I'm a structural engineer with a deep interest in computational mechanics and machine learning. My research centers on Physics-Informed Neural Networks (PINNs) — embedding the laws of structural mechanics directly into neural networks to detect damage and optimize designs without relying on large training datasets.
I completed my B.Tech at NIT Patna and my M.Tech in Structural Engineering at IIT Indore, and I'm now beginning a Ph.D. at IIT Delhi. Along the way I've contributed to the Delhi Metro Phase IV design, taught graduate and undergraduate mechanics courses, and authored research on differentiable truss optimization.
My toolkit spans classical structural analysis — Staad.Pro, ETABS, ANSYS — and modern ML frameworks like PyTorch, JAX, and Flax. I'm drawn to problems where rigorous physics and data-driven methods reinforce each other.
Advanced Solid Mechanics (Masters) & Design of Steel Structures (Bachelors). Guided students through numerical problems, prepared assignments, and ran doubt-clearing sessions.
Part of the team designing and analysing Delhi Metro Phase IV. Gained exposure to viaducts, bridge superstructures, and substructures.
Flexible pavement design — traffic loading, material selection, and layer thickness design using IITPave; prepared the Job Mix Formula.