J. (Jigar) Parekh, MSc
![Profile picture of J. (Jigar) Parekh, MSc](/staff/j.parekh/photo.png?unique=1638627114107.jpg)
I am currently working on Uncertainty Quantification (UQ) in Computational Fluid Dynamics (CFD) using data-independent methods like Intrusive Polynomial Chaos and data-driven models like 3D U-Net deep learning architecture. These models will be used in the UQ analysis for CFD simulation of wakes behind wind turbines.
Previously, I pursued a masters in Simulation Sciences from RWTH, Aachen.
Interests
• Computational Fluid Dynamics
• Uncertainty Quantification
• Polynomial Chaos, Deep Learning
• Reduced-Order Modeling
• AI in Healthcare and Sports
Key skills
• Languages: Python, C++
• Software: OpenFOAM
• ML Libraries: Scikit-learn, TensorFlow
• Developer Tools: Spyder, VS Code, GitHub
• Technologies: Linux, Anaconda
Leisure time
• Canoeing, Biking, Squash
Last modified: | 18 June 2024 07.55 a.m. |