Vivek Oommen Source Confirmed

Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.

Researcher

John Brown University

faculty

8 h-index 27 pubs 447 cited

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Biography and Research Information

OverviewAI-generated summary

Dr. Vivek Oommen's research encompasses both computational modeling and materials science, with a focus on applying advanced computational techniques to a variety of physical phenomena. His work spans the modeling of fluid dynamics, turbulent flows, solidification and crystal growth, and meteorological events. Oommen leverages model reduction techniques and neural networks to simulate complex systems, as evidenced by publications exploring the use of neural operators and autoencoder architectures to understand two-phase microstructure evolution. Recent work demonstrates an interest in physics-informed machine learning, including research on physics-informed kernels, as well as neural operators for shape optimization and the solution of inverse heat transfer problems. His broader research interests involve characterizing the microstructure properties of aluminum alloys.

Metrics

  • h-index: 8
  • Publications: 27
  • Citations: 447

Selected Publications

  • Code and Data for "Learning Turbulent Flows with Generative Models for Super Resolution and Sparse Flow Reconstruction" (2025) DOI
  • Code and Data for "Learning Turbulent Flows with Generative Models for Super Resolution and Sparse Flow Reconstruction" (2025) DOI
  • Learning two-phase microstructure evolution using neural operators and autoencoder architectures (2022) DOI

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