Shalika is an Epidemiology Ph.D. student advised by Professor Maya Petersen. She previously earned a B.S. in Environmental Sciences and an M.A. in Biostatistics from UC Berkeley. Prior to graduate school, Shalika worked as a research associate at the Public Health Institute’s Alcohol Research Group. As a graduate student, she worked on The Fit Study under the supervision of Professor Kristine Madsen. Her current research focuses on understanding the mechanisms by which the Sustainable East Africa Research in Community Health (SEARCH) trial impacted mother-to-child transmission of HIV...
Wenxin Zhang is a PhD student in Biostatistics at UC Berkeley, working with Prof. Mark van der Laan. His research interests lie in the intersection of causal inference, machine learning, and semi-parametric estimation. He is also interested in adaptive designs.
Yi Li is currently a PhD student in Biostatistics at the University of California, Berkeley, mentored by Mark van der Laan. His research interests primarily lie in causal inference, semi parametric estimation and network analysis. Recent work has been in adaptive design.
Yunwen Ji is currently a second year student in Biostatistics at the University of California, Berkeley, mentored by Alan Hubbard. Her research interests primarily lie in machine learning methodologies in precision medicine.
Zach is a Ph.D. candidate in Epidemiology at the UC Berkeley School of Public Health working under Professors Jack Colford and Alan Hubbard. His research primarily focuses on innovative design and analysis methods for randomized controlled trials in low and middle-income countries. His recent work applies Targeted Learning methodology to COVID-19 data, explores methods of synthetic data creation to improve data sharing and collaboration, and evaluates the relationships between maternal milk composition and child growth and development.