Georgios received his Ph.D. degree in computer science in 2002 from Michigan State University. From 2002 to 2004, he was a post-doctoral associate at the Computer Science and Artificial Intelligence Lab at M.I.T. In October 2004, he joined Intel Research as a research scientist and in July 2011, he joined Yahoo! Labs as a scientist. Finally he joined Adobe Research as a senior analytics researcher in July 2012.

Georgios’ interests include scaling up computational models of learning and planning under uncertainty and their applications to the real world. Specific areas of interest include reinforcement learning, completely and partially observable Markov decision processes (POMDPs), semi-Markov decision processes, hierarchical POMDPs, dynamic Bayesian nets, online learning with experts, general machine learning, information retrieval and big data processing.

His projects have evolved over time from building intelligent agents that interact with the world, such as robot navigation, to agents that interact one to one with people, such as a personal and physical math coin tutoring system, to large scale interactions, such as marketing and advertising agents that interact with millions of people. These interaction systems reason over the evolution of people’s behaviors and guide them to achieve long-term goals.