Jasmin Jelovica, University of British Columbia

Research

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

Latest papers

Predicting transmission loss in underwater acoustics using convolutional recurrent autoencoder network.
The Journal of the Acoustical Society of America · 2022 · senior author
Taguchi-based experimental investigation into weld cladding of Ni-WC MMC overlays by CMT process.
The International journal, advanced manufacturing technology · 2022 · senior author

All 2 publications

Latest funding

Computational methods for enhancing shipyard production efficiency
NSERC · 2025 · Principal investigator
$445,490
NSERC/SEASPAN Industrial Research Chairs in intelligent and green marine vessels (IGMVs): Advanced Tools and Techniques for Multiphysics Prediction and Design Optimization
NSERC · 2019 · Principal investigator
$664,950
Effective structural analysis and optimization of a cargo ship
NSERC · 2018 · Principal investigator
$25,000

All 6 grants and awards

2 publications.

01

Predicting transmission loss in underwater acoustics using convolutional recurrent autoencoder network.

Mallik W, Jaiman RK, Jelovica J

The Journal of the Acoustical Society of America2022Senior author

DOI: 10.1121/10.0013894 PMID: 36182300

02

Taguchi-based experimental investigation into weld cladding of Ni-WC MMC overlays by CMT process.

Karimi MR, Wang SH, Jelovica J

The International journal, advanced manufacturing technology2022Senior author

DOI: 10.1007/s00170-022-09816-7 PMID: 36147551

Computational methods for enhancing shipyard production efficiency

Principal investigatorNSERC2025Advantage

Principal investigators: Jelovica, Jasmin

Keywords: Transport equipment; Other manufactured products and processes

$445,490

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: Jelovica, Jasmin JJ

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

$664,950

Effective structural analysis and optimization of a cargo ship

Principal investigatorNSERC2018Engage Grants Program

Principal investigators: Jelovica, Jasmin

$25,000

Multi-physics, multi-scale modelling of liquefied natural gas (LNG) in marine shipping and heavy-duty trucking: transport, storage, spill, and atmospheric dispersion

Co-investigatorNSERC2017Collaborative Research and Development Grants

Principal investigators: Brinkerhoff, Joshua

$331,600

Failure of steel sandwich structures in compression: Modelling and testing

Principal investigatorNSERC2017Discovery Grants Program - Individual

Principal investigators: Jelovica, Jasmin

$161,000

Topology optimization of a bicycle storage unit using vectorized problem formulation

Principal investigatorNSERC2017Engage Grants Program

Principal investigators: Jelovica, Jasmin

$23,200

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

Write to this professor

A short, specific email works best. This draft uses one of their recent papers; replace the parts in brackets with your own details before sending.

Applying for

Paper to mentionMention their NSERC grant from 2025

Subject: Prospective PhD student: Computational fluid dynamics Dear Professor Jelovica, 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 "Predicting transmission loss in underwater acoustics using convolutional recurrent autoencoder network." (2022), 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 "Computational methods for enhancing shipyard production efficiency" (2025), 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]