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  1. www.linkedin.com › in › jduraisamyJay Duraisamy - Fiserv | LinkedIn

    View Jay Duraisamy’s profile on LinkedIn, a professional community of 1 billion members. Jay is a hands on senior technology executive/cto with passion to deliver business and…

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    • Fiserv
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  2. www.sciencedirect.com › science › articleA paradigm for data-driven predictive modeling using field...

    Jan 15, 2016 · Abstract. We propose a modeling paradigm, termed field inversion and machine learning (FIML), that seeks to comprehensively harness data from sources such as high-fidelity simulations and experiments to aid the creation of improved closure models for computational physics applications.

    • Eric J. Parish, Karthik Duraisamy
    • 2016

  3. arc.aiaa.org › doi › 10Machine-Learning-Augmented Predictive Modeling of Turbulent...

    Apr 27, 2017 · Karthik Duraisamy. Published Online:27 Apr 2017 https://doi.org/10.2514/1.J055595. Abstract. A modeling paradigm is developed to augment predictive models of turbulence by effectively using limited data generated from physical experiments.

    • Anand Pratap Singh, Shivaji Medida, Karthik Duraisamy
    • 2017

  4. websites.umich.edu › ~caslab › docsPhysics-constrained Data-driven modeling Learning & Inference Non...

    Duvall, J., Duraisamy, K., and Pan, S., “Non-linear Independent Dual System (NIDS) for Discretization- independent Surrogate Modeling over Complex Geometries,” arXiv:2109.07018, 2021. 2.

  5. arc.aiaa.org › doi › absMachine Learning Methods for Data-Driven Turbulence Modeling

    Jun 18, 2015 · Machine Learning Methods for Data-Driven Turbulence Modeling. Ze Jia Zhang. and. Karthikeyan Duraisamy. AIAA 2015-2460. Session: Turbulence Modeling and Uncertainty Quantification.

  6. www.cambridge.org › core › journalsReynolds averaged turbulence modelling using deep neural networks...

    Oct 18, 2016 · There exists significant demand for improved Reynolds-averaged Navier–Stokes (RANS) turbulence models that are informed by and can represent a richer set of turbulence physics. This paper presents a method of using deep neural networks to learn a model for the Reynolds stress anisotropy tensor from high-fidelity simulation data.

  7. www.rottentomatoes.com › celebrity › j_duraisamyJ. Duraisamy | Rotten Tomatoes

    Explore the filmography of J. Duraisamy on Rotten Tomatoes! Discover ratings, reviews, and more. Click for details!