"Doing research at Genentech poses an exciting level up challenge for me as a scientist. I need to prove that my research is not only rigorous and novel enough to be published well, but it should be immediately practically useful."
Similar to academia, Genentech provides a unique opportunity to pursue the intellectually appealing, cutting-edge research problems. But doing research at Genentech poses an exciting level up challenge for me as a scientist. I need to prove that my research is not only rigorous and novel enough to be published well, but it should be immediately practically useful.
As part of Genentech's large scientific community, I lead a team of interdisciplinary scientists that aim to integrate concepts from physical/mathematical sciences with cell biology and immunology to promote drug target/biomarker discovery in cancer immunology.
Before joining Genentech, I spent a few years as a postdoc and then as an instructor at the Genetics Department, Stanford University. Over those several years, my research has largely been focused on the mathematical modeling of ligand-receptor interactions, and on the development of statistical methods and software tools for performing computationally efficient and robust analysis of high-dimensional data.
Our research contributes into two large subfields: digital pathology and systems immunology. We develop analytical approaches to interrogate spatially resolved omics data enabling identification of biomarkers and drug targets for a wide range of diseases. As part of system immunology efforts, we develop novel cell-based assay and computational methods to quantitatively assess TCR-pMHC interaction specificity and kinetics. These research efforts open up the way to do in silico prediction of TCRs functional activity.