School of Medicine
Showing 781-800 of 937 Results
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Jaime Lopez, MD
Professor of Neurology and Neurological Sciences (Adult Neurology) and, by courtesy, of Neurosurgery
Current Research and Scholarly InterestsMy clinical interests are in the areas of Intraoperative Neurophysiologic Monitoring (IOM), clinical neurophysiology, electromyopgraphy and in the use of botulinum toxins in the treatment of neurologic disorders. Our IOM groups research is in the development of new and innovative techniques for monitoring the nervous system during surgical and endovascular procedures and how these alter surgical management and patient outcomes. I am also active in formulating national IOM practice guidelines.
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Romain Lopez
Affiliate, Genetics
BioSince Fall 2021, I am a joint postdoctoral scholar at Stanford University and Genentech Research and Early Development, hosted by Jonathan Pritchard and Aviv Regev. I recently obtained my PhD degree from the department of Electrical Engineering and Computer Sciences at UC Berkeley, advised by Mike Jordan & Nir Yosef. My research interests lie at the intersection of statistics, computation and modeling with a focus on biological applications.
A significant part of my research is driven by building more statistically accurate and faster machine learning software for analyzing single-cell omics data. I developed single-cell Variational Inference (scVI), a flexible model and a scalable inference method for comprehensive analysis of single-cell transcriptomes. I co-developed scvi-tools, an open-source software suite for fully-probabilistic modeling of single-cell multi-omics data. You may learn more about these topics in my guest lecture of the Deep Learning in the Life Sciences class at MIT.
More generally, I am interested in the broader area of ML + Science. Deep generative models provide an appealing and flexible paradigm for learning distributions, but quite some work is needed to fully exploit them as part of a scientific hypothesis testing pipeline (e.g., causality, interpretability, disentanglement, decision-making).
Previously, I worked on counterfactual inference and offline policy learning methods in collaboration with technology companies. In 2018, I visited Le Song at Ant Financial in Hangzhou. In 2019, I visited Inderjit Dhillon at Amazon in Berkeley. Before graduate school, I obtained a MSc in applied mathematics from Ecole polytechnique, Palaiseau in 2016. Additionally, I worked as an intern at the Harvard Medical School with Allon Klein in 2016. I was born and grew up in Bedarieux, France.
