Ph.D. student, Electrical Engineering & Computer Sciences, UC Berkeley Affiliations: Berkeley Artificial Intelligence Research & Center for Computational Biology Advisors: Michael I. Jordan & Nir Yosef email: romain [underscore] lopez [at] berkeley [dot] edu Curriculum Vitae

Research Interests

My interests – centered around mathematical statistics and applications to machine learning in biology – have taken a focus on probabilistic modeling of single-cell RNA sequencing data. Its ecosystem includes Bayesian modeling, variational inference and namely approximate posterior inference with neural networks. I am currently the lead contributor of single-cell Variational Inference (scVI).

Master's Thesis opportunities

We offer opportunities for MSc students anywhere in the world to apply for a funded visiting research position at UC Berkeley to work on projects related to scVI (example of assignment I proposed in the past to select the students).

Papers

• Deep Generative Modeling for Single-cell Transcriptomics
  Romain Lopez, Jeffrey Regier, Michael B. Cole, Michael I. Jordan, and Nir Yosef
  Nature Methods, 2018 [journal, preprint, News & Views, BAIR Blog, NIPS MLCB, BayLearn Oral]

• Information Constraints on Auto-Encoding Variational Bayes
  Romain Lopez, Jeffrey Regier, Michael I. Jordan and Nir Yosef
  Advances in Neural Information Processing Systems, 2018 [proc., preprint]

• Scrublet: computational identification of cell doublets in single-cell transcriptomic data
  Samuel L. Wolock, Romain Lopez and Allon M. Klein
  Cell Systems (to appear, 2018 [preprint])

About me

I grew up in small town of southern France (Bedarieux), where I spent my time riding motorcycles, learning and teaching Judo as well as thinking about quantitative models for evaluating the temperature of the different planets of the solar system. I then went through the traditional French system of classes preparatoires in Toulouse at lycée Pierre-de-Fermat. After that, I worked with Laurent Massoulie (Optimal stochastic control on random graphs) at Ecole polytechnique (France) where I received the Diplome d'Ingenieur (2016). After several real-world experiences at Cardiologs (Time-series classification) and in Systems Biology, HMS with Allon Klein (Sparse Matrix Factorization), I decided to maintain this versatile orientation between theory and applications. Recently, I also worked with Le Song at Ant Financial in Hangzhou on Counterfactual Inference and Offline policy optimization.