Machine learning and robotics Postdoctoral Researcher with a strong Computer Science and Engineering background, focusing on scalable algorithms for predictive modeling, incremental lifelong learning and applications in robotics, visual recognition and dynamics learning.
Raffaello Camoriano received the B. Sc. cum laude in Computer Engineering (2011) and the M. Sc. with top grades in Robotics Engineering (2013) from the University of Genoa (UNIGE), Italy. He completed his Ph. D. at UNIGE in 2017, working at the Italian Institute of Technology (IIT) under the supervision of Prof. Giorgio Metta and Prof. Lorenzo Rosasco.
He currently is a Postdoctoral Researcher with the IIT, where he investigates efficient large-scale learning algorithms, incremental lifelong learning, reinforcement learning, and applications in robot vision and dynamics learning.
He is author of 10 international peer-reviewed articles in the fields of machine learning and robotics.
Dr. Camoriano won the IEEE Computational Intelligence Society Italy Section Chapter’s 2017 Best Ph. D. Thesis Award for his Thesis "Large-scale Kernel Methods and Applications to Lifelong Robot Learning".
Other interests: Control Theory, Screw Theory, A.I. in general
LinkedIn profile: it.linkedin.com/in/raffaellocamoriano/en
DIBRIS page: http://www.dibris.unige.it/en/camoriano-raffaello
LCSL (IIT @ MIT) page: http://lcsl.mit.edu/#/people