Harshinee Goordoyal
Scholar

Harshinee Goordoyal

Google Scholar ID: jdihXmkAAAAJ
PhD Candidate, University of Bath (ART-AI), UK
Computational Fluid DynamicsScientific Machine LearningPhysics-Informed Machine Learning
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Citations & Impact
All-time
Citations
13
 
H-index
2
 
i10-index
0
 
Publications
2
 
Co-authors
0
 
Contact
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Publications
1 items
Physics-constrained DeepONet for Surrogate CFD models: a curved backward-facing step case
2025
Cited
1
Resume
Academic Achievements
  • Doctoral Recognition Award Winner 2022.
Research Experience
  • Project: Using artificial intelligence in CFD simulations of blood flow in artificial hearts and other cardiovascular devices. Focus areas include: 1. Using Fourier inspired methods to learn from oscillating flows with single frequencies to predict physiological pulsatile flows; 2. Refining the Reynolds Stress tensor by learning from Large Eddy Simulations (LES) to improve URANS modeling in transitional turbulent flows; 3. Using data from turbulent eddies gained from LES for creating numerical models for haemolysis implemented in URANS.
Education
  • Mechanical Engineering (MEng), University of Bristol, UK.
Background
  • A mechanical engineer by training, always inclined towards applying engineering knowledge in a medical context. Aims to research ways of improving the design of cardiovascular and medical devices to help elevate the quality and length of life of cardiovascular disease patients.
Miscellany
  • Contact: info@cdt-art-ai.ac.uk, press@cdt-art-ai.ac.uk
  • Address: University of Bath, Claverton Down, Bath, BA2 7AY, UK
  • Social Media: Twitter, LinkedIn