PhD Details

During my time at the Department of Aerospace Engineering, Indian Institute of Technology Madras, I focused on accelerating fluid-structure interaction simulations and surrogate modeling using Physics-Informed Neural Networks (PINNs) and High-Performance Computing.

Committee & Collaborators

• PhD Advisor: Prof. Sunetra Sarkar, IIT Madras
• Collaborator: Dr. Didier Lucor, CNRS - LISN, Paris, France
• External Examiner: Prof. Kai Fukami, Tohoku University
• Doctoral Committee:
  • Prof. Nandan Kumar Sinha, IIT Madras
  • Prof. Shaligram Tiwari, IIT Madras
  • Prof. R. I. Sujith, IIT Madras
• Chair Person: Prof. P. Sriram, IITM AE Dept.

Timeline

• Registration: 09th July, 2019
• Submission: 5th Feb, 2026
• Defence: 16th April, 2026
• Award: 17th July, 2026

Dissertation

Title: Accelerated computing and deep learning enablers for surrogate modeling of unsteady flow past moving bodies.

Interactive Dissemination

To make my research more accessible, I have set up an interactive notebook where you can query, explore, and learn more about the specifics of my thesis.

Explore my thesis via Saral Notebook LM

NotebookLM Podcast - AI reconstructs hidden pressure from moving bodies Listen to an AI-generated discussion breaking down the key concepts from my thesis:

Presentations & Seminars

Decoding the Invisible Flow (Pop Science Presentation)

ReCoVor Series Seminar (Johns Hopkins University)

Detailed technical presentation based on my thesis, given to Prof. Rajat Mittal’s group.