Welcome to the Geometric Robot Learning Lab!
In the GeoRob Lab, we develop data-efficient robot learning, optimization, and control algorithms with sound theoretical guarantees. To do so, we follow an interdisciplinary approach that considers inductive bias, typically in the form of geometry and physics, as cornerstone.
Interested in joining us?
That’s great! All open positions are published on KTH careers page, through which all applications should also be submitted. The current vacancies for the GeoRob Lab, if any, are also advertised on my website (usually here).
PhD students
Loizos Hadjiloizou
Geometry and symmetries of operational space learning and control
Riccardo Morandi
Physics-informed geometric representation learning for deformable object manipulation
Katharina Friedl
Physics-informed geometric learning and control for dynamical systems
Main supervisor: Danica Kragic
Francesco Buso
Physics-informed geometric learning and control for deformable object manipulation
Postdocs
Generalizable imitation learning via inductive biases
Vision-based geometric robot learning for manipulation
External PhD students
Research Engineers
Ulises Campodónico
Martín Gallegos
Alumnis
Federico Pavesi
Bayesian optimization on Riemannian manifolds
Visiting PhD student, University of Milano-Bicocca
Lab life 🙂
