Genevieve Patterson is the chief scientist at TRASH, a startup that is developing computational filmmaking tools for mobile iphono-graphers. Before that, she was a Postdoctoral Researcher at Microsoft Research New England. Her work is about creating dialog between AI and people. Her interests include video understanding, visual attribute discovery, human-in-the-loop systems, fine-grained object recognition, medical image understanding, and active learning. Genevieve received her Ph.D. from Brown University in 2016 under the direction of James Hays.
Nick Gaylord has worked as a data scientist in the Bay Area for about the last 5 years. Currently, he’s a member of the Johnson & Johnson Health Technology team, and prior to that, he has worked in different fields ranging from small business revenue analytics to enterprise machine-learning-as-a-service platforms. Like many data scientists, he started out as an academic before transitioning to industry, in his case earning a Ph.D. in Psycholinguistics from the University of Texas at Austin in 2013.
Dr. Jonathan Leslie obtained his Ph.D. in Biology from the University of London, studying blood vessel formation at the Cancer Research UK London Research Institute. After 20 years of researching the molecular processes underlying cancer, he turned to data science and founded a freelance consultancy business. He is passionate about promoting open-source software and routinely volunteers as a mentor in the R-programming and data science communities.