Speakers

Professor Edith Law is an Associate Professor at the David R. Cheriton School of Computer Science at University of Waterloo, and co-directs the Human Computer Interaction Lab. Previously, She was a CRCS postdoctoral fellow at Harvard University School of Engineering and Applied Sciences, and holds a Ph.D. in Machine Learning from Carnegie Mellon University, a Masters in Computer Science from McGill University and a B.Sc in Computer Science from University of British Columbia. She is broadly interested in social computing technology that coordinates small groups to large crowds, new models of interactions with machine intelligence, and how technology can be designed to foster and celebrate certain human values. The research conducted by Law and her students have received several best paper awards and honorable mentions at the CHI and CSCW conference. Law's work is funded by NSERC Discovery Grant, NSERC-CIHR Collaborative Health Research Project (CHRP) as well as the CFI-JELF program.

Professor Maya Cakmak is an Assistant Professor at the University of Washington, Computer Science & Engineering Department, where she directs the Human-Centered Robotics Lab. She holds a B.Sc. degree in Electrical & Electronics Engineering and a M.Sc. degree in Computer Engineering from the Middle East Technical University in Turkey. She received her Ph.D. in Robotics at the Georgia Institute of Technology in 2012, after working five years at the Socially Intelligent Machines Lab with Andrea L. Thomaz. Afterwards, she spent a year as a post-doctoral research fellow at Willow Garage, Inc. working with Leila Takayama. Her research interests are in human-robot interaction, end-user programming, and assistive robotics. She aims to develop robots that can be programmed and controlled by a diverse group of users with unique needs and preferences to do useful tasks.

Dr. Georg Martius is leading a research group on Autonomous Learning at the Max Planck Institute for Intelligent Systems in Tubingen, Germany. Before joining the MPI in ¨ Tubingen, he was a postdoc fellow at the IST Austria in the ¨ groups of Christoph Lampert and Gasper Tka ˇ cik after being ˇ a postdoc at the Max Planck Institute for Mathematics in the Sciences in Leipzig. He pursues research in autonomous learning, that is how an embodied agent can determine what to learn, how to learn, and how to judge the learning success. He is using information theory and dynamical systems theory to formulate generic intrinsic motivations that lead to coherent behavior exploration – much like playful behavior. With his research group, he is working on machine learning methods for robotics including reinforcement learning, intrinsic motivation, internal model learning, representation learning, and haptics.

Dr. Christoph Salge is a Senior Research Fellow at the University of Hertfordshire, with research interests in AI, intrinsic motivation, games and robotics. He recently completed a Marie-Curie Global Fellowship and is very interested to see how humans perceive and interact with artificial intelligence in games or robots. His talk will present both existing experimental work, and a future vision, for how to use coupled intrinsic motivation maximisation to create different social behaviours – based on the idea that the same algorithms that motivate reasonable single agent behaviour could be used to create reasonable agent-agent interaction.

Professor Goren Gordon is an associate professor in the Department of Industrial Engineering in Tel-Aviv University, Israel. He has a BMSc, MSc in physics and MBA from Tel-Aviv University, Israel. He has one PhD in chemical physics on dynamical quantum decoherence control and another PhD in neurobiology on mathematical models of curiosity, both from Weizmann Institute of Science, Israel. He was a postdoc at the Personal Robots Group in the Media Lab, MIT, researching how curious robots interact with curious children, where he also obtained a teaching certificate. He now heads the Curiosity Lab in Tel-Aviv University, Israel. His research interests are computational models of curiosity; quantitative assessment tools for curiosity; and curious social robots that learn about other agents in their environment, all by themselves.