Jerome Bernard Darbon

Jerome Darbon is an Associate Professor of Applied Mathematics at Brown University, specializing in Hamilton-Jacobi equations, imaging sciences, optimal control, and optimization. His research emphasizes developing efficient algorithms for variational estimations, combinatorial optimization, and stochastic sampling, with applications in remote sensing, geomorphology, and medical imaging. He holds a Ph.D. from École Nationale Supérieure des Télécommunications (Paris, 2005) and has been recognized with awards including the CNRS Prime d’Excellence Scientifique (2010-2014) and the UCLA Chancellor’s Award for Postdoctoral Research (2009). His work bridges theoretical mathematics with practical computational methods, addressing high-dimensional problems through innovative approaches like neural network architectures and algorithm-architecture co-design.

Research Interests:

• Hamilton-Jacobi PDEs and their applications in control theory
• Imaging sciences, including denoising and image restoration
• Optimization techniques for compressive sensing and inverse problems
• Algorithm development for parallel architectures

Key Contributions:

• Developed methods to overcome the curse of dimensionality in Hamilton-Jacobi equations
• Advanced landscape evolution models using PDE-based simulations
• Contributed to SAR image regularization and InSAR phase reconstruction

Awards and Grants:

• NSF Grant DMS 1820821 (2018-2021) for work on variational decomposition models
• ONR Grant N00014-11-1-0749 (2011-2014) for combinatorial scientific computing

Teaching: Courses include Applied PDEs, Numerical Optimization, and Computational Linear Algebra.