Speaker Bios
Mouna Akacha, PhD Panelist
Group Head of Statistical Methodology at Novartis
Mouna Akacha provides internal advice for clinical projects across all development phases and therapeutic areas. One key aspect of her work is to make complex statistical problems and methods accessible to a wider audience. In addition, she is engaged in developing and implementing innovative statistical methods for clinical projects. Learn more
Antonio Remiro Azócar, PhD Panelist
Statistical Innovation Leader, Novo Nordisk
Antonio Remiro Azócar is an expert in statistical methodology within the Methods and Outreach department at Novo Nordisk. His expertise lies in quantitative evidence synthesis, data fusion, HTA and observational science. He is currently developing and implementing innovative statistical methods for the enrichment of clinical trials with real-world data sources and for the transportability and generalizability of research data. Learn more
Kelley Branch, MD, PhD Panelist
Professor of Medicine and Associate Director Clinical Trials Service Unit, University of Washington
Dr. Branch has particular expertise in advanced cardiac imaging, including cardiac computed tomography, and clinical trials. He is board certified in cardiovascular disease and has been awarded the Cardiology Teaching Excellence Award and the School of Medicine Continuing Medical Education Teaching Award. Learn more
Tianxi Cai, ScD Keynote
Professor of Biomedical Informatics, Harvard Medical School; John Rock Professor of Population and Translational Data Sciences, Harvard T.H. Chan School of Public Health
Tianxi Cai is a major player in developing analytical tools for mining EHR data and predictive modeling with biomedical data. She provides statistical leadership on several large-scale projects, including the NIH-funded Undiagnosed Diseases Network at DBMI. Cai's research lab develops novel statistical and machine learning methods for several areas including clinical trials, real world evidence, and personalized medicine using genomic and phenomic data. Learn more
Marco Carone, PhD Session Chair
Professor of Biostatistics and Interim Associate Department Chair, University of Washington
Marco Carone’s research focuses on causal inference, survival analysis, and the integration of machine learning into statistical inference. He collaborates closely with researchers in infectious diseases—particularly on vaccine evaluation and respiratory virus epidemiology—as well as in neurology, with an emphasis on dementia research. Learn more
Stephen R. Cole, PhD Moderator
Carey C. Boshamer Distinguished Professor, Department of Epidemiology, University of North Carolina Chapel Hill
Stephen R. Cole works to build robust, accurate, and impactful knowledge at the intersection of epidemiology and statistics. He is interested in study designs and analyses that accurately estimate parameters of central interest to health scientists. These study designs include randomized experiments and observational studies. In particular, he is interested in infectious diseases, primarily HIV, and birth outcomes. Learn more
Issa Dahabreh, MD, MS, ScD Speaker
Associate Professor of Epidemiology, Harvard T.H. Chan School of Public Health
Dr. Issa Dahabreh’s research focuses on the development of novel methods of extending causal inferences from one or more trials to target populations and transporting clinical prediction models. Learn more
Maria Glymour, SD Keynote Speaker & Panelist
Chair and Professor, Department of Epidemiology, Boston University
Professor Glymour’s research focuses on how social factors experienced across the lifecourse, from infancy to adulthood, influence cognitive function, dementia, stroke, and other health outcomes in old age. She is especially interested in education and other exposures amenable to policy interventions. A separate theme of Glymour’s research focuses on overcoming methodological problems encountered in analyses of social determinants of health, Alzheimer's disease, and dementia. Learn more
Susan Gruber, PhD, MPH, MSSpeaker
Co-Founder, TL Revolution
Susan Gruber, co-founder of software start-up TL Revolution, is a biostatistician and computer scientist who is working to providing accessible, expert-driven tools for targeted learning. She specializes in causal inference and predictive modeling to support public health and regulatory decision making, leading and collaborating on numerous FDA-funded projects to improve evaluation of drug safety and effectiveness. Learn more
Michael Hudgens, PhD Speaker
Professor and Chair, Department of Biostatistics, University of North Carolina Chapel Hill
Dr. Michael Hudgens is a professor and chair of the Department of Biostatistics at UNC-Chapel Hill. He also serves as the director of the Biostatistics Core of the UNC Center for AIDS Research (CFAR). He has experience in collaborative research and statistical methodology development related to studies of infectious diseases. Learn more
Jay Kaufman, PhD Panelist
Professor, Department of Epidemiology, Biostatistics and Occupational Health, McGill University
Dr. Kaufman's work focuses on social epidemiology, analytic methodology, causal inference and on a variety of health outcomes including perinatal outcomes and cardiovascular, psychiatric and infectious diseases. Learn more
Ruth Keogh, PhD Speaker
Professor of Biostatistics and Epidemiology, Medical Statistics Department; Co-Director, Centre for Data and Statistics Science for Health, London School of Hygiene and Tropical Medicine
Ruth Keogh’s research focus is on statistical methodology for the analysis of observational data, such as arising from patient registries and electronic health records, with a particular emphasis on causal inference methods and methods for analysis of time-to-event data. She is also involved in a number of areas of applied health research and is especially interested in research in cystic fibrosis. Other areas of applied work include cancer, organ transplantation, Covid-19, and kidney disease. Learn more
Florian Lasch, PhD Speaker
Biostatistics Specialist, European Medicines Agency, Netherlands
Florian Lasch is a Biostatistician with a degree in mathematics and a PhD from Hannover Medical School. Florian works as a Biostatistics Specialist at the European Medicines Agency, providing scientific support throughout all stages of marketing authorisation assessments, and leads the ACT EU Priority Action on Clinical Trial Methodologies and the EMA Estimands Implementation Group.
Hana Lee, PhD Panelist
Senior Senior Staff Fellow, Food and Drug Administration
Hana Lee, PhD, is a Senior Statistical Reviewer in the Office of Biostatistics at the Center for Drug Evaluation and Research, FDA. She leads and oversees various FDA-led projects that support the development of the agency’s real-world evidence (RWE) program. She also serves as a co-lead of the RWE Scientific Working Group of the ASA Biopharmaceutical Section — a public-private partnership among the FDA, academia, and industry aimed at advancing the use of RWE to support regulatory decision-making. Learn more
Gregory Levin, PhD Keynote Speaker & Panelist
Associate Director for Statistical Science and Policy, Office of Biostatistics, Food and Drug Administration
Gregory Levin is the Associate Director for Statistical Science and Policy in the Office of Biostatistics in the FDA’s Center for Drug Evaluation and Research. Greg has experience supporting drug review across a wide range of therapeutic areas and has contributed to policy and guidance development on several topics, including estimands, adaptive design, master protocols, evaluation of drug safety, and benefit-risk assessment. Learn more
Qing Liu, PhD Panelist
Senior Director, Design and Innovation, Amgen
Qing Liu currently serves as Senior Director of Biostatistics and Head of Clinical Trial Modeling and Simulation within the Design and Innovation group at Amgen. Qing leads the advancement of innovative trial designs by applying robust statistical strategies and quantitative frameworks through modeling and simulation, enabling efficient trial designs that balance quality, speed, and cost, while promoting fit-for-purpose analytical approaches and data-informed decision-making across therapeutic areas. Her research interests include adaptive designs, causal inference, dynamic information borrowing, and quantitative decision-making.
Susan A. Murphy, PhD Speaker
Mallinckrodt Professor of Statistics and of Computer Science; Associate Faculty, Kempner Institute; Harvard University
The work of Dr. Murphy’s Statistical Reinforcement Learning Lab concerns the development of data analytic algorithms and methods for informing sequential decision making in health. In particular for (1) constructing individualized sequences of treatments (a.k.a., adaptive interventions) for use in informing clinical decision making and (2) constructing real time individualized sequences of treatments (a.k.a., Just-in-Time Adaptive Interventions) delivered by mobile devices. It is engaged in a number of clinical trials that use their real-time algorithms to learn and optimize the delivery of digital interventions. Learn more
Maya Petersen, MD, PhD Speaker
Professor, Epidemiology and Biostatistics, University of California Berkeley
Maya L. Petersen is a Professor of Biostatistics, Epidemiology, and Computational Precision Health who focuses on the development and application of novel causal inference and machine learning/AI methods to problems in health, both in the US and globally. Learn more
Henrik Ravn, PhD Speaker
Senior Statistical Director, Novo Nordisk
Henrik Ravn is senior statistical director within the Biostatistics Methods department at Novo Nordisk, Denmark. He currently provides statistical methodology advice and support for clinical projects in cardiometabolic diseases, in particular methods for event history data applied in large outcomes trials. He graduated with an MSc in theoretical statistics in 1992 from University of Aarhus, Denmark and completed a PhD in biostatistics in 2002 from the University of Copenhagen, Denmark. He joined Novo Nordisk in late 2015 after more than 22 years of experience from biostatistical and epidemiological research.
James M. Robins, MD Panelist
Mitchell L. and Robin LaFoley Dong Professor of Epidemiology, Harvard T.H. Chan School of Public Health
James M. Robins is an epidemiologist and biostatistician best known for advancing methods for drawing causal inferences from complex observational studies and randomized trials, particularly those in which the treatment varies with time. Learn more
Andrea Rotnitzky, Licenciate, PhD Session Chair
Professor of Biostatistics, University of Washington School of Public Health
Andrea Rotnitzky’s research centers in the development of analytical tools for estimating, from non or imperfect experimental data, the effects of interventions. She is primarily interested in the development of semiparametric efficient methods that exploit the information in the available data without making unnecessary assumptions about the parts of the data generating process that are not of substantive interest. Learn more
Daniel Scharfstein, ScD Panelist
Chief of the Division of Biostatistics, Department of Population Health Sciences, University of Utah School of Medicine
Daniel Scharfstein’s research is focused in how to report results in randomized trials with informative missing/censored data or irregular assessment times and in observational studies with non-random and time-varying treatment assignment. Learn more
Alisa J. Stephens Shields, PhD Speaker
Associate Professor of Biostatistics in Biostatistics and Epidemiology, Hospital of the University of Pennsylvania
Professor Stephens' research interests include clinical trials, in particular cluster-randomized trials, longitudinal data analysis, and causal inference with an emphasis on semiparametric methods. Her current collaborations include the Testosterone Trials, the Multidisciplinary Approach to Pelvic Pain Network and several projects in the prevention and treatment of HIV. Learn more
Elizabeth A. Stuart, PhD, AM Panelist
Chair and Professor, Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health
Professor Stuart’s primary research interests are in the development and use of methodology to better design and analyze the causal effects of public health and educational interventions. In this way she hopes to bridge statistical advances and research practice, working with public health and medicine researchers to identify and solve methodological challenges. Learn more
Eric Tchetgen Tchetgen, PhD Keynote Speaker & Panelist
Professor of Biostatistics, Biostatistics and Epidemiology; Professor of Statistics and Data Science; The Wharton School, University of Pennsylvania
Dr. Tchetgen Tchetgen’s primary area of interest is in semi-parametric efficiency theory with application to causal inference, missing data problems, statistical genetics and mixed model theory. In general, his work on the development of statistical and epidemiologic methods that make efficient use of the information in data collected by scientific investigators, while avoiding unnecessary assumptions about the underlying data generating mechanism. Learn more
Mark J. van der Laan, PhD Panelist
Jiann-Ping Hsu/Karl E. Peace Professor of Biostatistics and Statistics, University of California, Berkeley
Mark Johannes van der Laan has made contributions to survival analysis, semiparametric statistics, multiple testing, and causal inference. He also developed the targeted maximum likelihood methodology. He is a founding editor of the Journal of Causal Inference. Learn more
Janet Wittes, PhD Moderator
Consultant
Janet Wittes was formerly Branch Crief on the Biostatistics Research Branch at the National Heart, Lung and Blood Institute, In 1999, she founded Statistics Collaborative which worked closely with other organizations on statistical issues related to randomized controlled trials. Wittes' research focuses on the design of clinical trials and she has published on mark and recapture methods. She is a fellow of the American Statistical Association, the American Association for the Advancement of Science, and the Society for Clinical Trials. She is also an elected member of the International Statistical Institute.
Shu Yang, PhD Speaker
Professor of Statistics, North Carolina State University
Professor Yang’s research interests include survey sampling and methodology, missing data analysis and imputation methods, causal inference from longitudinal observational data, semiparametric efficient estimation, spatial data analysis-nonstationary process and spectral methods, and individual treatment regime learning, data integration and fusion methods. Learn more
Jiawen Zhu, PhD Speaker
Senior Principal Statistical Scientist, Genentech
Jiawen Zhu is a Senior Principal Statistical Scientist in PD Data Science at Genentech. Her experience spans methodological research, companion diagnostics (CDx), and molecule development across oncology and non-oncology programs. Her technical focus includes adaptive designs, dose optimization, and approaches that borrow information from external controls and real-world data (RWD). She served as principal investigator on an FDA grant (HHS U01) focused on hybrid control study design and decision making with RWE. Jiawen holds a Ph.D. in Statistics from Stony Brook University.