A little context
I enjoy taking complex, ambiguous systems and turning them into software people can trust. My work spans AI retrieval, data platforms, computer vision, software engineering, and connected hardware.
Curiosity travels well. The same instinct that pulls me up a mountain keeps me digging into hard technical problems.
Current chapter
New York City
Building AI-enabled products at Stratus after completing an M.Eng. in Applied AI.
Experience
Aug 2026 — Present
Stratus · New York, NY
Building project budgeting, permission-aware knowledge, and voice-driven time-entry products with PostgreSQL, hybrid retrieval, Sentry, Docker, and production infrastructure.
Sep 2025 — Aug 2026
PVEDI · New York, NY
Built an Azure-based RAG pipeline over NYC structural codes, accelerated compliant report production by 73%, and developed CRM and service-discovery products for AEC teams.
Jun 2025 — Sep 2025
Rees Scientific · Trenton, NJ
Created sensor anomaly detection with Azure Stream Analytics and ADTK, automated technical documentation, and unified legacy ERP data in MongoDB.
Jun 2024 — Sep 2024
National Science Foundation · Miami, FL
Integrated real-time detection, tracking, and facial recognition for drone operations, achieving 92% detection accuracy and training reinforcement-learning models in AirSim.
Sep 2023 — May 2024
Stevens Institute of Technology · Hoboken, NJ
Engineered a modular C++/Python offshore telemetry platform with four interchangeable IoT sensors and RF data acquisition over two kilometers.
Toolkit
Languages
AI & data
Product stack
Education
M.Eng. Applied Artificial Intelligence
Data Engineering concentration · 3.92 GPA · 2026
B.E. Software Engineering
Computer Science minor · 3.8 GPA · 2025
Beyond the coursework
Ansary Entrepreneurship Competition finalist, U.S. DOE Marine Energy Collegiate Competition presenter, and recipient of certifications from NVIDIA, Microsoft, LinkedIn, and Autodesk.