Mayur M. Desai, PhD, MPH, is a Professor of Epidemiology and the inaugural Associate Dean for Diversity, Equity, Inclusion, and Belonging (DEIB) at the Yale School of Public Health. Professor Desai received both his MPH in health policy and his PhD in epidemiology from Yale. He then served for two years as an Epidemic Intelligence Service (EIS) Officer at CDC’s National Center for Health Statistics, before returning to New Haven to join the Yale faculty. Professor Desai’s expertise is in the application of epidemiologic methods to clinical and health services research. The overarching goal of his work – across various content areas – is to improve health equity in access, quality, and outcomes of care in a broad range of populations and settings. Professor Desai has extensive experience (1) conducting studies at the interface of mental health and primary care; (2) developing risk-adjusted quality-of-care measures for the Medicare program; (3) determining the incidence, trends, and outcomes of surgical procedures; (4) examining the health, health beliefs, and healthcare utilization of marginalized and stigmatized populations, including immigrants, refugees, and incarcerated individuals; (5) contributing to numerous projects in low- and middle-income settings on a range of topics, including child health, prisoner health, diagnosis and treatment of both non-communicable and infectious diseases, and health systems strengthening; and (6) examining DEIB-related issues in the biomedical workforce. Professor Desai directs the accelerated, 11-month Advanced Professional MPH Program and is a core faculty member in Yale’s National Clinician Scholars Program and Global Health Leadership Initiative. He has a long and sustained history of global public health capacity-strengthening, having developed and taught innovative short courses and workshops on a range of topics – including epidemiology, biostatistics, monitoring and evaluation, strategic problem solving, and research mentorship and leadership – in over a dozen countries. He received the 2022 Drs. Anvar and Pari Velji Global Health Award for Teaching Excellence from the international Consortium of Universities for Global Health and is a 4-time recipient of YSPH’s Distinguished Teaching Award.

Dan Weinberger is an Associate Professor in Epidemiology of Microbial Diseases at Yale School of Public Health. His research uses a combination of quantitative analysis, laboratory experiments and field work to understand the epidemiology and biology of respiratory infections. Recent work has focused on developing novel analytical methods for the evaluation of vaccines using time series and spatial data. He collaborates widely with public health agencies and academic organizations around the world on these issues. He earned his PhD in biological sciences from Harvard School of Public Health, with a focus on Infectious Disease Epidemiology, and completed a postdoctoral fellowship in the Division of International Epidemiology and Population Studies in the Fogarty International Center at the NIH.Research: The research in the Weinberger Lab is at the intersection of microbiology and epidemiology. We focus on understanding the biological and epidemiological drivers of respiratory infections, including pneumococcus, RSV, influenza, and Legionella. Major research areas include understanding the biological drivers of the emergence of rare pneumococcal serotypes following vaccine introduction, developing novel statistical approaches to evaluate vaccine impact from observational data, evaluating the importance of interactions among respiratory pathogens, and understanding environmental drivers of Legionellosis. We employ a variety of tools including experimental and quantitative approaches. Our work is funded by grants from the NIH/NIAID, the Bill and Melinda Gates Foundation, and the Emerging Infections Program (a collaboration between the CDC, the Connecticut Department of Public Health, and Yale). You can learn more about our research here. Teaching: I teach the Public Health Surveillance course at YSPH. This class uses a mix of lectures, cases studies, and hands on data analysis exercises. Students learn to perform common surveillance analyses including aberration detection (e.g., CUSUM), time series analysis, and spatial cluster detection (SATSCAN). Students learn to do these analyses in either SAS or R.

Marney A. White, PhD, MS, is a clinical psychologist, specializing in eating and weight disorders. In addition to her appointment as Professor of Social and Behavioral Sciences in the Yale School of Public Health, she holds a secondary appointment in the Department of Psychiatry (Yale School of Medicine). Professor White's research focus is on weight and eating problems, with particular emphasis on how these relate to other behavioral and physical disorders. Recent projects have examined the associations among eating disorders, depression, and anxiety with dermatologic conditions. At Yale she has taught courses in Psychotherapy, Questionnaire Development (psychometrics), Behavior Change, Health Communication, and Epidemiology. She also teaches Biostatistics in the Yale National Clinician Scholars Program. Professor White's innovative "Self Care" course (Health Behavior Change: From Evidence to Action) is now publicly available through Coursera.

Dr. Zhao is an Associate Professor in the Department of Biostatistics at Yale School of Public Health. She is also affiliated with Yale Center for Analytical Sciences, Yale Alzheimer's Disease Research Center and Yale Computational Biology and Bioinformatics. Her main research focuses on the development of statistical and machine learning methods to analyze large-scale complex data (imaging, -omics, EHRs), Bayesian methods, feature selection, predictive modeling, data integration, missing data and network analysis. She has strong interests in biomedical research areas including mental health, mental disorders and aging, etc. Her most recent research agenda includes analytical method development and applications on brain network analyses, multimodal imaging modeling, imaging genetics, and the integration of biomedical data with EHR data.  Her research is supported by multiple NIH grants.  Dr. Zhao received her Ph.D. in Biostatistics from Emory University and postdoc training at Statistical and Applied Mathematical Sciences Institute (SAMSI) and the University of North Carolina at Chapel Hill. Prior to coming to Yale, she was an Assistant Professor in Biostatistics at Cornell University, Weill Cornell Medicine.