About
Melvin Leok is a professor of mathematics at the University of California, San Diego, where his research is supported by grants from NSF, AFOSR, and DoD, including the NSF CAREER Award, and the DoD Newton Award for Transformative Ideas. He is a NAS Kavli Frontiers of Science Fellow, a Simons Fellow in Mathematics, and received the SciCADE New Talent Prize, SIAM Student Paper Prize, and Leslie Fox Prize in Numerical Analysis. He gave plenary talks at Foundations of Computational Mathematics, NUMDIFF, and the IFAC Workshop on Lagrangian and Hamiltonian Methods for Nonlinear Control.
He is affiliated with the Center for Control Systems and Dynamics, the Contextual Robotics Institute, the Halicioglu Data Science Institute, and the NSF AI Institute, TILOS.
Available as a consultant for modeling, simulating, controlling, quantifying uncertainty, machine learning, and optimization for large scale interconnected systems that evolve on nonlinear configuration spaces.
Melvin Leok is a professor of mathematics at the University of California, San Diego, where his research is supported by grants from NSF, AFOSR, and DoD, including the NSF CAREER Award, and the DoD Newton Award for Transformative Ideas. He is a NAS Kavli Frontiers of Science Fellow, a Simons Fellow in Mathematics, and received the SciCADE New Talent Prize, SIAM Student Paper Prize, and Leslie Fox Prize in Numerical Analysis. He gave plenary talks at Foundations of Computational Mathematics, NUMDIFF, and the IFAC Workshop on Lagrangian and Hamiltonian Methods for Nonlinear Control.
He is affiliated with the Center for Control Systems and Dynamics, the Contextual Robotics Institute, the Halicioglu Data Science Institute, and the NSF AI Institute, TILOS.
Available as a consultant for modeling, simulating, controlling, quantifying uncertainty, machine learning, and optimization for large scale interconnected systems that evolve on nonlinear configuration spaces.