New York City Metropolitan Area
I build AI systems that turn messy, complex data into real-world impact. I’m a Machine Learning Engineer, working at the intersection of Generative AI, Machine Learning, Data Engineering, Healthcare AI, and 3D Computer Vision. Currently, I build production AI solutions in healthcare, where I work on systems that transform large-scale clinical and operational data into actionable intelligence. My recent work includes developing an LLM-powered scheduler intelligence platform, building natural-language AI agents for governed healthcare datasets, and architecting forecasting pipelines across 35M+ healthcare transactions. What excites me most is the space between research and production - taking ideas from papers, prototypes, and experiments, then turning them into reliable systems that people can actually use. Before moving deeper into AI, I worked as a software engineer building WebGL-based metaverse experiences, interactive 3D environments, and real-time visualization systems using Three.js and Unity. That experience shaped how I think about engineering: performance matters, user experience matters, and great technology should feel seamless. My graduate research focused on Neural Radiance Fields, studying how camera coverage and training budgets impact reconstruction quality in novel view synthesis. I’ve also worked on projects involving causal inference in healthcare, multilingual NLP, LLM agents, and AI-powered decision support. I enjoy building systems where data, engineering, and intelligence come together — whether that means deploying AI into production, designing scalable data pipelines, researching computer vision models, or creating tools that help people make better decisions. Always open to connecting with people working on AI, healthcare technology, intelligent agents, data platforms, applied ML research, or the future of computer vision.
Worked on creating no code, customisable Metaverse experiences for the web