Alejandra is a Biostatistics Ph.D. student in the UC Berkeley School of Public Health, advised by Professor Maya Petersen. She graduated from Brown University in 2014 with a concentration in Statistics and Public Health. She is interested in topics within global health and health economics. She is collaborating with a UCSF team to implement a cluster randomized trial which aims to improve maternal-infant health outcomes. She has also been working on a project which aims to reduce viral load testing costs for patients undergoing antiretroviral therapy.
Andre is a PhD student in Statistics advised jointly by Mark van der Laan and Alan Hubbard. He received an M.A. in Biostatistics from UC Berkeley and previously received B.S. degrees in Applied Mathematics and in Economics from North Carolina State University. His research seeks to develop target estimators for parameters of interest of semi-parametric and non-parametric statistical models. This work is motivated by problems arising in biomedical sciences, public health and precision medicine.
Bridgette is a PhD student in the Chemical Engineering department working with Professor Steven Brenner in the field of computational genomics. She was awarded a Bachelor of Science in Materials Engineering from the University of Illinois in 2017. Bridgette is interested in precision medicine and plans to work on advancing newborn genomic screening.
Jennifer is a Ph.D. student in the Comparative Biochemistry program under supervision of Dr. Mina Bissell. She has earned a B.S. in Molecular Biotechnology in 2013 as well as a M.S. in Biochemistry in 2016 from the Technical University of Munich. In her quest to understand the underlying mechanisms of Breast Cancer progression, she aims to integrate cell biology, clinical, patient derived data, as well as state of the art machine learning algorithms to improve diagnosis and predictive models.
Nick Altieri is a PhD student in the Statistics department advised by John DeNero and Bin Yu. Prior, he graduated from Berkeley with a BA in Mathematics, Statistics, and Computer Science. His research interests include information extraction, machine translation, domain adaptation, and interactive learning. Currently he is developing scaleable methods to parse electronic health records across cancers within UCSF.
Rachael is a Ph.D. student in Biostatistics, working with Professors Alan Hubbard and Mark van der Laan. She received an M.A. in Biostatistics from UC Berkeley in 2018. She graduated cum laude from Texas Tech University in 2015 receiving a B.S. in Biology with a Chemistry minor and a B.A. in Mathematics with a Spanish minor. Rachael is motivated to minimize human bias in scientific research and solve problems in molecular biology/human health by integrating tools from causal inference, machine learning, nonparametric statistical estimation, and computational statistics. She is also...