J. (Jigar) Parekh, MSc

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