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Omer San

Omer San


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

  • Pawarand 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
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