Angello Astorga

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About

Angello Astorga is a leading researcher at the intersection of machine learning, formal methods, and safety-critical systems. His primary contributions lie in developing rigorous frameworks to ensure the reliability of ML-enabled autonomous systems, particularly those relying on neural perception. In his highly influential work, "Perception Contracts for Safety of ML-Enabled Systems" (2023, 15 citations), Astorga introduced a groundbreaking theory of perception contracts—a formal mechanism to reason about safety when controllers interact with their environment through imperfect neural perception. This work provides a principled way to characterize and bound errors in ground-truth estimations, ensuring that system invariants are preserved even when perception is inaccurate. By bridging the gap between formal verification and machine learning, Astorga's research offers a powerful methodology for certifying the safety of autonomous vehicles, drones, and robotics. His contributions are essential for engineers and researchers seeking to deploy AI in high-stakes environments where reliability is paramount.