The Story
15+ years turning supply chains from cost centers into competitive advantages — from automotive to semiconductors, from spreadsheets to simulation and AI.
I started my career designing transmission components at Maruti Suzuki— India's largest automaker. It was there, watching parts move from design through sourcing to production, that I first understood supply chains aren't just logistics problems. They're complex adaptive systems.
That insight led me to Oklahoma State University for a Master's in Industrial Engineering, where I dove deep into optimization, simulation, and operations research. Graph algorithms, facility location problems, vehicle routing — I loved the intersection of math and real-world operations.
From 2017 to 2025, I was at Applied Materials, working in the semiconductor equipment space where a single hour of fab downtime can cost over $100,000. First in logistics network optimization — where I automated global reverse logistics routing, built duty models that saved $5M+ during trade wars, and designed a cartonization algorithm that cut $2.4M in packaging waste.
Most recently, I led spare parts planning projects, building machine learning models for intermittent demand forecasting and discrete-event simulations for end-to-end supply chain scenario planning. The goal: make supply chain decisions with data and simulation, not gut feel and spreadsheets.
What excites me most right now is agentic AI— autonomous AI systems that don't just predict, but act. I'm exploring how AI agents can handle routing decisions, trigger replenishment, and manage workflows with human-in-the-loop guardrails. I believe this will fundamentally change how supply chains operate.