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Research Interests

• Application of generative AI to engineering and education
• Model-order reduction of turbulent flows
• Numerical heat-transfer
• High-performance computing

Education

• University of Illinois at Urbana-Champaign
  PhD, Theoretical and Applied Mechanics, 2022
  • Advisor: Paul Fischer
  • Dissertation: “An augmented basis method for reduced order models of turbulent flow” (available upon request)
• University of Illinois at Urbana-Champaign
  MSc, Theoretical and Applied Mechanics, 2019
• University of Illinois at Urbana-Champaign
  BSc, Engineering Mechanics (Electrical Engineering Minor), 2016

Academic Work

[1] K Kaneko, C Le Bris, and A T Patera, “Error estimators for the small-Biot lumped approximation for the conduction dunking problem,” preprint, 2024. arXiv: 2406.12047 [math.NA]

[2] K Kaneko and P Fischer, “Augmented reduced order models for turbulence,” Frontiers in Physics, vol. 10, p. 905392, Sep. 2022. doi: 10.3389/fphy.2022.905392

[3] K Kaneko, P-H Tsai, and P Fischer, “Towards model order reduction for fluid-thermal analysis,” Nuclear Engineering and Design, vol. 370, pp. 110866, Dec. 2020. doi: 10.1016/j.nucengdes.2020.110866

[4] K Kaneko, P-H Tsai, and P Fischer, “Model-order reduction of buoyancy- driven heat-transfer,” Transactions of the American Nuclear Society, 1, vol. 121, pp. 844 – 847, Nov. 2019. doi: 10.13182/T31297

[5] P-H Tsai, K Kaneko, and P Fischer, “Reduced order model with constrained optimization for Navier-Stokes equations,” Transactions of the American Nuclear Society, 1, vol. 121, pp. 840 – 843, Nov. 2019. doi: 10.13182/T31285

BibTeX Citation for [1] – [5] and dissertation.