Projects

Production systems, ML pipelines, and performance-focused work.

Full-Stack / Backend / Infrastructure

Somerville Museum Inventory System

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Architected and shipped a production inventory management platform for the Somerville Museum.

Next.jsTypeScriptPostgreSQLServerlessVercel
  • ·Led 12 engineers through sprint cycles and code review standards
  • ·Designed architecture and relational schema
  • ·Built backend routes/serverless handlers
  • ·Introduced caching and query bundling for performance
  • ·Modernized hosting/database infrastructure
44%reduction in load times
95%reduction in annual operating costs
60%reduction in staff onboarding time

Full-Stack / Backend

Commonwealth Kitchen Job Board

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Built a production full-stack job board with role-based experiences for member vs business users.

Next.jsTypeScriptClerk AuthPostgres (Neon)Vercel
  • ·Full-stack application architecture and implementation
  • ·Clerk auth integration and role-based flows
  • ·Postgres schema design and deployment pipeline
80%increase in member engagement
50%decrease in admin overhead

Full-Stack Product Engineering

JumboMap

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Interactive event/tabling mapping platform for campus operations.

ReactTypeScriptTailwindMySQLNext.js API
  • ·Built map interaction + user workflows
  • ·Implemented REST APIs for auth, verification, and DB access
~150concurrent users at Tufts Community Day
Adoptedby Tufts OCL

ML + Data + Full-Stack

Reddit Politics Sentiment Dashboard

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Built a dashboard that scrapes political forums and classifies sentiment + political leaning.

MongoDBGPT-4 APIPythonJavaScript
  • ·Multi-source data scraping pipeline
  • ·MongoDB schema + data flow design
  • ·GPT-4 integration + custom classification model
  • ·Frontend dashboard for model outputs
84.3%leaning classification accuracy
92.3%sentiment accuracy

Graph ML / Data Engineering

Twitch Language Detection

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Predicted language communities from graph structure using embeddings + supervised learning.

PythonNode2VecXGBoostNetworkX
  • ·Generated Node2Vec embeddings
  • ·Trained and tuned XGBoost classifier
  • ·Built evaluation and visualization pipeline
90.1%accuracy on 168k-node Twitch SNAP graph
0.88macro F1 across six language families

Performance / Systems

Chess Engine Optimization

Alpha-beta pruning, move ordering, and board representation optimization.

C++
  • ·Implemented alpha-beta pruning + move ordering
  • ·Improved board representation and benchmarking
70%win rate vs initial implementation

Performance / Systems

Image Compressor/Decompressor

Custom binary encoding/decoding pipeline with optimized memory handling.

C
  • ·Built custom binary encoding/decoding pipeline
  • ·Optimized memory handling
Compressed to 33% of original size
~3%quality loss with meaningful compression