Summary
Charlott Vallon is an Assistant Teaching Professor and Controls PhD candidate with eight years of experience bridging model-based control, machine learning, and robotics for autonomous systems. Her research develops model-based transfer learning and hierarchical predictive control methods for navigation in time-varying environments, with demonstrated real-world implementations on robotic manipulators and autonomous vehicles. She has translated theory into practice—designing and testing motion controllers on physical rail vehicles, building Simulink models to guide mechanical design, and implementing MPC learning on a UR5e playing Kendama. A skilled educator, she created hands-on vehicle dynamics labs at Berkeley that scaled to 100-student final competitions, and she brings that pedagogy to engineering instruction at UCSB. Charlott also studies the societal feedback loops of data-driven systems and how communication shapes public adoption of research, an uncommon but strategic lens for control engineers. Based in Berkeley, she pairs deep technical rigor with practical system validation and an eye for human-centered deployment.
7 years of coding experience
10 years of employment as a software developer
Doctor of Philosophy (PhD) Mechanical Engineering, Doctor of Philosophy (PhD) Mechanical Engineering at University of California, Berkeley
Master of Science (MSc) Mechanical Engineering, Master of Science (MSc) Mechanical Engineering at ETH Zürich
French, Spanish, German, English