2020
PhD · Mechanical Engineering
IIT Madras
Advances in Stochastic Finite Element Method for Forward Uncertainty Quantification.
EXPERIENCE
A career connecting mechanical design, computational science, production software, and scientific machine learning.
2022 — PRESENT · OAKVILLE, CANADA
Scientific ML and engineering AI for energy and advanced manufacturing.
AI architecture for engineering applications, including diffusion-based generative design of turbine blades in spectral representations.
Neural operator digital twins for grid assets, Neural ODE models for wind-turbine manufacturing quality, and NASGRO-constrained fatigue crack-growth models.
Cross-organisational AI initiatives, scientific ML practices and technical mentorship. Developed data-driven robotic control for casting manufacturing.
Equipment qualification cost reduction
Annual waste reduction
Casting robotic-control outcomes reported in résumé.
Winner, North America — Simplify category.
Runner-up, Europe — Innovation of the Year category.
Scalable REST APIs and Angular ETL applications for financial data processing, with Kubernetes orchestration using OpenShift.
End-to-end machine-learning pipelines on GCP for customer-intent prediction using BERT and ensemble methods.
Stochastic finite element methods, Bayesian inference and neural-network surrogates. Published 10+ research papers and mentored three graduate students. Exchange research at the University of Luxembourg, April–July 2019.
Mechanical design and CATIA modelling for reusable launch-vehicle and GSLV structures, including parametric modelling for casting mockups.
EDUCATION
2020
IIT Madras
Advances in Stochastic Finite Element Method for Forward Uncertainty Quantification.
2011
Delft University of Technology
Space Systems Engineering & Aerostructures. Thesis: Design of a MEMS micro-resistojet.
2008
Cochin University of Science and Technology
Mechanical engineering.
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