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The Center for Computational Mathematics (CCoM) consists of a broad and diverse group of faculty, researchers, and students, who share a common interest in the mathematical aspects of computation. Research interests that are represented in the group include the theoretical analysis and development of numerical algorithms, and modeling and simulation of complex physical, biological, and engineering systems. A unique aspect of the CCoM group is the concurrent emphasis on mathematics, computation, and applications. This is achieved through a combination of rigorous mathematical analysis, and practical numerical implementation, while being motivated and informed by nontrivial real world applications.

The CCoM Group plays a lead role in UCSD's recently launched campus-wide interdisciplinary doctoral and masters programs in Computational Science, Mathematics, and Engineering (CSME). The CSME graduate program combines the three Physical Sciences departments (Mathematics, Chemistry & Biochemistry, and Physics) with three core engineering departments (Computer Science & Engineering, Mechanical & Aerospace Engineering, and Structural Engineering) to form a unique graduate training program that provides a combination of training in domain expertise with state-of-the-art mathematical and software tools for modern computational science. More information about this new graduate program may be found on the CSME website.

News and Announcements


CCoM Seminar
Tuesday, March 14, 2023
11:00 AM / AP&M 2402 and Zoom ID 994 0149 1091
Minimum-norm Perturbations and Regularization in Modified Newton Methods for Unconstrained Optimization
Jeb Runnoe, UCSD

CCoM Seminar
Tuesday, March 7, 2023
11:00 AM / Zoom ID 994 0149 1091 (Zoom ONLY today)
Distributionally Robust Optimization with Moment Ambiguity Sets
Jiawang Nie, UCSD

CCoM Seminar
Tuesday, February 14, 2023
11:00 AM / AP&M 2402 and Zoom ID 994 0149 1091
Monotone meshfree methods for linear elliptic equations in non-divergence form via nonlocal relaxation
Qihao Ye, UCSD

CCoM Seminar
Tuesday, January 31, 2023
11:00 AM / AP&M 2402 and Zoom ID 994 0149 1091
Deep Learning on Graphs and Manifolds via the Geometric Scattering Transform
Mike Perlmutter, UCLA