Assistant Professor in the Department of Health Policy and Management at the Johns Hopkins Bloomberg School of Public Health, with a forthcoming joint appointment in the Department of Biostatistics. He is also a core faculty member in the Hopkins Business of Health Initiative and affiliated with the Center for Population Health Information Technology (CPHIT) and the Center for Health Services and Outcomes Research (CHSOR). He will begin his appointment at Johns Hopkins on June 1, 2025, following his position at New York University.
- PhD, Biostatistics and Scientific Computing, University of Michigan, 2022
- M.S., Economics, University of Wisconsin-Madison
- M.A., Labor Economics, Central University of Finance and Economics
- B.A., Financial Management, Tianjin University
Dr. Wu's research lies at the intersection of statistical methodology, machine learning, causal inference, and artificial intelligence, with a strong emphasis on health equity and data-driven clinical decision-making. His methodological interests include deep learning, natural language processing, double/debiased machine learning, ensemble learning, and meta-learning, which he applies to address challenges in provider profiling, social determinants of health, caregiving burdens, and racial and ethnic segregation. Clinically, his work focuses on Alzheimer's disease and related dementias, kidney disease, and disparities in organ donation and transplantation.
His recent publications reflect a strong trend in applying advanced statistical and machine learning methods to real-world health data, particularly electronic health records and administrative claims. The articles span topics such as kidney transplantation equity, racial disparities in prophylaxis, dynamic modeling of pandemic impacts, and robustness of clinical trial guidelines, showcasing a consistent focus on methodological rigor and health equity.
- Top Cited Article Published by Health Services Research in 2023, John Wiley & Sons, Inc., 2025
- Butler-Williams Scholar, National Institute on Aging, 2024
- Student Paper Travel Award, 14th International Conference on Health Policy Statistics, 2023
- Alice S. Hersh Student Scholarship, AcademyHealth, 2022
- Student Membership Award, Applied Public Health Statistics Section, American Public Health Association, 2021
- Isadore & Margaret Mezey Junior Investigator Conference Award, Michigan Alzheimer's Disease Center, University of Michigan, 2021
- 2021-2022 MICDE Fellowship, Michigan Institute for Computational Discovery & Engineering, University of Michigan, 2021
- First Place Winner, APHS/Stata Scholar Award, Applied Public Health Statistics Section, American Public Health Association, 2021
- Health Services Research Summer Student Fellowship, Institute for Healthcare Policy and Innovation, University of Michigan, 2021
- Student Paper Award, Lifetime Data Science Section, American Statistical Association, 2021
Dr. Wu has advised or collaborated with several early-career researchers, including postdoctoral fellow Alec McClean and PhD student Jiayi Cheng. He is actively seeking a postdoctoral researcher to work on causal inference, machine learning, NLP, and foundation models in population health. His research is supported by affiliations with major centers such as the NYU Center for Data Science and the Hopkins Business of Health Initiative. He serves as a Statistical Reviewer for NEJM Evidence and is involved in organizing academic events such as webinars and conferences.
Dr. Wu leads and participates in research teams focused on data science applications in healthcare, including provider profiling, NLP for social determinants extraction, and dynamic prediction models. He is particularly active in initiatives related to health equity, AI in medicine, and causal inference methods development.
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