Gianni Di Caro

Teaching Professor, Computer Science

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Before joining CMU-Q 2016, Di Caro held a permanent senior research position at Dalle Molle Institute for Artificial Intelligence (IDSIA), in Switzerland. During his career, he has been awarded three individual Marie Curie / TMR and one Japan Science and Technology fellowships. He has been a researcher at Istituto per la ricerca scientifica e tecnologica (IRST) in Trento, Italy, University of Trento, Université Libre de Bruxelles (ULB) in Brussels, Belgium, and Advanced Telecommunications Research (ATR) in Kyoto, Japan. Di Caro has published more than 130 peer-reviewed works that have received about 25,000 citations. He has been granted more than 3.5M USD in grants and an individual, project coordinator and co-PI.


Ph.D. in Applied Sciences with full honors, Université Libre de Bruxelles, Brussels, Belgium 

D.E.A. (Diplome d'Etudes Approfondies / Master of Applied Sciences), Université Libre de Bruxelles, Brussels, Belgium

Laurea in Physics, magna cum laude, University of Bologna, Italy

Area Of Expertise

  • Swarm and collective intelligence 
  • Swarm robotics 
  • Multi-robot systems 
  • Autonomous robotics 
  • Human-(multi)robot interaction 
  • Optimization 
  • Artificial intelligence 
  • Networked systems

Research Description

Di Caro has a truly multi- and inter-disciplinary expertise. In the past 25 years he has been working on a number of research topics in the domains of parallel and distributed computing, artificial intelligence, swarm intelligence, combinatorial optimization, telecommunication networks, modeling of biological systems, autonomous robotics, distributed and swarm robotics and human-robot interaction. He co-authored the work that laid down the formal foundations of the Ant Colony Optimization metaheuristic, and he developed the algorithms that are de facto the main references for swarm intelligence in network optimization. Di Caro has co-authored pioneering research in swarm robotics, in particular networked swarms and human-swarm interaction. His recent work focuses on planning and coordination in mobile multi-robot systems, integration of networking and control, and use of learning techniques for robot recognition and navigation tasks. In a new research project, he will explore various interaction and coordination  issues in heterogeneous teams of autonomous aerial and aquatic robots.

Courses Taught

  • 15-381/781: Artificial Intelligence: Representation and Problem Solving 
  • 16-311: Introduction to Robotics 
  • 15-382: Collective Intelligence