I joined Genentech in 2021 as part of the acquisition of Prescient Design. Prior to joining Prescient, I led Machine Learning at Pfizer Worldwide Research & Development from 2017 to 2020, working on developing methods for a variety of challenging problems in the medicinal sciences and across broader R&D. My background is in statistical machine learning, having worked on my Ph.D. in Computer Science and Statistics. I finished my graduate studies at Columbia University and undergraduate studies at Cornell University.
Broadly, my team studies machine learning, its application to scientific discovery, and as a means to better understand complex processes in the life sciences. As part of Prescient, we are interested in developing approaches for adaptive and controllable generation in generative models, uncertainty quantification, robust representation learning, and optimizing the interface between in silico frameworks and in vitro / in vivo experiments.