About me
Currently completing my M.S. in Computer Science at Rutgers University (GPA: 3.68), I specialize in production AI engineering, data pipelines, and LLM-based automation. My work spans real-time inference systems, large-scale ETL infrastructure, and enterprise compliance agents.
My capstone project, Core Sentinel, is a Windows AI agent that monitors activity in real time, runs local ONNX-quantized TinyBERT inference, and enforces HIPAA, FERPA, and SEC compliance guardrails — achieving sub-100ms end-to-end latency with zero data exfiltration. At Code-blue AI (UC Berkeley–affiliated), I designed and shipped real-time multimodal detection systems achieving 98.9% model accuracy in production. At Rutgers, I am architecting automated NLP pipelines across a 27-year SEC EDGAR financial archive on HPC infrastructure.
Beyond engineering, I manage analytics for a platform serving 75,000+ active users across 4 countries, led a GitHub Copilot rollout that delivered a 20% efficiency improvement for a corporate client, and grew Paid Social acquisition 3× within 18 months through data-driven optimization.
Stack: Python, SQL, C++, AWS, GCP, Docker, ONNX, LLMs, NLP, LangChain, RAG pipelines, ETL, Power BI, Shell Scripting
Published researcher — IEEE ICRITO 2024 (Best Paper Award). President, Rutgers Graduate Student Organization. AWS Solutions Architect Associate (Expected April 2026). Actively targeting full-time roles in AI Engineering, ML Infrastructure, and Data Engineering — available May 2026.
What I'm Doing
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Production AI & ML
Real-time inference, ONNX-quantized models, LLM and RAG pipelines, LangChain, and shipping multimodal systems to production with measurable accuracy and latency targets.
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Compliance & Guardrails
Enterprise agents and desktop tooling aligned with HIPAA, FERPA, and SEC-style policy: local inference, zero exfiltration, and sub-100ms guardrails where the workload demands it.
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Data Pipelines & Cloud
Large-scale ETL on AWS and GCP, Dockerized services, HPC-oriented batch jobs, and automated NLP over long-horizon archives (e.g., multi-decade regulatory filings).
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Analytics & Impact
GA4 and marketing analytics at scale, executive-facing reporting with Power BI, and measurable lifts in efficiency and acquisition through experiment-driven optimization.
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