Postdoctoral Researcher at University of Tuebingen
Saint-Sulpice, Vaud, Switzerland
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Summary
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Bernardo Fichera is a postdoctoral researcher and machine learning scientist with a decade of experience bridging aerospace engineering, robotics, and geometric learning. Trained at Politecnico di Milano and Cornell, his PhD work at EPFL focused on leveraging differential geometry for control and learning, including manifold methods to extract energy functions and detect attractors in dynamical systems. He has hands-on experience deploying algorithms on real robot platforms (ABB YuMi, IRB 14000) and has developed spiking neural controllers and MPI-based cluster simulations for microrobotic flight. As a teaching lead for large ML courses at EPFL, he combines rigorous research with practical instruction and exam design for hundreds of students. Now at the University of Tübingen, he continues to translate theory into robot-ready algorithms, with a particular knack for marrying biologically inspired learning rules to continuous-time control problems. An uncommon strength is his fluency across scales—from neural-inspired controllers to spectral manifold analysis—making him adept at turning abstract math into tangible robotic behaviors.
10 years of coding experience
7 years of employment as a software developer
Master of Science - MS, Aerospace, Aeronautical and Astronautical/Space Engineering, Master of Science - MS, Aerospace, Aeronautical and Astronautical/Space Engineering at Politecnico di Milano
Doctor of Philosophy - PhD, Machine Learning & Robotics, Doctor of Philosophy - PhD, Machine Learning & Robotics at EPFL
Contributions:6 PRs, 31 pushes, 4 branches in 2 years
controlleractor-criticstabilityactorspiking
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Bernardo Fichera - Postdoctoral Researcher at University of Tuebingen