4/8/26: Biostatistics and Epidemiology Career Panel Spring 2026

Join us for our Spring Biostatistics and Epidemiology Career Panel! We’re thrilled to bring you a career panel featuring leading figures in biostatistics and epidemiology. Dive into their career stories, explore their research, and their unique perspectives on the field. 

Date: Wednesday, April 8th

Time: 12:00pm - 1:30pm (This event will begin at 12pm sharp)

Location: Berkeley Way West, 5th Fl, Rm 5101

Meet our Chair

Laura Balzer

Dr. Laura B. Balzer is an Associate Professor of Biostatistics at the University of California, Berkeley. Her expertise is in causal inference, machine learning, and messy real-world data. Dr. Balzer's work addresses challenges in the design and analysis of both randomized trials and observational studies, including novel approaches for semi-parametric inference, differential measurement, and complex dependence. Dr. Balzer's work is largely been motivated by ongoing collaborations in Uganda and Kenya. She is the Primary Statistician for several studies aiming to eliminate HIV and improve community health in rural East Africa (e.g., www.searchendaids.com(link is external)). Overall, Dr. Balzer's work is informed by cross-disciplinary, real-world problems and aims to ensure methodological advances in academia translate into real-world impact.

Meet our Panelists

Biostatistics & Epidemiology Career Panel

Courtney Schiffman

Courtney is a Principal Statistician at Genentech, Inc. working remotely in San Diego, Ca. She was a summer intern at Genentech in 2018 and joined as a full time employee after graduating from the Berkeley PhD Biostatistics program in May 2019. She works in late stage clinical trials in non-oncology indications, and currently leads a Ph3 program in Ulcerative Colitis. Courtney is fortunate enough to have had Berkeley's very own star, Kaitlyn Lee, as an intern this past year!

Lauren Dang

Lauren Eyler Dang received her MD from UCSF and MPH and PhD in Biostatistics from UC Berkeley. She subsequently served as a Mathematical Statistician at the National Institute of Allergy and Infectious Diseases before moving to Amgen’s Center for Observational Research where she is now a Director of Observational Research for Pharmacovigilance Epidemiology and Causal Inference.

Lina Montoya

Dr. Lina Montoya is an assistant professor in the School of Data Science and Society at the University of North Carolina at Chapel Hill, with a joint appointment in the Department of Biostatistics at the Gillings School of Global Public Health. Her methodological research focuses on questions in causal inference, in particular within the field of precision medicine, motivated by applications in the U.S. criminal legal system and HIV care adherence in sub-Saharan Africa. Currently, her research interests involve 1) uncovering treatment effect heterogeneity and 2) estimating, evaluating, and implementing (optimal) dynamic treatment regimes in the presence of such heterogeneity. Previously, Dr. Montoya was a postdoctoral research associate in biostatistics at the University of North Carolina at Chapel Hill, and she received her doctorate and masters in biostatistics at the University of California, Berkeley. Prior to that, she was a full-time research assistant at the Laboratories of Cognitive Neuroscience at Boston Children’s Hospital/Harvard Medical School. She earned her bachelor’s degree at Johns Hopkins University.

Milena Gianfrancesco

Milena Gianfrancesco, PhD, MPH is Senior Director, Immunology & Inflammation Team Lead at Pfizer, Inc., within the Real-World Evidence & Epidemiology, Medical Evidence Generation organization. She is responsible for overall epidemiology strategy and leading a team to design and conduct studies to inform clinical development, regulatory activities, and understanding of benefit-risk profiles of medicines. Milena brings over 15 years of experience in immunology & inflammation research using a variety of observational data sets and has published over 70 peer-reviewed articles in the field. Prior to joining Pfizer, Milena was an Assistant Professor in the Division of Rheumatology, School of Medicine at UCSF. During her time at UCSF, she conducted several large-scale analyses using electronic health record data (EHR), including data from a national rheumatic disease registry of over 2 million patients aggregated from over 30 different EHR systems. Her work integrates genetic and observational data such as electronic health records and claims data with machine learning and causal inference methods. Milena earned her PhD in Epidemiology from UC Berkeley, School of Public Health with a Designated Emphasis in Computational and Genomic Biology, and an MPH in Chronic Disease Epidemiology from Yale University, and her BS in Neuroscience from Brown University. She also continues to serve as an Adjunct Assistant Professor at UCSF, and is an Executive Member-at-Large of the Society for Epidemiologic Research.