Euiyoung Kim

Euiyoung Kim

Ph.D. student in Mechanical Engineering at Purdue University. Research interests: SciML, CFD, and fluid dynamics.

Euiyoung Kim

Scientific Machine Learning / Fluid Dynamics

I build data-driven and physics-aware models for fluid-flow problems.

I am Euiyoung Kim, a Ph.D. student in the School of Mechanical Engineering at Purdue University. My research interests sit at the intersection of scientific machine learning, computational fluid dynamics, and reduced-order modeling for complex flow systems.

  • Scientific Machine Learning
  • Computational Fluid Dynamics
  • Physics-Informed Modeling
  • Reduced-Order Models
  • Fluid Dynamics
Publications Talks CV Google Scholar GitHub

Research Focus

SciML for Flows

Learning flow representations that respect physical structure and remain useful beyond a narrow training regime.

CFD and Modeling

Connecting numerical simulation, data-driven modeling, and interpretable analysis for aerodynamic and fluid systems.

Efficient Prediction

Developing compact models that make expensive flow computations easier to explore, compare, and deploy.

Background

  • Ph.D. student, Mechanical Engineering, Purdue University.
  • M.S. in Aerospace Engineering, Korea Aerospace University.

Contact

I am always happy to connect about scientific machine learning, computational fluid dynamics, and research collaboration. The quickest way to reach me is by email through the sidebar.