I'm a software engineer at the University of Rochester studying Computer Science and Business Information Systems.
I enjoy building software that solves real business and operational problems. Most of my recent work has been around AI, backend engineering, distributed systems, and Institutional Knowledge Intelligence.
At Franklin Templeton, I worked on financial process automation and built a platform for capturing and retrieving institutional knowledge. I've also contributed to open source AI infrastructure through MemVerge and currently lead the engineering work behind Foundly, where we're building technology for lost property recovery across aviation.
June 2026 – August 2026
Worked within Fiduciary Trust International on AI, data, automation, and process improvement.
- Automated an alternative investment reconciliation process with Python and LLMs, reducing processing time from about 6 days to 3 minutes
- Built an Institutional Knowledge Intelligence platform to preserve knowledge from employees, meetings, past decisions, business rules, exceptions, and client relationships
- Used GraphRAG, knowledge graphs, embeddings, and retrieval pipelines to make that knowledge searchable
- Worked with subject matter experts to understand existing processes and turn them into structured automation logic
- Helped other interns with AI integrations, data processing, and debugging
October 2025 – May 2026
Contributed to MemMachine, an open source memory system for AI applications.
- Worked on cache synchronization and persistence across distributed components
- Improved token retrieval and sequence reconstruction
- Contributed to memory infrastructure for long context AI applications
- Worked primarily with Python, Docker, and distributed systems
January 2025 – Present
Building software for lost property recovery across airports and airlines.
- Built reporting, matching, case management, communication, and tracking features
- Developed REST APIs, authentication, access controls, and database architecture
- Built matching logic using structured data, location information, and AI
- Designed dashboards for staff managing lost property cases
- Built multi tenant architecture for organizations, users, cases, and operational data
December 2024 – May 2025
- Developed forecasting microservices and analytics dashboards
- Integrated APIs and AWS services for application deployment and data processing
- Built internal analytics tools used for business intelligence and operational reporting
November 2021 – December 2025
- Built applications across healthcare, education, and business operations
- Developed backend services, APIs, databases, and deployment pipelines
- Built and maintained full stack applications used in production
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A full stack vehicle marketplace for buying, selling, and discovering vehicles.
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A customer analytics platform for understanding retention, sentiment, and customer behavior.
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Python • Java • JavaScript • TypeScript • SQL
React • Node.js • Flask • Django • FastAPI • REST APIs
LLMs • RAG • GraphRAG • Knowledge Graphs • Institutional Knowledge Intelligence • Embeddings • Retrieval Systems
AWS • Docker • Cloudflare Workers • PostgreSQL • MySQL • Supabase • Firebase • Git • CI/CD
Computer Science & Business Information Systems
Expected May 2027
- Artificial Intelligence
- Operating Systems
- Database Systems
- Data Structures & Algorithms
- Web Programming
- Statistical Methodology
- LeFrak Friedberg Scholar
- Draper Data Science Business Plan Competition Finalist
- Global Hackathon Finalist, Top 6 of 500+ Teams, ITU 2022
- Google Data Analytics Certification
- Carnegie Mellon University CS Academy Python Certification