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 for a bit over a year.  I work with Luca Carlone (LIDS/AeroAstro).

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 in 2017 IEEE Conference on Decision and Control (CDC).  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.

Research interests

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

My goal is to enable an Internet of Resilient Robotic Teams (IoR2T), where mobile robots in the wild will not only withstand attacks and failures but also adapt and recover.  To this end, I have worked on robotics and control towards a provably robust autonomy against deception and denial-of-service attacks and failures, identifying fundamental limits, and contributing provably optimal algorithms.  I have built on fundamental tools of automatic control, robotic perception, statistics, combinatorial and non-convex optimization, and computational complexity.
Towards the IoR2T, I plan to wed tools for a robust autonomy with tools for a multi-robot distributed intelligence that is driven by adaptive learning and control capabilities.

Ultimately, my goal is a future where mobile robots will reliably support our efforts in safety-critical tasks of

  • search and rescue, e.g., localizing people in burning buildings;
  • autonomous navigation, e.g., self-driving cars; and
  • surveillance, e.g., tracking adversarial behavior,

even if the robots need to operate at extreme navigational speeds, in extreme environmental conditions, and in the presence of dynamic attacks and failures.

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