Posts by Collection

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Identifying Governing ODEs in Irregular Physical Domain with Diffusion

Published: October 19, 2022

Poster at 64th Annual Meeting of the American Physical Society Division of Plasma Physics. Abstract available here.

Influence of Initial Conditions on Data-Driven Model Identification for Ideal MHD Test Problems

Published: May 22, 2023

Poster at 50th IEEE International Conference on Plasma Science (ICOPS). Abstract available here.

Successes and Challenges Using a Data-Driven Model Selection Algorithm on Plasma Simulations

Published: July 10, 2023

Presentation during diagnostic and computational techniques session at Dense Z-Pinch Conference. Abstract available here.

Successes and Challenges Using a Data-Driven Model Selection Algorithm on Plasma Simulations

Published: August 10, 2023

Presentation in Data Science/Machine Learning session at Z Fundamental Science Program Workshop.

Influence of Initial Conditions on Data-Driven Model Identification for Ideal MHD Test Problems

Published: December 04, 2023

Poster at annual CHaRMNET meeting.

Learning Plasma Fluid Equations via Data-Driven Model Identification

Published: March 06, 2024

Invited presenter for MSU’s AIDMM-NRT scientific machine learning workshop.

Data-Driven Recovery of Hammett-Perkins Closure from Particle Data

Published: August 08, 2024

Presentation in Theory and Data Science/Machine Learning session at Z Fundamental Science Program Workshop.

Influence of Initial Conditions on Data-Driven Model Identification for Ideal MHD Test Problems

Published: August 15, 2024

Poster at 5th International Conference on Data Driven Plasma Science (ICDDPS).

Developing and applying quantifiable metrics for diagnostic and experiment design on Z

Published in Technical Report, 2023

Developing and applying quantifiable metrics for diagnostic and experiment design on Z

Influence of initial conditions on data-driven model identification and information entropy for ideal mhd problems

Published in arxiv (under review at JCP), 2023

Submitted for review at Journal of Computational Physics, available on arxiv here.

Graduate Teaching Assistant

Class, Michigan State University, Computational Mathematics, Science, and Engineering, 2022

Computational Modeling and Data Analysis II

• Explain key concepts of
  • coding in python
  • data structures
  • command line interfaces and version control
• Grading
• Office Hours

Graduate Teaching Assistant

Class, Michigan State University, Computational Mathematics, Science, and Engineering, 2024

Computational Modeling and Data Analysis I

• Explain key concepts of
  • algorithmic thinking
  • data visualization
  • numerical methods
• Grading
• Office Hours