Nicholas Barbara
Modern ML can bring complex systems to life in new and exciting ways, but it has much to learn from classical control about safety and robustness.
Nicholas Barbara is a postdoctoral scientist working in the Dependable Control and Decision (DECODE) group at EPFL. His research involves developing (mathematically certifiable) robust AI models for all things control, estimation, robotics, and more.
Previously, he was a postdoc in the Dynamics and Neural Systems Group at the University of Sydney from 2025–2026. He received his PhD from USYD in 2025, where he was part of the Australian Centre for Robotics (ACFR), as well as the combined B. Sci & B. Eng (Hons 1, University Medal) degrees in 2021. His interests span control systems, neural-network design, robust machine learning, and their applications to robotic control. In his spare time, you'll find him on a cricket field, up a mountain, or somewhere quiet with a good book.
