Jonathan Frankle is Chief Scientist at MosaicML and Chief Scientist (Neural Networks) at Databricks, where he leads the company's research team toward the goal of developing more efficient ways of training neural networks. In his PhD at MIT, he empirically studied deep learning with Prof. Michael Carbin, specifically the properties of sparse neural networks that allow them to train effectively (his "Lottery Ticket Hypothesis" - ICLR 2019 Best Paper). In addition to his technical work, he is actively involved in policymaking and challenges related to AI. He earned his BSE and MSE in computer science at Princeton and has previously spent time at Google Brain and Facebook AI Research as an intern and Georgetown Law as a Staff Technologist and Adjunct Professor of Law.