HPSS EXECUTIVE COMMITTEE
MOUSUMI BANERJEE
CHAIR
Dr. Banerjee is a Professor in the Department of Biostatistics at the University of Michigan School of Public Health (UM-SPH), Director of Biostatistics at the Pediatric Cardiac Critical Care Consortium, and Director of Global StatCore, an initiative intended to enhance biostatistical support of global public health research, education, and training at UM-SPH and in collaboration with international partners. Her research has focused on predictive modeling, machine learning, causal inference, correlated data, survival analyses, and competing risks with primary applications to health services and outcomes research. She also studies health disparities and fundamental issues related to optimal quality and equitable care delivery in the population. Dr. Banerjee is an elected Fellow of the American Statistical Association (ASA) and an elected member of the International Statistical Institute (ISI). She received her BStat and MStat degrees at the Indian Statistical Institute and her PhD in statistics at the University of Wisconsin - Madison.
JASON BRINKLEY
CHAIR-ELECT
Dr. Brinkley is a biostatistician, principal data scientist, and health researcher who leads the Research Design and Analytics team in Digital and Data Services Division at Abt Associates. He has expertise in a wide range of analytic methods, and he specializes in machine learning, customized data visualizations, maps, and dash-boarding. He balances research time between examining theoretical ways to assess the impact of medical interventions on public health and developing best practices for using statistical software. Before joining Abt, Dr. Brinkley was a senior researcher at American Institute of Research. Prior to that, he was an assistant professor of biostatistics at East Carolina University, where he remains as a research affiliate with the school’s North Carolina Agromedicine Institute (NCAI). H has a passion for rural health, methods for exploring disparities, and in evaluating bias in machine learning and other algorithms.
LAYLA PARAST
PAST CHAIR
Dr. Parast is an Associate Professor in the Department of Statistics and Data Sciences at the University of Texas at Austin. Her statistical research has focused on developing robust methods to evaluate surrogate markers, robust estimation of treatment effects, and developing and evaluating risk prediction procedures for long term survival. Her applied research has focused on measuring and comparing health care quality, and survey design and analysis for health care related surveys in a variety of settings including the emergency department, inpatient hospital, hospice, and pediatric setting. Prior to joining UT Austin, she was a senior statistician at the RAND Corporation and co-director of RAND's Center for Causal Inference.
KUAN LIU
SECRETARY
Dr. Liu is an assistant professor in Health Services Research and Biostatistics at the Institute of Health Policy, Management and Evaluation at the Dalla Lana School of Public Health, University of Toronto. Her research targets the development and application of novel statistical methods motivated by applications using observational or quasi-experimental data in a variety of disciplines, such as pediatric rheumatology, critical care medicine, and population health. Her methodological interests include causal inference, Bayesian statistics, longitudinal data analysis, and joint modelling. Dr. Liu received her PhD in biostatistics from the University of Toronto and has worked professionally as a biostatistician at several health research institutes in Canada.
ZHENKE WU
TREASURER
Dr. Wu is currently an Associate Professor of Biostatistics at University of Michigan -- Ann Arbor, and a faculty affiliate in the Michigan Institute for Data Science (MIDAS). Dr. Wu serves as an Associate Editor for Annals of Applied Statistics, Biostatistics, Journal of the Royal Statistical Society: Series A (JRSS-A), and as a statistical consultant and reviewer for New England Journal of Medicine - Artificial Intelligence (NEJM-AI). Please see Dr. Wu's website for further information: https://zhenkewu.com.
JAMES O'MALLEY
COUNCIL OF SECTIONS REPRESENTATIVE
Dr. O’Malley is the Peggy Y. Thomson Professor of the Evaluative Clinical Sciences in The Dartmouth Institute of Health Policy and Clinical Practice and Professor in The Department of Biomedical Data Science at the Geisel School of Medicine at Dartmouth. His methodological interests in statistics encompass social network analysis, multivariate hierarchical models, causal inference using instrumental variables, and Bayesian inference. Much of his work is motivated by problems in health services research. He has published over 240 peer-reviewed research papers. He chaired the HPSS in 2008 and co-chaired its International Conference in 2011. In 2011, he received the HPSS Mid-career Excellence award, in 2012 became an elected fellow of the ASA, and in 2019 received the ISPOR Methodological award for scientific excellence.
FATEMA SHAFIE KHORASSANI
PROGRAM CHAIR
Dr. Shafie Khorassani is an Assistant Professor of Biostatistics at the Boston University School of Public Health. Her statistical methodology research focuses on data integration methods for time-to-event outcomes, causal inference for observational data, and statistical methods for the evaluation of surrogate outcomes. Her work is motivated by studying health disparities using complex observational data sources. She also does work on the use of cigarettes, electronic nicotine delivery systems, and other tobacco products. She earned her PhD in Biostatistics from the University of Michigan.
ZHEYU WANG
PROGRAM CHAIR-ELECT
Dr. Wang is an Associate Professor in the Division of Quantitative Sciences at the Sidney Kimmel Comprehensive Cancer Center, with joint appointments in the Departments of Biostatistics and Applied Mathematics & Statistics at Johns Hopkins University. She is also the biostatistics core lead in the Armstrong Center for Diagnostic Excellence. Her research focuses on methodological development and practical applications to improve diagnostic procedures in healthcare, such as enhancing diagnostic accuracy, enabling early detection and intervention, and identifying subgroups for personalized medicine.
JASON ROY
FUNDRAISING COMMITTEE CHAIR
Dr. Roy is Chair and Professor of Biostatistics in the Department of Biostatistics and Epidemiology at Rutgers School of Public Health. He is the Rutgers co-lead of the Biostatistics, Epidemiology, Research Design (BERD) Core for the New Jersey Alliance for Clinical and Translational Science. His research interests include developing flexible Bayesian methods for causal inference problems, especially applied to real world data. His primary collaborations are in pharmacoepidemiology and long COVID research.
MINGYANG SHAN
FUNDRAISING COMMITTEE
Dr. Shan is a Director of Statistics and leads the Real-World Analytic Capabilities team at Eli Lilly, where he applies a spectrum of advanced analytic methods to deliver real-world evidence (RWE) and enable innovative evidence generation. His current focus is on developing methodology and best analytical practices to leverage evidence from real-world data (RWD) in drug development. His research includes external control design and analysis methods, data integration, Bayesian analysis, data linkage, and target trial emulation. He has supported trials across immunology, neuroscience, and cardiometabolic health. Prior to joining Eli Lilly, he received his PhD in biostatistics from Brown University.
ROBERT TUMASIAN III
PUBLICATIONS OFFICER
Dr. Tumasian is a mathematical statistician (statistical reviewer) in the Center for Drug Evaluation and Research (CDER) at the US Food and Drug Administration (FDA). His primary areas of interest include pharmacovigilance, pharmacoepidemiology, optimizing clinical trial designs and analyses, personalized/precision medicine, constructing clinically meaningful and statistically sound estimands, mitigating the overdose crisis, and drug and regulatory policy. Dr. Tumasian received his BS in applied mathematics from SUNY Geneseo and his PhD in biostatistics from Columbia University. He has been an active member of the American Statistical Association (ASA) since 2021.