New York City Metropolitan Area
I build production AI systems that solve real problems in healthcare, government, and environmental justice,shipping code that serves millions while advancing the state of the art. Currently pursuing my Master's in Public Informatics with AI Specialization at Rutgers University (cross-registered at Princeton), I combine strong engineering fundamentals with cutting-edge AI research to deliver scalable, production-ready systems. SOME OF THE SYSTEMS I'VE BUILT Healthcare AI (MOMCare) Engineered RAG-based chatbot achieving 82% automated accuracy and 4.8/5 human evaluation scores, deployed with multi-layered safety guardrails. Scaled to multi-agent architecture (MOMCare Connect) with real-time crisis detection and automated phone intervention via Retell AI. Built end-to-end: data pipeline → dual embedding system → FAISS indexing → LLM generation → safety validation. Large-Scale Environmental Monitoring Built data pipeline processing 429,813+ sensor observations from distributed network of 35 wearable devices. Developed novel exposure analysis algorithms revealing 3.5x pollution disparities. System integrates multiple sensor types (Atmotube Pro, QuantAQ, AirVisual) with automated quality control and statistical validation. Government AI Infrastructure Engineering production LLM pipelines for NJ state agencies using Azure AI services. Built evaluation frameworks measuring accuracy, bias, and workflow impact across document analysis and case summarization use cases. Enterprise Healthcare Systems (HM Health Solutions) Led team of 5 developers building billing systems for millions of Medicare beneficiaries. Reduced errors by 40% through automated testing and root cause analysis. Optimized ETL pipelines reducing data retrieval time by 60% while improving accuracy. TECH STACK Production AI: Python, PyTorch, TensorFlow, Hugging Face Transformers, LangChain, FAISS, Azure AI LLMs & RAG: Llama 3.2, Mistral, FLAN-T5, DeepSeek-R1, dual embeddings, retrieval optimization NLP Pipeline: BERTopic, UMAP/HDBSCAN, BART-large-MNLI, sentence-transformers Computer Vision: 3D Gaussian Splatting, ResNet, EfficientNet, COLMAP, OpenCV Data Engineering: SQL, Pandas, NumPy, ETL workflows Languages: Python, SQL, R, Java, JavaScript, Bash WHAT I'M LOOKING FOR Applied AI/ML roles where I can build production systems that combine cutting-edge research with real-world impact. Particularly interested in healthcare AI, foundational models, RAG systems, or scaling ML to millions of users.
Led technical development for healthcare billing systems serving millions of Medicare beneficiaries, reducing errors and improving efficiency through data-driven solutions. Led team of 5 application developers, mentoring on complex Java challenges and establishing best practices for code review, testing, and production deployment. Guided technical decisions for application enhancements improving system efficiency. Reduced billing errors by 40% through root cause analysis and Java code solutions for production issues. Developed automated testing frameworks preventing regression while maintaining system reliability for critical healthcare operations affecting millions of beneficiaries. Built ETL workflows using SQL automating data extraction and transformation, reducing data retrieval time by 60% while improving accuracy for billing operations. Optimized queries and pipelines handling millions of records daily. Collaborated with customers, business analysts, and cross-functional teams to translate complex requirements into scalable technical solutions. Served as technical liaison between development team and business stakeholders.