People

Bhramar Mukherjee, Ph.D.

Professor Bhramar Mukherjee is the Anna M.R. Lauder Professor of Biostatistics and Professor of Chronic Disease Epidemiology at the Yale School of Public Health (YSPH). Professor Mukherjee serves as the inaugural Senior Associate Dean of Public Health Data Science and Data Equity at YSPH. She holds a secondary appointment in the Department of Statistics and Data Science and is affiliated with the MacMillan Center and the Institute for the Foundations of Data Science. She serves on the Yale Cancer Center Director’s cabinet.

Jackson Higginbottom, M.P.H.

Jackson Higginbottom, MPH, is Managing Director of the Public Health Data Science and Data Equity initiative at Yale School of Public Health and Assistant Director of the Yale Data Science Fellows Program. His work focuses on using AI, digital technology, and strategic communication to improve health outcomes, strengthen public trust, and advance health equity. He received his MPH in Social and Behavioral Sciences from Yale and is pursuing a DrPH in Health Policy and Management at Johns Hopkins Bloomberg School of Public health. He also serves as Director and Board President of Manos Juntas: OKC Free Clinic, applying technology and community partnerships to expand access to care.

Cheng-Han Yang, Ph.D.

I am an Associate Research Scientist in Biostatistics at Yale University, where I work with Dr. Bhramar Mukherjee. My research focuses on electronic health record (EHR) data analysis and the development of statistical methods for complex missing data problems in real-world health data. In particular, I study settings where missingness may be informative or missing not at random, such as when sicker patients return to the hospital more often and therefore have more frequent clinical measurements recorded. If these processes are ignored, analyses can lead to biased results and misleading scientific conclusions. My work aims to develop rigorous methods that account for these biases and improve valid inference from longitudinal EHR data. I received my PhD in Biostatistics and Data Science from the University of Texas Health Science Center at Houston in 2025. My broader methodological interests include survival analysis, causal inference, and Bayesian methods for clinical trial design. Within Yale’s Data Science and Data Equity community, I contribute through methodological research on EHR-based data science and missing data in complex clinical settings.

Sean McGrath, Ph.D.

Sean McGrath is a postdoctoral associate in the Department of Biostatistics at Yale School of Public Health. His research currently focuses on developing and applying causal inference methods, particularly in settings where data are integrated from multiple sources. Previously, he was a research fellow at Harvard Medical School and Harvard Pilgrim Health Care Institute. He completed a PhD in Biostatistics at Harvard University.

Henan Xu, Ph.D.

Henan Xu is a Postdoctoral Associate in the Department of Biostatistics at Yale School of Public Health. He received his PhD in Statistics from the University of Waterloo in 2026, after completing an MA in Statistics at Columbia University and a BSc in Mathematics and Statistics at the London School of Economics and Political Science. His research focuses on causal inference and statistical methodology, with particular interests in causal mediation analysis, longitudinal and functional data, and applications in health research. He has also been a Collaborating Research Trainee at Homewood Research Institute, where he contributes to collaborative mental health research.

Snigdha Das, Ph.D.

Snigdha Das is a Postdoctoral Associate in the Department of Biostatistics at the Yale School of Public Health. She received her PhD in Statistics from Texas A&M University in 2026. Her research interests lie broadly in developing rigorous and computationally efficient statistical methods for analyzing complex health data. Her doctoral work focused on advancing Bayesian inference and computation under complex data-generating mechanisms. This included methodological developments in Bayesian nonparametrics, selection bias in probability sampling, and deep generative modeling, with an emphasis on valid uncertainty quantification and applications in oral health and biomedicine.

Madeline Brooks, PhD, MPH

Madeline Brooks, PhD, MPH is a Postdoctoral Associate in the Public Health Data Science and Data Equity (DSDE) initiative at the Yale University School of Public Health. She received her PhD in Epidemiology from Johns Hopkins University and her MPH in Public Health Practice from Thomas Jefferson University. Her research focuses on causal inference, electronic health records, artificial intelligence, and spatial analysis, with applications to age-related chronic disease.

Yiren Hou, M.S.

Yiren Hou joined the team as a statistician in June 2025. She holds a Master of Science in Biostatistics from the University of Michigan and a Bachelor of Science in Statistics from the University of Georgia, where she also minored in Mathematics and Computer Science. At the Data Science and Data Equity Initiative, Yiren is responsible for applying appropriate statistical methods to support data-driven projects and research studies. Her academic training allows her to contribute effectively to the design, programming, execution, and analysis of studies.

                           

Lillian Rountree, M.S.

Lillian Rountree is a PhD student in the Department of Biostatistics at Yale. She joined the Mukherjee Lab in August 2023, when she began her masters at the University of Michigan. She also holds a Bachelors of Arts in Statistics and French from Columbia University. Her research interests include developing causal methods for infectious disease transmission and operationalizing data equity. In her other life, outside of research and academia, she is a fiction writer; in her free time beyond that, she loves literature, pop culture, and meandering walks.

Youqi Yang

Youqi Yang is a second-year PhD candidate in Biostatistics at the University of Michigan, working under the mentorship of Dr. Bhramar Mukherjee and Dr. Walter Dempsey. His research focuses on causal inference, data integration, and survey analysis. In his free time, Youqi enjoys exploring pop culture, discovering great movies, and playing badminton. He also runs a “growing” food Instagram account with 24 followers.

Waveley Qiu

Waveley is a PhD student in the Department of Biostatistics at Yale, having begun in 2023 and joining the Mukherjee Lab in 2026. Prior to Yale, she received a MS in Biostatistics from Columbia University and a BS in Statistics from UCLA. She is interested in topics at the intersection of causal inference, real-world evidence, and drug discovery/development, motivated by her previous experience as a statistical programmer within the pharmaceutical industry. In her free time, Waveley enjoys reading good books and learning to make things from scratch – especially with others!

Xingran Chen

Xingran joined the Mukherjee Lab in May 2024 and is a PhD student in Biostatistics at the University of Michigan. He is co-advised by Dr. Bhramar Mukherjee and Dr. Zhenke Wu. His research focus on missing data problems (e.g., prediction-based inference) and synthetic electronic health record generation. Outside of research, Xingran enjoys running, birding, and spending time in nature.