drawing

Book

B.C. Vermeire, C.A. Pereira, H.R. Karbasian, Computational Fluid Dynamics: An Open-Source Approach, Concordia University Press, 2020.


Thesis


Patent

H.R. Karbasian, N. Saghatoleslami, Mechanical respiratory system for underwater breathing (Mechanical gill), No. 71062 B/ 390010253 App. Iranian Patent, 2011.


Peer-reviewed articles


Invited talks

  • H.R. Karbasian, Design in Chaos: High-Fidelity Aerodynamic Optimization Using Novel Physics Constrained Machine Learning, Department of Mechanical and Aerospace Engineering, University of California, Davis, Feb. 2022.

  • H.R. Karbasian, Physics-constrained data-driven reduced-order modelling for large-scale optimizations, National Research Council Canada, Dec. 2021.

  • H.R. Karbasian, Sensitivity analysis and uncertainty quantification using novel physics-constrained machine learning, Department of Mathematics and Statistics, Utah State University, Sep. 2021.

  • H.R. Karbasian, B.C. Vermeire, Design in Chaos, University of Toronto Institute for Aerospace Studies, Toronto, Canada, Apr. 2021.

  • H.R. Karbasian, Design in Chaos, Department of Mechanical Engineering, The University of British Columbia, Vancouver, Canada, Apr. 2021.

  • H.R. Karbasian, B.C. Vermeire, Shadow of the Chaos, University of Toronto Institute for Aerospace Studies, Toronto, Canada, Nov. 2020.


Conference papers & presentations (refereed)


Hamid R. Karbasian

Postdoctoral Research Associate
Department of Mechanical Engineering
Masschusetts Institute of Technology
Cambridge, USA

Email: karbasian [at] mit [dot] edu
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https://www.mit.edu/