Francesco Borrelli
Mechanical Engineering
University of California Berkeley
About Professor Francesco Borrelli
The University of California Berkeley, particularly its Department of Mechanical Engineering, stands as a global leader in engineering innovation and research. Consistently ranked among the world's top programs, UC Berkeley Mechanical Engineering is renowned for its pioneering contributions across diverse fields, from advanced materials to robotics and energy systems. The department fosters a dynamic academic environment, attracting exceptional faculty and students committed to addressing complex challenges through groundbreaking research. Professor Francesco Borrelli is a distinguished member of this faculty, contributing significantly to the department’s reputation for excellence in control systems and their diverse applications. His work exemplifies UC Berkeley’s commitment to pushing the boundaries of scientific discovery and technological advancement.
🧬Research Focus
Professor Borrelli’s research profoundly impacts critical areas including model predictive control (MPC), automotive systems, autonomous vehicles, and sustainable energy systems. His work in robust control and distributed control frameworks is pivotal for developing safe and efficient autonomous decision-making in complex environments. This expertise extends to solar power optimization, where his innovations contribute to maximizing energy capture and grid stability. Furthermore, his research integrates robotics and AI, exploring intelligent control solutions for next-generation automated systems. These interdisciplinary contributions drive advancements in areas from enhanced vehicle autonomy and energy management to more adaptive robotic systems, promising significant real-world breakthroughs in efficiency, safety, and sustainability across industries.
🎓Student Fit & Career
Graduate students aspiring to conduct high-impact research in advanced control systems and their real-world applications would find an exceptional academic mentorship opportunity with Professor Borrelli. Ideal PhD students will possess a strong foundation in control theory, optimization, and programming, coupled with a keen interest in bridging theoretical concepts with practical implementation in fields like autonomous driving, robotics, or energy management. Students in his group can expect to develop cutting-edge skills in model predictive control, distributed control, and AI integration. Graduates are well-prepared for leading roles in academia, advanced R&D in the automotive, aerospace, or energy sectors, and innovative technology companies driving the future of intelligent systems.
Research Areas
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