Joy Zora Nakato is currently a Masters student in Biostatistics at the University of California, Berkeley mentored by Laura Balzer and Mark van Der Laan. Her research interests include using targeted machine learning and causal inference to address challenges that arise during design and analysis of clinical trials and observational studies. She is currently working on efficient estimation of causal effects in Cluster Randomized trials addressing differential measurement and mediation with an application to uptake of HIV biomedical prevention among high risk populations in rural...
Nerissa Nance is an Epidemiology PhD and Biostatistics MA student at UC Berkeley, advised by Maya Petersen. She helps lead the JICI working group on applying the longitudinal causal roadmap to Danish registry data. Nerissa has also worked as a Biostatistics Data Consultant at Kaiser Permanente Northern California's Division of Research. She holds a Master's in Public Health degree in Epidemiology/Biostatistics, also from Berkeley.
Priya Pillai is currently a 2nd year PhD student in Computational Biology at the University of California, Berkeley, mentored by Dr. Alan Hubbard. Previously, she has worked on software development for viral diagnostic design. She is interested in researching causality in computational analyses when applied to health data and its ethical and political implications. Recent work has been in analyzing biomarkers in human milk.
Sky Qiu is a PhD student in Biostatistics at the University of California, Berkeley, mentored by Alan Hubbard and Mark van der Laan. His research interests primarily lie in causal inference and targeted learning. Recent work has been in extending the statistical method for hybrid randomized-observational data to survival outcomes, as well as developing scalable versions of highly adaptive lasso.
Seraphina Shi is currently a PhD candidate in Biostatistics at the university of California, Berkeley, working/mentored by professors Alan Hubbard and Haiyan Huang. Her research interests primarily lie in precision medicine, causal inference, and machine learning methodologies and applications. Recent work has been in causal inference, and machine learning methodologies and applications in precision medicine.
Nikolina Walas is currently a Ph.D. student in Environmental Health Sciences at the UC, Berkeley, School of Public Health, mentored by Jay Graham and Ben Arnold. Her research interests primarily lie in genomic drivers of antimicrobial resistance, serological surveillance of infectious disease, and immune development against enteric pathogens. Her recent work investigated the role of plasmids in antimicrobial resistance (AMR) gene transmission among clinically relevant E. coli in Alameda County, as well as the role of dogs in environmental AMR contamination and transmission.
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.