Romain Lopez

Romain Lopez is an Assistant Professor of Computer Science and Biology at New York University. He received his MSc in Applied Mathematics from École polytechnique and his PhD in Computer Science from UC Berkeley, advised by Professors Michael I. Jordan and Nir Yosef. He was a Postdoctoral Fellow at Genentech and Stanford University, hosted by Professors Aviv Regev and Jonathan Pritchard. He has received Best Paper honors at leading AI and computational biology venues, an AI2050 Early Career Fellowship, as well as a STAT Wunderkind Award (2024), recognizing North America’s most promising early-career scientists. His research develops probabilistic and causal machine learning methods to uncover the mechanisms that govern cellular behavior and disease, including the scVI framework and the scvi-tools ecosystem for deep generative modeling of single-cell omics data.

AI2050 Project

Steering immune cells towards states able to fight cancer and autoimmune disease holds enormous medical promise but requires testing vast numbers of experimental conditions to find the right genetic or chemical interventions. Lopez’s project develops AI systems that intelligently decide which experiments to run next, learning from each round of results to focus on the most informative interventions. By integrating knowledge from biological databases and language models, the system navigates experimental spaces far too large for trial-and-error approaches. Lopez’s team will apply this framework to engineering improved therapeutic T cells in collaboration with an immunology lab.