Join The Data Incubator and Zoubin Ghahramani, Chief Scientist for Uber, for the December 2018 installment of our free monthly webinar series, Data Science in 30 minutes: Uber’s Chief Scientist Explores Frontiers of Machine Learning and AI.
Zoubin will review fundamental concepts and recent advances in artificial intelligence. He will then highlight some areas of research at the frontiers, touching on topics such as deep learning, probabilistic programming, Bayesian optimisation, and AI for data science. Finally, he will describe how these areas fit into Uber’s mission.
About the speakers:
Zoubin Ghahramani is Chief Scientist of Uber and a world leader in the field of machine learning, significantly advancing the state-of-the-art in algorithms that can learn from data. He is known in particular for fundamental contributions to probabilistic modeling and Bayesian nonparametric approaches to machine learning systems, and to the development of approximate variational inference algorithms for scalable learning. Zoubin also maintains his roles as Deputy Director of the Leverhulme Centre for the Future of Intelligence and Professor of Information Engineering at the University of Cambridge. He holds joint appointments at Carnegie Mellon University, University College London and the Alan Turing Institute and has been a Fellow of St John’s College, Cambridge since 2009.
Michael Li founded The Data Incubator, a New York-based training program that turns talented PhDs from academia into workplace-ready data scientists and quants. The program is free to Fellows, employers engage with the Incubator as hiring partners. Previously, he worked as a data scientist (Foursquare), Wall Street quant (D.E. Shaw, J.P. Morgan), and a rocket scientist (NASA). He completed his PhD at Princeton as a Hertz fellow and read Part III Maths at Cambridge as a Marshall Scholar. At Foursquare, Michael discovered that his favorite part of the job was teaching and mentoring smart people about data science. He decided to build a startup to focus on what he really loves. Michael lives in New York, where he enjoys the Opera, rock climbing, and attending geeky data science events.
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