Linking these different tissue-based data modalities together with other molecular and electronic health record information presents significant opportunities for discovery, but poses major statistical and computational challenges. The computational arm of our work weaves together high-dimensional statistics, network analysis, deep learning, computer vision, and open-source software to solve these challenging biomedical data analysis problems. The scientific arm of our work aims to improve clinical practice through the use of data-driven methods to understand disease development, discover biomarkers, improve diagnosis, and predict response to therapeutics.
Team

Iain Carmichael
Neyman Visiting Assistant Professor, Department of Statistics, UC Berkeley
Adjunct Visiting Assistant Professor, Department of Pathology, UCSF

Huong Vu
PhD student in Statistics
UC Berkeley

Neo Yin
PhD student in Statistics
UC Berkeley

Shenghuan (Harry) Sun
PhD student in the Biological and Medical Informatics Program
UCSF

Kaitlin Smith
Masters student in Statistics
UC Berkeley

Reya Vir
Undergraduate student in EECS
UC Berkeley

Jerry Li
Undergraduate student in Computer Science and Statistics
UC Berkeley

Kevin Zhou
Undergraduate student in Computer Science and Applied Math
UC Berkeley

Kanish Mirchia
Neuropathology Fellow
UCSF

Daniel Qazi
Cytopathology Fellow
UCSF

Michael Sharpnack
Resident in Pathology
UCSF