About Me

My journey into tech started with a healthy curiosity for “how the internet works” and snowballed into a career that blends infrastructure, intelligence, and interface.

From optimizing Kafka pipelines that process over a billion events a day to embedding LLMs into financial systems, I've worked across backend, frontend, and ML to make software smarter, faster, and occasionally even fun to use.

These days, I work at Intuit on QuickBooks' Fintech AI team, where I help build ML-powered user experiences and reconciliation pipelines. Before that, I was at Amazon working on search ranking and debugging infrastructure. And before that? I was reverse-engineering influence networks and building social signal pipelines for political discourse modeling.

A huge part of my growth happened at the University of Illinois Urbana-Champaign, where I had the chance to explore machine learning research under the guidance of amazing professors. I'm especially grateful for the mentorship of Professor Tarek Abdelzaher and his research group, where I was encouraged to build things, break things, and push boundaries — from building belief embedding models to designing real-time social data pipelines.

I like writing code that doesn't break (too often), building things that make users go “whoa,” and occasionally pretending I understand how Kubernetes actually works.