Alonso Marco-Valle

Alonso Marco-Valle is a Senior Robotics/AI Engineer at Figure AI, where he develops control algorithms for humanoid robots and machine learning systems. Previously, he held a Postdoctoral Research Fellow (Research Fellow) position at the Hybrid Systems Lab at the University of California Berkeley, focusing on safe autonomous systems with out-of-distribution monitoring.

• PhD: Robotics and Machine Learning, Max Planck Institute for Intelligent Systems and University of Tübingen, Germany
• MSc: Artificial Intelligence, Polytechnical University of Catalonia, Spain

His research spans robotics, machine learning, and control theory, with specific interests in Bayesian optimization, Gaussian processes, model-based reinforcement learning, and safe learning frameworks. He has contributed to out-of-distribution detection, probabilistic dynamical models, and failure-aware optimization algorithms that balance exploration with risk.

His recent publications focus on data-efficient learning, safety in autonomous systems, and physics-informed probabilistic modeling. Awards include the Rafael del Pino Excellence Fellowship, a highly competitive recognition for Spanish researchers.

Collaborations include work with leading researchers such as Prof. Claire J. Tomlin (UC Berkeley), Prof. Sebastian Trimpe (Max Planck), Prof. José Miguel Hernández-Lobato (Cambridge), and Prof. Philipp Hennig (Max Planck), with research stays at institutions like Stanford, NASA ULI, and Meta AI.