Georgios Theocharous

Senior Research Scientist

BigData Experience Lab, San Jose

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.

 

My Publications

Capacity-aware Sequential Recommendations

de Nijs, F., Theocharous, G., Vlassis, N., Weerdt, M., Spaan, M. (Jul. 10, 2018)
Proceedings of the 17th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2018),

Personalizable and Interactive Sequence Recommender System

Du, F., Malik, S., Theocharous, G., Koh, E. (Apr. 21, 2018)
CHI Extended Abstracts on Human Factors in Computing Systems

Interactive Campaign Planning for Marketing Analysts

Du, F., Malik, S., Koh, E., Theocharous, G. (Apr. 21, 2018)
CHI Extended Abstracts on Human Factors in Computing Systems

Importance of Recommendation Policy Space in Addressing Click Sparsity in Personalized Advertisement Display

Chaudhuri, S., Theocharous, G., Ghavamzadeh, M. (Jul. 17, 2017)
International Conference on Machine Learning and Data Mining in Pattern Recognition

An Interactive Points of Interest Guidance System

Theocharous, G., Vlassis, N., Wen, Z. (Mar. 13, 2017)
Proceedings of the 22nd International Conference on Intelligent User Interfaces

Automated Data Cleansing through Meta-Learning

Gemp, I., Theocharous, G., Ghavamzadeh, M. (Feb. 4, 2017)
Innovative Applications of Artificial Intelligence (IAAI)

Predictive Off-Policy Policy Evaluation for Nonstationary Decision Problems, with Applications to Digital Marketing

Thomas, P., Theocharous, G., Ghavamzadeh, M., Durugkar, I., Brunskill, E. (Feb. 4, 2017)
Innovative Applications of Artificial Intelligence (IAAI)

Graphical Model Sketch

Kveton, B., Bui, H., Ghavamzadeh, M., Theocharous, G., Muthukrishnan, S., Sun, S. (Sep. 19, 2016)
European Conference on Machine Learning and Knowledge Discovery in Databases

A Ranking Approach to Address the Click Sparsity Problem in Personalized Ad Recommendation

Chaudhuri, S., Theocharous, G., Ghavamzadeh, M. (Dec. 11, 2015)
Workshop: Machine Learning for eCommerce (NIPS) 2015.

Policy Evaluation Using the Ω-Return

Thomas, P., Niekum, S., Theocharous, G., Konidaris, G. (Dec. 1, 2015)
Neural Information Processing Systems (NIPS) 2015.

High Confidence Policy Improvement

Thomas, P., Theocharous, G., Ghavamzadeh, M. (Jul. 1, 2015)
International Conference on Machine Learning (ICML) 2015.

Personalized Ad Recommendation Systems for Life-Time Value Optimization with Guarantees.

Theocharous, G., Thomas, P., Ghavamzadeh, M. (Jul. 1, 2015)
International Joint Conference on Artificial Intelligence (IJCAI) 2015.

Ad Recommendation Systems for Life-Time Value Optimization

Theocharous, G., Thomas, P., Ghavamzadeh, M. (May. 1, 2015)
Workshop on Ad Targeting at Scale (WWW) 2015.

High Confidence Off-Policy Evaluation

Thomas, P., Theocharous, G., Ghavamzadeh, M. (Jan. 1, 2015)
Association for the Advancement of Artificial Intelligence (AAAI) 2015.

Lifetime Value Marketing Using Reinforcement Learning

Theocharous, G., Hallak, A. (Oct. 25, 2013)
The 1st Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM) 2013.

Structured Kernel-Based Reinforcement Learning

Kveton, B., Theocharous, G. (Jul. 14, 2013)
Association for the Advancement of Artificial Intelligence (AAAI) 2013.

Kernel-Based Reinforcement Learning on Representative States

Kveton, B., Theocharous, G. (Jul. 14, 2012)
Association for the Advancement of Artificial Intelligence (AAAI) 2012.

Towards a Physical and Personal Math Coin Tutoring System

Theocharous, G., Butko, N., Philipose, M. (Sep. 19, 2011)
Artificial Intelligence in Education (AIED) 2011.

Automated Facial Affect Analysis for one-on-one Tutoring Applications

Butko, N., Theocharous, G., Philipose, M., Movellan, J. (Mar. 19, 2011)
IEEE International Conference on Automatic Face and Gesture Recognition (FG) 2011.

Compressing POMDPs Using Locality Preserving Non-Negative Matrix Factorization

Theocharous, G., Mahadevan, S. (Jul. 14, 2010)
Association for the Advancement of Artificial Intelligence (AAAI) 2010.