About

I am a Noah Harding Chair and professor in the Department of Computational Applied Mathematics & Operations Research at Rice University.

Google Scholar.        orcid.org/0000-0002-9305-4221

PostDoc Opening

I expect an opening for a postdoc position with start date Jan 1 or July 1, 2024. This opening will be part of our search for Pfeiffer Postdoctoral Instructors. I am looking for highly motivated applicants working in optimization, reduced order modeling, and parameter identification of large-scale differential equation based models. Successful applicants will work on one of two interdisciplinary projects: Optimization of biophysical models for single neurons, or multi-physics design analysis and optimization grounded in rigorous model reduction. The ideal candidate has a strong background in computational and applied mathematics, is familiar with continuous optimization, numerical solution of differential equations, and model reduction, and development of mathematical software, and has good communication skills.

Pfeiffer Postdoctoral Instructors teach one undergraduate lecture course each semester and conduct research in collaboration with a faculty mentor.

The position will be advertised later this fall. Please check back!

Research Training Group in Numerical Mathematics & Scientific Computing (NASC)

Profs. Beatrice Riviere, Jesse Chan, and I were awarded an National Science Foundation grant for our Research Training Group in Numerical Mathematics & Scientific Computing (NASC). This RTG trains the next generation of scientists in NASC and its applications, preparing researchers in computational and applied mathematics for both industry and academic careers. It provides many exciting training and research opportunities for undergraduate and graduate students, as well as postdocs. Please visit the Research Training Group in Numerical Mathematics & Scientific Computing (NASC) web-page for more information.

Research Interests

My group's research is concerned with the design and analysis of mathematical optimization algorithms for nonlinear, large-scale (often infinite dimensional) problems and their applications to science and engineering problems. Specific research areas include large-scale nonlinear optimization, model order reduction, optimal control of partial differential equations (PDEs), optimization under uncertainty, PDE constrained optimization, iterative solution of KKT systems, domain decomposition in optimization. Applications come in form of parameter identification, optimal control, or shape optimization problems. The snapshots above are samples from work performed in my group.