Akhtar Khan
Professor
School of Mathematics and Statistics
College of Science
585-475-6367
Office Hours
TTh 12:30PM -1:30PM, or by appointment
Office Location
Office Mailing Address
Gosnell Hall 2308, 85 Lomb Memorial Drive, Rochester, NY 14623
Akhtar Khan
Professor
School of Mathematics and Statistics
College of Science
Education
MS, Technical University Kaiserslautern (Germany); Ph.D., Michigan Technological University
Bio
- Joined School of Mathematical Sciences at RIT in 2008.
- I advise undergraduate and graduate students in research in applied and computational mathematics.
585-475-6367
Areas of Expertise
Inverse Problems
Uncertainty Quantification
Optimal Control
Numerical Optimization
Parameter Identification
PDE Constrained Optimization
Set-valued Optimization
Variational and Quasi-Variational Inequalities
Regularization
Elasticity Imaging
Select Scholarship
- Uncertainty Quantification in Variational Inequalities: Theory, Numerics, and Applications. Joachim Gwinner, Baasansuren Jadamba, Akhtar A. Khan, Fabio Raciti, monograph, Taylor & Francis (2021)
- Introduction to Set-Valued Optimization. Akhtar A. Khan, Christiane Tammer, Constantin Zalinescu, monograph, Springer (2014)
- Deterministic and Stochastic Optimal Control and Inverse Problems. Baasansuren Jadamba, Akhtar A. Khan, Stanislaw Migorski, and Miguel Sama (editors), Taylor & Francis (2021)
- Variational Analysis and Set Optimization. Akhtar A. Khan, Elisabeth Koebis, Christiane Tammer (editors), Taylor & Francis (2019)
- B. Jadamba, A. A. Khan, M. Sama, H-J. Starkloff, Chr. Tammer, A Convex Optimization Framework for the Inverse Problem of Identifying a Random Parameter in a Stochastic Partial Differential Equation, SIAM/ASA J. Uncertainty Quantification, 9 (2), 922-952 (2021)
- S. Zeng, S. Migórski, A. A. Khan, Nonlinear Quasi-Hemivariational Inequalities: Existence and Optimal Control, Siam J. Control Optim., 59, 1246-1274 (2021)
Currently Teaching
MATH-241
Linear Algebra
3 Credits
This course is an introduction to the basic concepts of linear algebra, and techniques of matrix manipulation. Topics include linear transformations, Gaussian elimination, matrix arithmetic, determinants, vector spaces, linear independence, basis, null space, row space, and column space of a matrix, eigenvalues, eigenvectors, change of basis, similarity and diagonalization. Various applications are studied throughout the course.
MATH-326
Boundary Value Problems
3 Credits
This course provides an introduction to boundary value problems. Topics include Fourier series, separation of variables, Laplace's equation, the heat equation, and the wave equation in Cartesian and polar coordinate systems.
MATH-412
Numerical Linear Algebra
3 Credits
This course covers numerical techniques for the solution of systems of linear equations, eigenvalue problems, singular values and other decompositions, applications to least squares, boundary value problems, and additional topics at the discretion of the instructor.
MATH-498
Independent Study in Mathematical Sciences
1 - 3 Credits
This course is a faculty-guided investigation into appropriate topics that are not part of the curriculum.
MATH-602
Numerical Analysis I
3 Credits
This course covers numerical techniques for the solution of nonlinear equations, interpolation, differentiation, integration, and matrix algebra.
MATH-603
Optimization Theory
3 Credits
This course provides a study of the theory of optimization of linear and nonlinear functions of several variable with or without constraints. The theory is applied to solve problems in business, management, engineering, and the sciences. Algorithms for practical applications will be analyzed and implemented. Students taking this course will be expected to complete applied projects and/or case studies.
MATH-790
Research & Thesis
0 - 9 Credits
Masters-level research by the candidate on an appropriate topic as arranged between the candidate and the research advisor.
MATH-799
MATH GRADUATE Independent Study
1 - 3 Credits
Independent Study