Omer San
Education
Ph.D., Engineering Mechanics
Virginia Tech, 2012
M.S., Aerospace Engineering
Old Dominion University, 2007
B.S., Aeronautical Engineering
Istanbul Technical University, 2005
Research Interests
- Fluid dynamics
- large eddy simulations
- high performance computing
- trustworthy AI
- scientific machine learning
- big data cybernetics
- digital twin
- exascale computing
- heterogeneous computing
- data assimilation
- uncertainty quantification
- optimization and control
- model reduction
Awards and Recognition
- CEAT Excellent Scholar Award, Oklahoma State University, 2020
- U.S. Department of Energy Early Career Research Program Award in Applied Mathematics, 2018
Professional Memberships
- American Physical Society (APS)
- Society for Industrial and Applied Mathematics (SIAM)
- American Institute of Aeronautics and Astronautics (AIAA)
Courses Taught
- MAE 3013 Engineering Analysis and Methods
- MAE 5093 Engineering Numerical Analysis
- MAE 5283 Data Assimilation in Science and Engineering
Recent Publications
- Pawar† and O.San. Data assimilation empowered neural network parameterizations for subgrid processes in geophysical flows.Accepted 16 November 2020, Physical Review Fluids (In Press, pp. 1–28)
- C. Mou, B. Koc, O.San, L. G. Rebholz, and T. Iliescu. Data-driven variational multiscale reduced order models.Computer Methods in Applied Mechanics and Engineering, 373:113470,2021
- S. Pawar†, S. E. Ahmed†, and O.San. PyDA: A hands-on introduction to dynamical data assimilation with Python.Fluids, 5(4):225, 2020
- S. E. Ahmed†, O.San, K. Kara, R. Younis, and A. Rasheed. Interface learning of multiphysics and multiscale systems.Physical Review E, 102(5):053304, 2020
- S. E. Ahmed†, K. Bhar†, O.San, and A. Rasheed. Forward sensitivity approach for estimating eddy viscosity closures in nonlinear model reduction.Physical Review E, 102:043302, 2020