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.
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 for a provably robust collaborative autonomy against attacks and failures, identifying fundamental limits, and contributing provably optimal algorithms. I focus on deception and denial-of-service attacks and failures that lie beyond the reach of cybersecurity and classical control, requiring novel algorithmic foundations for resilient collaborative autonomy. I develop such algorithms by building on fundamental tools of automatic control, robotic perception, statistics, combinatorial and non-convex optimization, and computational complexity. Broadly, the developed algorithms apply from multi-robot systems (e.g., robust multi-robot planning with limited communication) to resilient infrastructures (e.g., robust estimation in smart grids).
Towards the IoR2T, I plan for a technological convergence between (i) “cyber” capabilities for a distributed artificial intelligence, driven by adaptive learning and robust data-driven perception and control algorithms, and (ii) “physical” capabilities of self-reconfigurable systems and structures, self-healing materials, and smart devices.
Ultimately, my goal is a future of collaborative autonomous systems that will reliably support our efforts in safety-critical sectors, such as
- emergency response services, such as localizing people in burning buildings, e.g., with teams of agile aerial vehicles;
- transportation, such as minimizing congestion, e.g., with intelligent self-driving flying cars;
- environmental health and defense, such as predicting disastrous environmental conditions, or monitoring adversarial behavior, e.g., with continuous sensing driven by air-space-sea-land autonomous systems,
even if the systems operate at extreme environmental conditions, and in the presence of dynamic attacks and failures.
- Invited seminar at the Mechanical Engineering Department, Massachusetts Institute of Technology (MIT); Seminar title: Algorithmic Foundations of Resilient Collaborative Autonomy: From Robust Combinatorial Optimization to Perception and Control.
- Invited seminar at the Electrical Engineering Department, Harvard University; Seminar title: Algorithmic Foundations of Resilient Collaborative Autonomy: From Robust Combinatorial Optimization to Perception and Control.
- Invited seminar at the Aerospace Engineering Department, University of Michigan; Seminar title: Algorithmic Foundations of Resilient Collaborative Autonomy: From Robust Combinatorial Optimization to Perception and Control.
- 10/16/19: Promoted to research scientist.
- 09/24/19: New paper on Robust and Adaptive Sequential Submodular Optimization, with Ali Jadbabaie and George J. Pappas.
- 09/11/19: New paper on Graduated Non-Convexity for Robust Spatial Perception: From Non-Minimal Solvers to Global Outlier Rejection,with Heng (Hank) Yang, Pasquale Antonante, and Luca Carlone.