Alexei Novikov

Alexei Novikov is a Professor in the Department of Mathematics at Pennsylvania State University, affiliated with the Eberly College of Science. He holds a Ph.D. from Stanford University (1999). His research focuses on applied analysis, probability, stochastic processes, and their applications in fluid dynamics, imaging science, and materials modeling. Key areas include wave propagation in complex media, sparse signal recovery, and homogenization techniques for heterogeneous systems.

His teaching includes advanced courses such as Functional Analysis (Math 503), Stochastic Calculus (Math 519), and Differential Equations (Math 251). He has led NSF-funded research on transport phenomena in heterogeneous media and contributed to algorithm development for imaging in complex environments. Notable works include studies on eddy viscosity in cellular flows, network approximation methods, and fractional kinetic processes.

Novikov’s recent work emphasizes interdisciplinary applications, including neural network approaches for super-resolution imaging and stochastic models for knowledge diffusion. His publications span journals like Communications on Pure and Applied Mathematics, SIAM Journal on Mathematical Analysis, and Inverse Problems.