I'm an AI engineer working on applied LLM systems — agentic workflows, retrieval pipelines, and the unglamorous plumbing that makes them reliable enough to trust.
Most of my work comes back to the same problem: taking input that wasn't designed for a machine to read, and turning it into structure something downstream can act on.
A tenant describing a leak over the phone. A scanned insurance card at a clinic's front desk. Sixty-four sensor channels drifting slowly out of spec across thousands of flights. The domains are unrelated; the shape of the problem is nearly identical.
I finished my MS in Data Science at RIT in May 2026, where my capstone was a hybrid anomaly detection pipeline on aviation telemetry.
Before that I did my undergraduate degree in Computer Science at Vellore Institute of Technology, specializing in information security, and co-filed an Indian patent for a cardiac risk prediction model.
Today I'm a Data Scientist at Digestive Disease Care, one of two founding members of the AI and data science function, working on claims and revenue cycle intelligence.
Outside of work I'm usually building something with a partner or two, mentoring students through Rewriting the Code, hiking, or at tech networking events.
I'm always open to talking about agentic systems, healthcare AI, or anything at the intersection.
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A photo of you outside of work — mentoring, a hackathon, an AI Tinkerers meetup.
Experience
Data Scientist · Digestive Disease Care
2026 – Present
- Leading an AI and data science initiative focused on claims and revenue cycle operations, including a denial-prediction model, automated insurance verification at intake, and payer performance analytics — working directly with billing and clinical teams to map current systems and historical claims data.
- Scoping an interoperability layer for standardized payer data exchange, evaluating HL7 FHIR-based integration with the practice's EHR environment to support real-time eligibility checks and cost estimation.
- Designing an OCR-based insurance card intake pipeline paired with DDC's historical billing data to generate pre-visit out-of-pocket cost estimates for patients.
- Applying prior applied AI/LLM experience — agentic systems, RAG pipelines, workflow automation — to healthcare-specific problems, including claims denial patterns, patient billing communication, and operational analytics.
- One of two founding members of DDC's AI/Data Science function, leading the team's roadmap as it scales with additional hires.
AI Intern · Google Developers
May – Jul 2023
Built ML components in Python and Node.js and the API pipelines that served their predictions, working on a computer vision system that identified food from user photos and estimated nutritional content.
Full Stack Developer Intern · Malonus Consulting LLP
May – Jul 2023
Frontend and backend feature work in JavaScript, Bootstrap, and Node.js on client platforms, with Docker-based environment setup across the team.
Graduate Assistant, Civic Engagement · RIT Center for Leadership & Civic Engagement
Nov 2025 – May 2026
Coordinated the Spring 2026 Community Service Fair — 43 external organizations, 300+ student participants — owning logistics, stakeholder communication, and issue resolution.
Peer Advisor Leader · RIT International Student Services
Aug 2025
Led orientation sessions for incoming international students and provided academic and transition guidance.
Education
Rochester Institute of Technology — MS, Data Science
Aug 2024 – May 2026
Machine Learning & Data Science: Statistical Machine Learning, Neural Networks, Applied Data Science I, Applied Data Science II
Systems & Engineering: High Performance Data Science (CUDA, MPI, GPU programming), Database Design & Implementation, Software Engineering
Statistics: Applied Statistics
Vellore Institute of Technology — BS, Computer Science & Engineering (Information Security)
Oct 2020 – May 2024
Certifications
Microsoft Azure AI Fundamentals (AI-900)
Introduction to Cybersecurity Tools & Cyber Attacks (IBM)