At learnCPS, we bring together learning, optimization, and control theory to study intelligent Cyber-Physical-Human Systems.

learnCPS research topics learnCPS research topics

If you are interested in joining, send us an email at christos.mavridis [at] tuwien.ac.at.
Use title "Interest in joining learnCPS" and include:

  • your interest in a specific job opening (if any)
  • your research background and experience
  • your research interests and how they connect to publications that you liked from our lab (see Publications page)
  • your CV with complete list of publications (if applicable)


Research Directions

We tackle inference and control problems in various Cyber-Physical-Human Systems, from autonomous cars to UAV swarms, and from industrial robots to collaborative human-robot systems. We focus on the analysis of the underlying learning algorithms using principles from:

  • hybrid systems theory
  • stochastic optimization
  • robust and risk-sensitive control
  • knowledge representation and reasoning
  • group-invariant and hierarchical topologies
  • homotopy optimization and bifurcation theory

Beyond fundamental research on Optimization, Learning Theory, (Hybrid) Systems and Control Theory, and Multi-Agent Systems, we are interested in a wide range of applications, including:

  • Robotics, Autonomous Vehicles, UAVs
  • Explainable AI & Learning-based Control
  • Human-Robot Interaction & Collaboration
  • Risk-Sensitive Reinforcement Learning
  • Communication-aware Robotics
  • Swarm Dynamics Identification
  • Intelligent Transportation
  • Smart Cities