I start as an assistant professor at the University of Michigan (U-M, Ann Arbor) on January 2021, Department of Aerospace Engineering (Aero). Currently, I am a research scientist at the Massachusetts Institute of Technology (MIT), Department of Aeronautics and Astronautics (AeroAstro), and Laboratory for Information & Decision Systems (LIDS).  Before that, I was a post-doctoral associate at AeroAstro and LIDS.  I work with Luca Carlone (AeroAstro/LIDS).

I did my PhD at the University of Pennsylvania (UPenn), Department of Electrical and Systems Engineering (2018).  During the summer and fall of 2017, I was a visiting PhD student at MIT, Institute for Data, Systems, and Society (IDSS).  My PhD advisors were George J. Pappas (UPenn), and Ali Jadbabaie (MIT). I was a Best Student Paper Award finalist, at the 2017 IEEE Conference on Decision and Control (CDC).  My co-authors and I received the Best Paper Award in Robot Vision, at the 2020 International Conference on Robotics and Automation (ICRA). Before my PhD, I completed my undergraduate studies at the National Technical University of Athens (NTUA), Department of Electrical and Computer Engineering. My undergraduate thesis advisors were Trifon Koussiouris and Evangelos Markakis.

Here are links to my Google Scholar and ORCID profiles, and to my CV (updated June 2020).

Research interests

Research pillars for an Internet of Resilient Robotic Teams (IoR2T)

I care for a trustworthy collaborative autonomy, with emphasis on aerospace systems.  I work at the intersection of learning, perception, control, and combinatorial optimization for an Internet of Resilient Robot Teams (IoR2T), where autonomous systems can safely and effectively collaborate with each other despite attacks and failures that result to agent removals and deceptions. I care identifying fundamental optimization limits, and developing provably optimal algorithms and experimentally verified systems. I build on tools of control, perception, machine and statistical learning, game theory, computational complexity, and non-convex and combinatorial optimization. Long term, I plan for a technological convergence between (i) “cyber” capabilities for a distributed intelligence, driven by adaptive learning and resource-aware control and perception algorithms, and (ii) “physical” capabilities of self-reconfigurable robotic and aerospace systems, self-healing materials, and smart devices.

Ultimately, I aim for a trustworthy distributed collaborative autonomy that will reliably support via novel aerospace robot systems critical tasks.

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