AI/ML Engineer & Computer Science Graduate building intelligent systems that solve real-world problems.
I'm a Computer Science graduate specializing in Artificial Intelligence and Machine Learning. I work with modern AI frameworks, neural networks, and large language models, with hands-on experience in fine-tuning and evaluating LLMs.
As a Legal Intern at NYC Emergency Management, I develop full-stack applications and intelligent document processing systems using AI/ML technologies. I've built projects ranging from fine-tuned LLaMA models for specialized knowledge bases to neural networks for financial forecasting.
I'm passionate about leveraging AI to solve real-world problems and help organizations harness the power of artificial intelligence.
Developed a full-stack web application for a Disaster Law Symposium, enabling 1000+ participants to register and attend both online and in-person sessions, demonstrating scalable system design and user experience optimization
Built an intelligent Document Processing Suite that automated the sorting and renaming of 16,000+ procurement contracts and supporting documents using Python, implementing machine learning-based document classification, OCR technology for scanned documents, and intelligent vendor name standardization
Engineered automated workflow solutions that reduced manual contract processing time by implementing smart document classification (MSA, SOW, NDA, Purchase Orders) and metadata extraction for large-scale document management systems
Led engaging campus tours for 100+ prospective students and their families, effectively showcasing university programs and campus life while providing exceptional support throughout the admissions process
Assist in coordinating and executing 15+ Honors College events annually, programs, and activities, ensuring an engaging community for 200+ students and leveraging data-driven insights to optimize event planning and student engagement strategies
Collaborate with staff to manage communications and outreach efforts across 5+ digital platforms, enhancing visibility and engagement through promotional materials, and automated workflow solutions to streamline administrative processes
Built a production-scale NLP pipeline processing 16,000+ unstructured legal documents.
Implemented automated classification using OCR integration (AWS Textract), text-pattern analysis, and hybrid rule-based/probabilistic classification.
Designed scalable ETL workflows and data validation pipelines that standardized multi-source vendor data.
Designed and deployed automated event registration system serving 1,000+ participants.
Built using Microsoft Power Platform (Power Automate workflows), SharePoint Lists, and custom connectors.
Eliminated manual registration processing with zero downtime during peak periods.
Built reverse-mode automatic differentiation engine from scratch in Jupyter Notebooks.
Implemented dynamic computation graphs, custom gradient functions, and full training loop for neural networks.
Developed character-level language model inspired by Karpathy's makemore.
Designed case management workflows and data architecture using SharePoint Lists and Power Automate.
Implemented structured request intake processes and document routing automation.
Improved departmental operational efficiency by 30%.
Developing a behavioral ML system that predicts user intent from skip patterns and listening context.
Moving beyond collaborative filtering to model psychological engagement (discovery vs. comfort modes).
Engineered 4 custom recommendation algorithms: momentum-based transitions, rage-skip detection with immediate fallback, novelty injection for zero-play tracks, and user-controlled exploration parameters.
Built ETL pipeline processing 100K+ songs with engineered audio features (valence, energy, tempo).
I'm happy to discuss AI/ML, Cybersecurity, research opportunities, and professional collaborations. Feel free to reach out for with any inquiries or potential opportunities.