Perumal Nithiarasu
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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)
Swansea University
Swansea University
3 months ago
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
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