Alexei (Alyosha) Efros joined UC Berkeley in 2013. Prior to that, he was for a decade on the faculty of Carnegie Mellon University, and has also been affiliated with École Normale Supérieure/INRIA and University of Oxford.
His research is in the area of computer vision and computer graphics, especially at the intersection of the two. He is particularly interested in using data-driven techniques to tackle problems where large quantities of unlabeled visual data are readily available.
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The Munich AI Lectures are a joint initiative of baiosphere, Bavarian Academy of Sciences and Humanities (BAdW), Helmholtz Munich, Ludwig-Maximilians-Universität München (LMU), Technische Universität München (TUM), AI-HUB@LMU, ELLIS Chapter Munich, Konrad Zuse School of Excellence in Reliable AI (relAI), Munich Center for Machine Learning (MCML), Munich Data Science Institute (MDSI) at TUM and Munich Institute of Robotics and Machine Intelligence (MIRMI), coordinated by the Bavarian AI Agency. The aim is to attract renowned AI researchers to Munich. To keep up to date with the latest Munich AI Lectures, follow us on LinkedIn or visit the lecture series’ website.