I am a tenured Associate Professor in the Department of Biostatistics, Yale School of Public Health, and the Department of Biomedical Informatics & Data Science, Yale School of Medicine, Yale University. I am also affiliated with Yale Center for Analytical Sciences, Yale Alzheimer's Disease Research Center, Yale Wu Tsai Institute,  Yale Center for Brain and Mind Health, Yale Computational Biology and Bioinformatics, Yale Institute for Foundations of Data Science, and Yale Biomedical Imaging Institute.

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My methodology research focuses on the development of cutting-edge statistical and AI models to analyze large-scale, multimodal biomedical data. I work across neuroimaging, medical imaging, multi-omics, EHRs and wearable data. Methodologically, I focus on Bayesian modeling (including Bayesian deep learning), feature selection, causal inference, data integration, and network analysis. A current emphasis of my group is on the AI-statistics interface, creating reliable, interpretable analytical tools for multimodal integration in complex, real-world settings. I have strong interests in subject matter fields including aging, mental health and psychiatry. My research has been supported by multiple NIH and foundation grants with me as the principal investigator or co-investigator.

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​I am honored to be the recipient of the Thelma and Marvin Zelen Emerging Women Leaders in Data Science Award from the Institute of Mathematical Statistics (IMS), and the COPSS Emerging Leader Award from the Committee of Presidents of Statistical Societies (COPSS). Additionally, I have received the Investigator Research Prize from the Yale School of Public Health (YSPH) and the Research Scholar Award from the Yale Alzheimer’s Disease Research Center (ADRC). I serve as an Associate Editor for the Journal of the American Statistical Association, Biometrics, and Statistical Learning and Data Science. I am currently a standing member of the NIH Biodata Management and Analysis (BDMA) study section.