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A Work in Progress
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portfolio
Google Summer of Code
Published:
Here I will document work done in fulfillment of the project NumFocus & SciML, PDEs on Graphs.
publications
Physics Informed Machine Learning of SPH: Machine Learning Lagrangian Turbulence
Published in arXiv preprint arXiv:2110.13311, 2021
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Recommended citation: Michael Woodward, Yifeng Tian, Criston Hyett, Chris Fryer, Daniel Livescu, Mikhail Stepanov, Michael Chertkov, "Physics Informed Machine Learning of SPH: Machine Learning Lagrangian Turbulence." arXiv preprint arXiv:2110.13311, 2021.
Lagrangian Large Eddy Simulations via Physics Informed Machine Learning
Published in arXiv preprint arXiv:2207.04012, 2022
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Recommended citation: Yifeng Tian, Michael Woodward, Mikhail Stepanov, Chris Fryer, Criston Hyett, Daniel Livescu, Michael Chertkov, "Lagrangian Large Eddy Simulations via Physics Informed Machine Learning." arXiv preprint arXiv:2207.04012, 2022.
Physics-informed Machine Learning for Reduced-order Modeling of Lagrangian Turbulence
Published in Bulletin of the American Physical Society, 2022
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Recommended citation: Yifeng Tian, Michael Woodward, Mikhail Stepanov, Chris Fryer, Criston Hyett, Michael Chertkov, Daniel Livescu, "Physics-informed Machine Learning for Reduced-order Modeling of Lagrangian Turbulence." Bulletin of the American Physical Society, 2022.
Control of Line Pack in Natural Gas System: Balancing Limited Resources under Uncertainty
Published in arXiv2304.01955, 2023
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Recommended citation: Criston Hyett, Laurent Pagnier, Jean Alisse, Lilach Sabban, Igal Goldshtein, Michael Chertkov, "Control of Line Pack in Natural Gas System: Balancing Limited Resources under Uncertainty." arXiv2304.01955, 2023.
talks
Machine Learning Statistical Lagrangian Geometry of Turbulence
Published:
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Recommended citation: Criston Hyett, Michael Chertkov, Yifeng Tian, Daniel Livescu, "Machine Learning Statistical Lagrangian Geometry of Turbulence." In the proceedings of APS Division of Fluid Dynamics Meeting Abstracts, 2020.
Data-Analysis of the Coarse-Grained Velocity Gradient Tensor
Published:
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Recommended citation: Criston Hyett, Yifeng Tian, Michael Chertkov, Daniel Livescu, Mikhail Stepanov, "Data-Analysis of the Coarse-Grained Velocity Gradient Tensor." In the proceedings of APS Division of Fluid Dynamics Meeting Abstracts, 2021.
Machine Learning Lagrangian Large Eddy Simulations with Smoothed Particle Hydrodynamics
Published:
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Recommended citation: Yifeng Tian, Michael Chertkov, Michael Woodward, Mikhail Stepanov, Chris Fryer, Criston Hyett, Daniel Livescu, "Machine Learning Lagrangian Large Eddy Simulations with Smoothed Particle Hydrodynamics." In the proceedings of APS Division of Fluid Dynamics Meeting Abstracts, 2021.
Machine Learning Statistical Evolution of the Coarse-Grained Velocity Gradient Tensor
Published:
Use Google Scholar for full citation
Recommended citation: Criston Hyett, Michael Chertkov, Yifeng Tian, Daniel Livescu, Mikhail Stepanov, "Machine Learning Statistical Evolution of the Coarse-Grained Velocity Gradient Tensor." In the proceedings of APS Division of Fluid Dynamics Meeting Abstracts, 2021.
Physics Informed Machine Learning of Smooth Particle Hydrodynamics: Solving Inverse Problems using a mixed mode approach
Published:
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Recommended citation: Michael Woodward, Michael Chertkov, Yifeng Tian, Mikhail Stepanov, Daniel Livescu, Criston Hyett, Chris Fryer, "Physics Informed Machine Learning of Smooth Particle Hydrodynamics: Solving Inverse Problems using a mixed mode approach." In the proceedings of APS Division of Fluid Dynamics Meeting Abstracts, 2021.
Physics Informed Machine Learning of Smooth Particle Hydrodynamics: Validation of the Lagrangian Turbulence Approach
Published:
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Recommended citation: Michael Woodward, Yifeng Tian, Michael Chertkov, Mikhail Stepanov, Daniel Livescu, Criston Hyett, Chris Fryer, "Physics Informed Machine Learning of Smooth Particle Hydrodynamics: Validation of the Lagrangian Turbulence Approach." In the proceedings of APS Division of Fluid Dynamics Meeting Abstracts, 2021.
Applicability of Machine Learning Methodologies to Model the Statistical Evolution of the Coarse-Grained Velocity Gradient Tensor
Published:
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Recommended citation: Criston Hyett, Yifeng Tian, Michael Woodward, Michael Chertkov, Daniel Livescu, Mikhail Stepanov, "Applicability of Machine Learning Methodologies to Model the Statistical Evolution of the Coarse-Grained Velocity Gradient Tensor." Bulletin of the American Physical Society, 2022.
Lagrangian Large Eddy Simulations via Physics-Informed Machine Learning
Published:
Use Google Scholar for full citation
Recommended citation: Michael Chertkov, Yifeng Tian, Mikhail Stepanov, Chris Fryer, Michael Woodward, Criston Hyett, Daniel Livescu, "Lagrangian Large Eddy Simulations via Physics-Informed Machine Learning." Bulletin of the American Physical Society, 2022.
Physics Informed Machine Learning with Smoothed Particle Hydrodynamics: Compressiblity and Shocks
Published:
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Recommended citation: Michael Woodward, Yifeng Tian, Criston Hyett, Chris Fryer, Daniel Livescu, Mikhail Stepanov, Michael Chertkov, "Physics Informed Machine Learning with Smoothed Particle Hydrodynamics: Compressiblity and Shocks." Bulletin of the American Physical Society, 2022.
teaching
Math 112
Teaching Assistant, University of Arizona, 2019
Assisted in development of course materials, leading lectures, and grading.
Math 112
Teaching Assistant, University of Arizona, 2020
Assisted in development of course materials, leading lectures, and grading.