معرفی
Mark Cannon is an Associate Professor in the Department of Engineering Science at the University of Oxford and a Tutorial Fellow at St John's College. He holds degrees from the University of Oxford (MEng in Engineering Science, DPhil) and MIT (SM). His research focuses on advanced control strategies, particularly Model Predictive Control (MPC), with applications in aerospace, biomedical systems, and energy management. He leads the Oxford Control Group, emphasizing robust and stochastic MPC, adaptive systems, and optimization under uncertainty. Notable contributions include works on deep learning integration in MPC for Parkinson’s disease treatment and energy-efficient hybrid electric aircraft.
His teaching includes courses on nonlinear systems, MPC, and dynamical systems. He has developed software like COSMO, an ADMM-based solver for convex optimization. Recent research highlights include publications on safe adaptive NMPC, robust MPC for VTOL aircraft, and data-driven control strategies.
Mark Cannon's work bridges theoretical control advancements with practical applications in engineering and healthcare, supported by collaborations in academia and industry.
