Robert Ball M.D., M.P.H., Sc.M., is Deputy Director, Office of Surveillance and Epidemiology (OSE), Center for Drug Evaluation and Research, at the Food and Drug Administration (FDA) where he shares in responsibilities leading OSE staff in premarket and postmarket regulation of drugs and therapeutic biologics through adverse event surveillance, pharmacoepidemiology, risk management, and medication error preventionFrom 2008-2013, he served as the Director, Office of Biostatistics and Epidemiology, Center for Biologics Evaluation and Research, FDA where he led statistical and epidemiological evaluation of vaccines, blood, cell, tissue, and gene therapy products. His recent research has included the application of natural language processing and machine learning to improve the evaluation of medical product safety and effectiveness in electronic healthcare data systems.

Noam Barda, M.D., Ph.D.  I am a lecturer at the Department of Software and Information Systems Engineering & Department of Epidemiology, Biostatistics and Community Health Sciences at Ben-Gurion University. In parallel, I am the head of the Real-World Evidence Research and Innovation Lab and the Chief Epidemiologist at the Sheba Pandemic Research Readiness Institute (SPRI), both in Sheba Medical Center. I have broad training in medicine (MD, with a specialty in public health and epidemiology), computer science (B.Sc.) and biostatistics (M.Sc.). My post-doctorate was at the department of biomedical informatics at Harvard Medical School. My rResearch focuses on three main fields: causal inference, applied predictive modeling in healthcare, and algorithmic fairness. In each field, I try to use state-of-the-art methods, combining epidemiological and computational methods. Over the last several years, I have published extensively on the topic of Covid-19 vaccines and immunity. These publications have been featured in prestigious medical journals, and have been an aid in determining policy in multiple countries.

Brian Caffo, Ph.D., received his doctorate in statistics from the University of Florida in 2001 before joining the faculty at the Johns Hopkins Department of Biostatistics, where he became a full professor in 2013. He has pursued research in statistical computing, generalized linear mixed models, neuroimaging, functional magnetic resonance imaging, image processing and the analysis of big data. He created and led a team that won the ADHD-200 prediction competition and placed twelfth in the large Heritage Health prediction competition. He was the recipient the Presidential Early Career Award for Scientists and Engineers, the highest award given by the US government for early career researchers in STEM fields. He co-created and co-directs the SMART (www.smart-stats.org) group focusing on statistical methodology for biological signals. He also co-created and co-directs the Data Science Specialization, a popular MOOC mini degree on data analysis and computing. Dr. Caffo is the former director of the graduate programs in Biostatistics, president of the Bloomberg School of Public Health Faculty Senate, the recipient of the Golden Apple teaching award and AMTRA mentoring awards.

Tala H. Fakhouri, Ph.D., MPH, is the Associate Director for Policy Analysis at the Food and Drug Administration. Dr. Fakhouri manages a team tasked with developing, coordinating, and implementing medical policy with a focus on the use of Artificial Intelligence (AI) in drug development. She also contributes to the development of medical policy related to real-world evidence (RWE) for medical product development. In 2023, She was selected by the Office of Management and Budget to serve on the Federal Committee for Statistical Methodology for her expertise in statistical methods.

Prior to joining FDA, Dr. Fakhouri served as Chief Statistician for the CDC’s flagship population survey, the National Health and Nutrition Examination Survey (NHANES), which is recognized as the premier source of nationally representative data on the health of the nation. Prior to NHANES, she served as an Epidemic Intelligence Service Officer with the CDC, and deputy lead for health surveys at ICF-Macro International. Dr. Fakhouri published over 30 government reports, peer-reviewed papers, and book chapters.

Dr. Fakhouri earned a Ph.D. in Oncological Sciences from The Huntsman Cancer Institute at the University of Utah, an MPH in Epidemiologic and Biostatistical Methods from the Johns Hopkins University School of Public Health, and a postdoctoral fellowship in molecular biology and genetics from Harvard University, and holds a BSc Medical Technology form the Jordan University of Science and Technology.

Qingxia Chen, Ph.D., is a Professor of Biostatistics, Biomedical Informatics, and Ophthalmology & Visual Sciences at Vanderbilt University Medical Center. She also serves as the Vice Chair of Education at the Department of Biostatistics and co-leads the statistical efforts at the Data and Research Center for the All of Us Research Program.

Lauren Eyler Dang, M.D., Ph.D., M.P.H., is a Statistician in the National Institute of Allergy and Infectious Diseases Biostatistics Research Branch. She received her Ph.D., in Biostatistics from University of California, Berkeley and her MD from University of California, San Francisco. Her research focuses on the application, dissemination, and development of causal inference and targeted learning methods, particularly as applied to global health and infectious disease research.

Junshui Ma, Ph.D., serves as an Associate Vice President, and the head of the Biometrics Research department at Merck Research Lab. He obtained his PhD in Signal Processing and Machine Learning from Ohio State University in 2001. Following his tenure as a postdoc at Los Alamos National Lab and a faculty member at Ohio State University, he joined Merck in January 2005. Over the past 18 years, he has participated in all stages of drug Research & Development (R&D), encompassing preclinical discovery, clinical development, regulatory filing, and translational medicine. A key area of his research involves the application of AI/ML to drug R&D. He has co-authored more than 30 peer-reviewed journal papers, in addition to numerous conference abstracts and posters.

Subha Madhavan, Ph.D., is a dynamic and results-driven leader with a strong track record of excellence in organizations that operate at the nexus of science, technology and business. She has initiated and successfully directed several productive clinical research and development programs at the Georgetown Lombardi Comprehensive Cancer Center, MedStar hospital network, FDA, NIH and BioPharma industry. She was co-leader of the FDA’s Center for Excellence in Regulatory Science and worked with the oncology and vaccine teams. She was an advisory member to the Biden Foundation’s Cancer Moonshot Program and advised on pre-competitive data sharing initiatives across pharma, health tech companies and research organizations to drive innovation. She has been recognized for her work through several awards including the Service to America award in the Science and Environment category (2005), Research Acceleration Award by AACR and Pancreatic Cancer Action Network (2015), and Women in Tech Global award (2021). She is currently the Head of Clinical AI/ML & Digital Sciences at Pfizer worldwide R&D where she leads a team focused on advancing precision therapies across multiple treatment areas including Anti-Infectives, Oncology, Immunology & Inflammation among others.

Anthony Philippakis, M.D., Ph.D., is the chief data officer of the Broad Institute of MIT and Harvard, and the co-director of the Eric and Wendy Schmidt Center.

He trained as a cardiologist at Brigham and Women’s Hospital, with a focus on rare genetic cardiovascular diseases. At the Broad Institute he is the founding director of the Data Sciences Platform, an organization of over 200 software engineers and computational biologists that develops software for analyzing genomic and clinical data. In addition to his roles at the Broad Institute and Brigham and Women’s Hospital, Philippakis is a venture partner at GV, focusing on machine learning, distributed computing, and genomics. Philippakis received his M.D. from Harvard Medical School and completed a Ph.D. in biophysics at Harvard. As an undergraduate, he studied mathematics at Yale University, and later completed the Part III (equivalent to M.Phil) in mathematics at Cambridge University.

Hoifung Poon,Ph.D., is the General Manager at Microsoft Health Futures. His research interest is in developing next-generation AI technology to accelerate progress in access, safety, and preventative care for precision health. At Microsoft, He leads biomedical AI research and incubation, with a particular focus on scaling real-world evidence generation by structuring all medical data. He obtained a B.S. with Distinction in Computer Science from Sun Yat-Sen University, and a Ph.D. in Computer Science and Engineering (my dissertation) from University of Washington. He is an affiliated faculty professor at University of Washington Medical School, and serves as co-PI for various academic projects such as DARPA Big Mechanisms. His past work spans diverse topics in machine learning and NLP, and has been recognized with Best Paper Awards in top conferences such as NAACL, EMNLP, and UAI. For more information, check out his publications and LinkedIn profile.

Pranav Rajpurkar, Ph.D., is an Assistant Professor at Harvard University and a researcher in the field of medical artificial intelligence. With a focus on medical image interpretation, Dr. Rajpurkar’s research lab strives to develop AI models that can match the proficiency of top-tier medical doctors. His research group is at the forefront of developing “Generalist Medical AI” systems that can closely resemble doctors in their ability to reason through a wide range of medical tasks, incorporate multiple data modalities, and communicate in natural language. Dr. Rajpurkar has published more than 65 academic papers which have received over 19K citations, including in Nature, NEJM, and Nature Medicine. His work has been covered by media outlets including NPR, The Washington Post, and Wired. In 2022, Dr. Rajpurkar has been recognized as a recipient of Forbes 30 Under 30 and as a Nature Medicine Early-career Researcher To Watch. Dr. Rajpurkar leads educational initiatives including the Harvard-Stanford Medical AI Bootcamp Program, and CS197: AI Research Experiences at Harvard. Prior to starting at Harvard in 2021, Dr. Rajpurkar earned his B.S., M.S., and Ph.D. degrees, all in Computer Science from Stanford University.

Omer Reingold, Ph.D., is the Rajeev Motwani professor of computer science at Stanford University and the director of the Simons Collaboration on the Theory of Algorithmic Fairness. Past positions include the Weizmann Institute of Science, Microsoft Research, the Institute for Advanced Study in Princeton, NJ, AT&T Labs and Samsung Research America. His research is in the foundations of computer science and most notably in computational complexity, cryptography and the societal impact of computation. He is an ACM Fellow and a Simons Investigator. Among his distinctions are the 2005 Grace Murray Hopper Award and the 2009 Gödel Prize.

David Sontag, Ph.D., is a Professor of Electrical Engineering and Computer Science at MIT, part of the Institute for Medical Engineering & Science, the Computer Science and Artificial Intelligence Laboratory, and the J-Clinic for Machine Learning in Health. His research focuses on advancing machine learning and artificial intelligence, and using these to transform health care. Previously, he was an Assistant Professor of Computer Science and Data Science at New York University.

Marc Adam Suchard, M.D., Ph.D., is Professor in the Departments of Biomathematics and of Human Genetics in the David Geffen School of Medicine at UCLA and in the Department of Biostatistics in the UCLA Fielding School of Public Health at the University of California, Los Angeles. He was elected as a Fellow of the American Statistical Association in 2012, and he received the COPSS Presidents’ Award in 2013.

Dr. Yuanjia Wang, Ph.D., is a Professor in the Department of Biostatistics and Department of Psychiatry at Columbia University, and a core member of the Division of Biostatistics at New York State Psychiatry Institute. She was elected as a Fellow of the American Statistical Association (ASA) in 2016. Dr. Wang works on developing data-driven approaches to explore relationship between biomarkers, clinical markers, and health outcomes to assist discoveries in disease etiology, and increase diagnostic capabilities of psychiatric and neurological diseases. Her methodological interests include statistical learning, analytics for personalized medicine, network analysis, and novel design and analysis of clinical trials. Her substantive research area of interest includes psychiatric disorders and neurological disorders.

David Madigan, Ph.D., came to Northeastern from Columbia University, where he served as executive vice president for arts and sciences and dean of the Faculty of Arts and Sciences. In those roles, he oversaw five schools with 27 departments and some 50 research centers and institutes. He led successful initiatives to expand lifelong learning programs, and to make Columbia’s faculty and student body more diverse. Notably, he spearheaded a program to ensure that Columbia’s first-generation students would have the mentoring and support they needed to succeed in a highly demanding academic environment.

At Columbia and in his previous position as Rutgers University’s Dean of Physical and Mathematical Sciences, Madigan developed new interdisciplinary learning and research collaborations, and forged industry partnerships to support student and faculty innovation. Under his leadership as department chair, Columbia’s statistics faculty ascended to the ranks of the nation’s top 10.

A fellow of the American Association for the Advancement of Science, Madigan has long been a leading researcher at the intersection of Big Data with healthcare innovation. While serving on the statistics faculty at the University of Washington, he was a member of the world-renowned Fred Hutchinson Cancer Research Center.

Madigan also brings a strong global perspective to Northeastern. A native of Ireland, he has led large-scale global collaborations involving academic and pharmaceutical company researchers and government regulators in the U.S. and Europe. Beyond the halls of academia, he has experience as an entrepreneur, innovation leader, researcher, and consultant, both in the U.S. and Ireland. He earned his BA and PhD from Trinity College Dublin.