At the iOS Development Center, SRMIST (Apple × Infosys), I’m building native iOS applications, designing SwiftUI components and connecting them to asynchronous data layers and REST services. I was selected for the iOS Student Developer Program from a pool of 1000+ applicants.
At Tech Mahindra, I built predictive models for equipment failures using industrial sensor data, improving prediction accuracy by 15–20%. I also developed reusable data pipelines that reduced processing time by about 30%.
During my summer research internship at Indian Institute of Technology Roorkee, I developed an ML surrogate model to predict seismic isolation device parameters from elastomer properties and loading descriptors, replacing repeated high-cost simulations.
In my projects, I built Setu, a Hindi voice-enabled RAG system with a FastAPI backend, and an avalanche forecasting pipeline for the Western Himalayas. The forecasting project reached 0.85 recall and 0.89 PR-AUC and was accepted to the WiML Workshop at NeurIPS 2026.
