Akhtar Khan

Akhtar Khan is a Professor in the School of Mathematics and Statistics at Rochester Institute of Technology (RIT), part of the College of Science. He joined RIT's School of Mathematical Sciences in 2008 and advises students in applied and computational mathematics. His research focuses on inverse problems, uncertainty quantification, optimal control, numerical optimization, and PDE-constrained optimization. He holds an MS from Technical University Kaiserslautern (Germany) and a Ph.D. from Michigan Technological University.

Current teaching responsibilities include courses such as Linear Algebra (MATH-241), Boundary Value Problems (MATH-326), Numerical Linear Algebra (MATH-412), and Optimization Theory (MATH-603). His work spans theoretical advancements in variational inequalities and practical applications in imaging and stochastic systems.

Recent research highlights include contributions to stochastic inverse problems in partial differential equations and regularization frameworks for tumor identification. He collaborates internationally, exemplified by hosting the Abel Visiting Scholar Nguyen Thi Van Anh in 2023. His publications include monographs like Uncertainty Quantification in Variational Inequalities (2021) and edited volumes on deterministic and stochastic control systems.

Awards and recognitions are not explicitly listed, but his extensive publication record and editorial roles (e.g., Deterministic and Stochastic Optimal Control and Inverse Problems) underscore scholarly impact. He actively mentors students through independent studies and graduate research (MATH-790).