Organizers

Vicenç GómezVicenç Gómez is a post-doctoral fellow at the Artificial Intelligence group at Universitat Pompeu Fabra (UPF) under UPFellows grant (FP7 Marie Curie Actions COFUND Programme). Before joining the group, he worked as a research fellow in the machine learning group at the Radboud University Nijmegen (The Netherlands) with Prof. Dr. Hilbert. J. Kappen, where he performed research within several European-Union funded projects for more than five years. He obtained the Ph.D. in Computer Science and Digital Communication at UPF in 2008. Vicenç research focuses primarily on the development of novel machine learning methods for the analysis and/or control of complex systems. He follows a multi-disciplinary approach at the interface between computer science, control theory and statistical physics. He has applied his research in domains such as social networks, robotics, brain computer interfaces and the smart grid. His has recently developed control methods that have been successfully applied to coordinate teams of helicopter drones.

Gerhard NeumannGerhard Neumann is Assistant Professor at the TU Darmstadt since September 2014 and head of the Computational Learning for Autonomous Systems (CLAS) group. Before becoming assistant professor, he joined the IAS group as Post-Doc in November 2011 and became a Group Leader for Machine Learning for Control in October 2013. He obtained his Ph.D. at the Graz University of Technology (TUG) under the supervision of Wolfgang Maass. During his Ph.D., he was involved in several nation-funded and European-Union funded projects which concentrated on reinforcement learning for robotics, biologically inspired robotics, neural motor control and probabilistic inference for motor planning.

Jonathan YedidiaJonathan Yedidia is a senior research scientist at Disney Research Boston. He holds a Ph.D. in theoretical statistical physics from Princeton (1990). From 1990 to 1993, he was a junior fellow at Harvard’s Society of Fellows. From 1993 to 1997 he played chess professionally (he is an international master and was New England chess champion in 1992 and co-champion in 2012). In 1997 he joined the web start-up Viaweb, where he helped develop the shopping search engine that became Yahoo! Shopping. In 1998, he joined Mitsubishi Electric Research Labs (MERL), where he worked on probabilistic inference algorithms such as the famous belief propagation and generalized belief propagation algorithms, and their applications in a variety of fields, including communications, signal processing and artificial intelligence. He left his position as distinguished research scientist at MERL in 2011 to join Disney Research, where he works on algorithms for artificial intelligence, optimization, computer vision, and machine learning. At Disney Research, he has focused in particular on the optimization of multi-agent systems using distributed message-passing algorithms derived from the alternating direction method of multipliers, and new machine learning algorithms designed for fast online learning and recall.

  Peter StonePeter Stone is the David Bruton, Jr. Centennial Professor of Computer Science at the University of Texas at Austin. In 2013 he was awarded the University of Texas System Regents’ Outstanding Teaching Award and in 2014 he was inducted into the UT Austin Academy of Distinguished Teachers, earning him the title of University Distinguished Teaching Professor. Professor Stone’s research interests in Artificial Intelligence include machine learning (especially reinforcement learning), multiagent systems, robotics, and e-commerce. Professor Stone received his Ph.D in Computer Science in 1998 from Carnegie Mellon University. From 1999 to 2002 he was a Senior Technical Staff Member in the Artificial Intelligence Principles Research Department at AT&T Labs – Research. He is an Alfred P. Sloan Research Fellow, Guggenheim Fellow, AAAI Fellow, Fulbright Scholar, and 2004 ONR Young Investigator. In 2003, he won an NSF CAREER award for his proposed long term research on learning agents in dynamic, collaborative, and adversarial multiagent environments, and in 2007 he received the prestigious IJCAI Computers and Thought Award, given biannually to the top AI researcher under the age of 35.

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