Rajeev Jaiman, University of British Columbia

Research

Computational fluid dynamics Machine learning Fluid-structure interaction Multiphysics simulations Data-driven modeling Finite element methods Intelligent and Green Marine Vessels Marine structures

Latest papers

A Finite-Difference Summation-by-Parts Conditionally Stable Partitioned Algorithm for Conjugate Heat Transfer Problems.
Journal of scientific computing · 2026 · senior author

All 1 publications

Latest funding

Intelligent Marine Vessel Optimization Framework for Reducing Greenhouse Gas Emissions
NSERC · 2024 · Principal investigator
$60,400
Improved stabilization and efficiency of coupling algorithms for fluid-structure interaction
NSERC · 2023 · Principal investigator
$84,670
A Novel Framework for Model Reduction and Data-Driven Modeling of Fluid-Structure System: Application to Flapping Dynamics
NSERC · 2019 · Principal investigator
$234,000

All 4 grants and awards

1 publications.

01

A Finite-Difference Summation-by-Parts Conditionally Stable Partitioned Algorithm for Conjugate Heat Transfer Problems.

Nataj S, Del Rey Fernández DC, Brown D, Jaiman R

Journal of scientific computing2026Senior author

DOI: 10.1007/s10915-026-03462-x PMID: 42756191

Intelligent Marine Vessel Optimization Framework for Reducing Greenhouse Gas Emissions

Principal investigatorNSERC2024Alliance Grants

Principal investigators: Jaiman, Rajeev RK

Keywords: computational fluid dynamics; fuel consumption; greenhouse gas emission; intelligent marine vessels; machine learning; multi-objective optimization; simulation-based design; surrogate modeling

$60,400

Improved stabilization and efficiency of coupling algorithms for fluid-structure interaction

Principal investigatorNSERC2023Alliance Grants

Principal investigators: Jaiman, Rajeev RK

Keywords: computational fluid dynamics; elasticity; fluid-structure interaction; multiphysics simulations; navier-stokes equations; partitioned coupling; projection methods

$84,670

A Novel Framework for Model Reduction and Data-Driven Modeling of Fluid-Structure System: Application to Flapping Dynamics

Principal investigatorNSERC2019Discovery Grants Program - Individual

Principal investigators: Jaiman, Rajeev

Keywords: Data-driven computing; Flapping dynamics; Flow and acoustic control; Flow-induced vibrations; Fluid-structure interaction; Machine learning; Model order reduction; Multiphysics simulations; Separated flows; Vortex and wake flows

$234,000

NSERC/SEASPAN Industrial Research Chairs in intelligent and green marine vessels (IGMVs): Advanced Tools and Techniques for Multiphysics Prediction and Design Optimization

Principal investigatorNSERC2019Industrial Research Chairs

Principal investigators: Jaiman, Rajeev RK

Keywords: computational fluid dynamics; data-driven modeling; finite element methods; intelligent and green marine vessels; machine learning; marine structures; ship design and hydrodynamics; structural design and optimization; transportation systems; underwater noise

$744,950

From CIHR, NSERC and SSHRC funding decisions: CIHR since 2008, NSERC since 1991 and SSHRC since 1998, including their latest published competition results.

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Applying for

Mention their NSERC grant from 2024

Subject: Prospective PhD student: Computational fluid dynamics Dear Professor Jaiman, My name is [your name], and I am a [your current degree or role] at [your institution]. I am applying for a PhD position starting in [term and year]. I read your paper "A Finite-Difference Summation-by-Parts Conditionally Stable Partitioned Algorithm for Conjugate Heat Transfer Problems." (2026), and it connects closely to my own work on [your research topic]. [One or two sentences on what you did and what you learned.] I also saw your NSERC-funded project "Intelligent Marine Vessel Optimization Framework for Reducing Greenhouse Gas Emissions" (2024), and I would be glad to contribute to work in that direction. Are you accepting new PhD students for [term and year]? I have attached my CV and transcripts, and I would be glad to talk at a time that suits you. Thank you for your time. Kind regards, [your name]