LabCompass

Jie Shen

Engineering · Purdue University West Lafayette

Established · publishing since 1987

Publications

361

Citations

26,071

Est. group size

~2

Recurring co-author estimate

Active years

39

Publishing since 1987

Research summary
AI-generated

Jie Shen works on numerical analysis and the design of computer algorithms for solving complex equations that describe fluid flow, phase changes, and other physical processes (such as the Navier-Stokes, Cahn-Hilliard, and Landau-Lifshitz equations). A recurring focus is developing 'energy-stable' or 'structure-preserving' numerical schemes, which are computational methods designed to remain accurate and stable while respecting key physical properties of the underlying equations. This work is mathematical/computational in nature and has applications in modeling fluids, materials science, and other physics-based systems.

Numerical methods for partial differential equationsEnergy-stable and structure-preserving computational schemesFluid dynamics (Navier-Stokes equations)Phase-field and gradient flow modelingError analysis and stability theory for numerical algorithms

Publication output has remained fairly steady to slightly growing over the last decade, fluctuating between roughly 10 and 27 papers per year with no clear long-term decline.

Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026

Publication cadence
Publications per year over the last 10 years — averaging 13.8/year recently
2017: 16 publications172018: 10 publications182019: 18 publications192020: 27 publications27202021: 19 publications212022: 16 publications222023: 14 publications232024: 19 publications242025: 20 publications2526
Recent publications
Publishes in
  • arXiv (Cornell University)×31
  • Journal of Computational Physics×22
  • Journal of Scientific Computing×17
  • SIAM Journal on Scientific Computing×15
  • SIAM Journal on Numerical Analysis×11
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This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.

Last updated Jul 20, 2026.

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