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.
Toru Shirakawa, M.D., is an incoming Ph.D. student in Computational Precision Health at UC Berkeley and UCSF, mentored by Mark van der Laan. He develops longitudinal causal inference algorithms to optimize chronic disease management and promote healthy longevity. His recent work enhances longitudinal targeted learning with deep neural networks.
Sylvia Song is currently a Master’s student in Biostatistics at the University of California, Berkeley, mentored by Laura Balzer. Her research interests primarily lie in the application of machine learning techniques and causal inference strategies to address real-world health issues. She is currently working on characteristics and predictive factors of incident Tuberculosis infection among children and adolescents in rural Southwestern Uganda.
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.
Mingxun Wang is currently an MA student in Biostatistics at the University of California, Berkeley, mentored by Mark van der Laan and Alejandro Schuler. His research interests primarily lie in TMLE, HAL, and Semiparametric Inference, with a focus on analyzing the theoretical properties of the estimators. His other research interests include Nonparametric statistics, Empirical Process, Percolation, Optimal Transport, and Manifolds. He is looking forward to exploring the applications of his research in various fields.
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.
