Position: Associate Professor
Office: 141.A31
Phone: +30-28210-37208
Fax: +30-28210-37542
Email: gehalk  intelligence.tuc.gr
Personal Page: http://www.intelligence.tuc.gr/~gehalk

Short CV

Georgios Chalkiadakis is an Associate Professor at the School of Electrical and Computer Engineering, Technical University of Crete (TUC). His research interests are in the areas of multiagent systems, algorithmic game theory, and machine learning; and more specifically, in coalition formation, decision making under uncertainty, reinforcement learning in multiagent domains, and in designing mechanisms and intelligent software systems for the Smart Grid. His PhD thesis (University of Toronto, 2007) was nominated for the IFAAMAS-2007 Victor Lesser Distinguished Dissertation Award. Georgios is a co-author of the graduate level textbook “Computational Aspects of Cooperative Game Theory” (Morgan and Claypool, 2011). He has also co-authored three book chapters in scientific collections, and has published more than 50 research papers in top international conferences and journals, and has over the years participated in many research projects. Georgios has served as an editorial board member of the Journal of Artificial Intelligence Research (JAIR), as a senior program committee or program committee member for several top international conferences, and as a reviewer for several top journals in his areas of expertise. Since March 2018, he is the Deputy Chair of the Board of Directors of the European Association for Multi-Agent Systems (EURAMAS); from Jan 2015 to Dec 2018, he served as the General Secretary of the Hellenic Artificial Intelligence Society (EETN). Before joining TUC, he was a Research Fellow at the School of Electronics and Computer Science, University of Southampton, UK. Georgios has also worked as a software engineer at the Institute of Computer Science of the Foundation for Research and Technology - Hellas, and as a teacher of informatics in Greek high schools. More information about Georgios can be found at his webpage: www.intelligence.tuc.gr/~gehalk

Education

• 2007: PhD in Computer Science, University of Toronto, Canada
• 1999: MSc in Computer Science, University of Crete, Greece
• 1997: BSc in Computer Science, University of Crete, Greece

Teaching

Undergraduate Courses

• COMP 201: Design and Development of Information Systems
  Description
  System Lifecycle/Development Methodologies. Object-Oriented Design and Development. Requirements capturing. Project Feasibility Study. System Analysis and System Design. UML and main types of UML diagrams (use-case, class, sequence, collaboration, state machines). User Interface Design basics. Java: interfaces, threads, exceptions, files, event processing. Analysis and Design Patterns.
  Courses Portal Link: Design and Development of Information Systems
  
• COMP 517: Multiagent Systems
  Description
  Agent types and characteristics. Multiagent systems and agent interactions. Links to Game Theory and Artificial Intelligence. Focus on agents that are rational utility maximizers. Decision making using utility theory, decision theory and game theory. Preferences, utility functions, utility maximization and rationality. Taking strategic decisions. One-shot and repeated strategic games. Nash equilibirum, Pareto optimality, and other game theoretic solution concepts. Equilibrium selection. Distributed problem solving. Coalitional games and coalition formation. Coalition formation applications (e-commerce, telecommunication networks, decentralized electricity market and the smart electricity grid). Trust and reputation. Bargaining and negotiations. Electronic auctions. Auctions and mechanism design. Auction and mechanism design applications (electronic auctions, ad auctions). Opponent modelling and learning in games. Connections to Machine Learning. Handling uncertainty. Multiagent systems' applications: agents in telecommunication/ad-hoc wireless/peer-to-peer networks, sensor networks, the smart electricity grid.
  Courses Portal Link: Multiagent Systems
  

Postgraduate Courses

• COMP 606: Decision Making and Learning in Multi-Agent Worlds
  Description
  Utility Theory, Decision Theory, and Game Theory (cooperative and non-cooperative). Rationality and strategic decision making. Reinforcement Learning and Multiagent Reinforcement Learning. Unsupervised Learning and Probabilistic Topic Modeling. Deep Learning and Deep Reinforcement Learning). Learning in Game-Theoretic Settings.
  Courses Portal Link: Decision Making and Learning in Multi-Agent Worlds
  

Supervision

• PhD Theses (2)
• M.Sc. Theses (6)
• Diploma Theses (1)

Publications

All Publications by Year




Publications by Category

• Conference Publications (50)
• Journal Publications (16)
• Workshop Proceedings (1)
• Books (1)
• Book Chapters (3)
• Proceedings (1)
• Miscellaneous (1)

Funding

• ViP: Visit Planner: Integrated Information and Tour Planning Service for Cruise Tourism based on Hybrid Recommender Systems.
  The goal of the project is the development of an integrated tourist services platform aiming at the best experience of the visitors of any city in Greece.
  [More information about this project] 
• PISMA: Automating Pistachio Canopy Temperature Identification: A Machine Learning Approach
  Employing existing and developing novel image recognition and machine learning techniques to determine the plant canopy temperature and, subsequently the irrigation requirements.
  [More information about this project]