Perumal Nithiarasu

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Swansea University
Country flagUnited Kingdom

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About

Professor Perumal Nithiarasu is a faculty member at Swansea University in the United Kingdom. His research focuses on the application of machine learning and deep learning techniques in areas such as physics-informed neural networks, heat conduction problems, and cardiovascular modeling. Recent articles highlight his work on hyperparameter selection for neural networks, detection of stenoses and aneurysms, and data-driven inverse modeling in computational heat transfer.

Recent Grants

Grant: Close

Engineering complex fluids in biology and medicine

Open Date: 2010-01-01

Close Date: 2011-04-29

Grant: Close

Patient Specific Modelling Network

Open Date: 2009-07-31

Close Date: 2013-01-31

Grant: Close

DIFFERENTIAL DISTANCE FUNCTION COMPUTATIONS FOR MESH GENERATION

Open Date: 2007-08-31

Close Date: 2010-08-30

Grant: Close

Patient Specific Computational Modelling of Human Upper Airway Collapse

Open Date: 2006-09-30

Close Date: 2011-09-29

Positions (1)

Publisher
source

Swansea University

Swansea University

PhD studentship at Swansea University in Mechanical Engineering , focused on fusion energy , digital twins , physics-based modelling , AI , and data-driven validation . The project investigates how experimental data, synthetic datasets, and physics-informed models compare when building reliable digital twins for fusion devices and components. The research will examine fundamental thermomechanical and thermofluid phenomena, uncertainty quantification, and the limits of replacing physics-based models with AI systems. It is especially relevant for students interested in model validation, hybrid modelling strategies, and the reliability of digital twin methods under real operating conditions. Supervisors: Professor P. Nithiarasu, Dr Alberto Coccarelli, and Lloyd Fletcher (UKAEA). Informal enquiries may be directed to Professor Perumal Nithiarasu. Funding: full tuition fees plus an annual UKRI stipend (£20,780 for 2025/26; £21,805 for 2026/27 onwards) and up to £1,000 per year in research expenses. Eligibility: PhD applicants should hold a 2.1 undergraduate degree or equivalent in Engineering or a closely related science discipline. IELTS 6.5 overall with 5.5+ in each component, or an accepted equivalent, is required where applicable. Some applicants may need ATAS clearance. Deadline: 2026-07-06. Applications may be submitted in Welsh. Applicants must apply online using RS973 and upload the required documents, including CV, transcripts, degree certificates, cover letter/personal statement, reference, and supporting evidence as applicable.

3 months ago

Articles (4)

Year:

2024

Year:

2021

Year:

2021

Year:

2020

Collaborators (1)

Sanjay Pant

Associate Professor

Swansea University

UNITED KINGDOM
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