Panayiotis Danassis

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Research Scientist in AI at Telenor
panayiotis.danassis [at] telenor [dot] com

About me  Publications

I am a research scientist in AI at Telenor Research and an AI/ML research consultant.

I completed my postdoc at Harvard working with Milind Tambe to build AI systems with positive social impact, and my Ph.D. at the Artificial Intelligence Laboratory, École Polytechnique Fédérale de Lausanne (EPFL), under the supervision of Professor Boi Faltings (my thesis was nominated for distinction).

Prior to that, I studied Electrical and Computer Engineering at the National Technical University of Athens (NTUA) after which I was employed as a research associate at the Microprocessors and Digital Systems Laboratory (microLAB).


My Research

My research interests lie in the area of Artificial Intelligence (AI) for Social Good, drawing on the fields of multi-agent systems (cooperation & coordination), reinforcement learning, game theory, and Agentic AI. I have always been strongly motivated by the goal to provide practical solutions to societal challenges, having developed AI methods for mobility, sustainability of fisheries, and maternal health (e.g., see newspaper articles on a project I contributed at Harvard in collaboration with Google and ARMMAN: indiatoday, businesstoday, financialexpress).

I have led multidisciplinary research in collaboration with experts on diverse fields and stakeholders, including industry partners (Google, Telenor) and NGOs (ARMMAN). My work aims to facilitate the integration of intelligent agents in society by building AI systems that work in the real world, and result in positive social impact!

The true potential of intelligent systems will only be realized when they are tightly integrated into our daily lives. Such a future will involve a plethora of interacting autonomous learning agents mediating many aspects of our social, economic, cultural, and technological world, giving rise to complex machine behavior. Carefully designing autonomous learning systems and studying their behavior is, I believe, one of the most pressing problems we currently face in AI.