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.