TU Darmstadt, FG IAS,
Room E323, Building S2|02
Roberto Calandra joined Technische Universitaet Darmstadt (translates roughly as Darmstadt University of Technology) on January 2012 as a PhD student. There he will develop new "Probabilistic Methods in Learning for Control & Robotics" working with Jan Peters and Marc Deisenroth.
Previously, he achieved a Master degree in Machine Learning and Data Mining at the Aalto University (formerly known as Helsinki University of Technology or TKK) in Finland. There he had the opportunity to work on Gaussian Process as research assistant under the supervision of Aki Vehtari. Furthermore Roberto wrote his thesis An Exploration of Deep Belief Networks toward Adaptive Learning on the topic of Deep Learning under the supervision of Olli Simula with the collaboration of Federico Montesino Pouzols and Tapani Raiko.
Before, Roberto achieved his Bachelor in Computer Science engineering at the Università degli studi di Palermo in Italy. There he wrote his thesis Design and Build of a Robotics mobile platform [in Italian] under the supervision of Haris Dindo.
Roberto's main interest is what he calls "Artificial Stupidity", where opposite to the traditional Artifical Intelligence the emphasis is not on the "Intelligence" but on the adaptibility and continuous learning. For this purpose his interest includes but are not limited to: Machine Learning, Robotics and Self-organizing Systems.
The topic that he is currently developing is High-dimensional model-based Reinforcement Learning in the context of Robotics (which involves Gaussian Process modeling, Optimization, Reinforcement learning, and Deep Learning).
# Calandra, R.; Seyfarth, A.; Peters, J.; Deisenroth, M.P. (2014). An Experimental Comparison of Bayesian Optimization for Bipedal Locomotion, Proceedings of 2014 IEEE International Conference on Robotics and Automation (ICRA). See Details [Details] Download Article [PDF] BibTeX Reference [BibTex]
A full list of publications can be found on this page.
I am currently looking for students for 1 Master Thesis and 1 Bachelor Thesis. If you are interested, contact me as soon as possible.
* Supervisor Master Thesis: Kai Steinert - Heteroscedastic Gaussian Processes for control (co-supervised by Filipe Veiga)
Locomotion (supervised by Katayon Radkhah)
Supervisor Robot Learning Project Spring 2014: Schnell, F. - Advanced Bayesian optimization models
New bachelor & master thesis topics are available. If you are interested please contact me as soon as possible!