Data Science student at Northeastern University. I build things that make data make sense and tools that make life easier.
Building Codescape at Forge Product Lab - a VS Code extension that turns your codebase into a city. Classes become buildings, functions add floors, and your project grows into something you can actually see and share. Making invisible progress visible for developers learning to code.
Engineering tools at Generate Product Development Studio - improving application portals and analytics dashboards for 200+ candidates and 30+ recruiters. Building the infrastructure that connects students with opportunities.
Researching soccer analytics at the Network Science Institute - using directed network analysis to understand what makes goal-scoring attacks work. Tracking how the ball moves through 1,500+ possession sequences to find patterns in successful plays.
Teaching DS 3000 - helping 100+ students figure out machine learning and linear algebra through office hours and labs. Explaining NumPy tensor operations in ways that actually make sense.
Codescape - VS Code Extension (In Progress) Developer tool that visualizes codebases as growing 3D cities. Uses Tree-sitter for parsing, renders live in VS Code, exports to JSON for sharing on GitHub. Solving the problem of abandoned side projects by making your progress feel real.
CoopScout - Job Search Automation Scraped 1000+ co-op postings using Python and Selenium, built a Flask API with PostgreSQL backend, added TF-IDF-based recommendations. Created to level the playing field for students navigating the co-op search.
sportsnetsci - Soccer Network Analysis Framework for analyzing possession chains using graph theory and spatial geometry. Applies Delaunay triangulation and centrality metrics to 1,500+ sequences from StatsBomb data to identify tactical patterns in attacking play.
great-textpectations - Constitutional Text Analysis
NLP framework that analyzes 17 constitutional documents from 1787-1997 using TF-IDF, LDA topic modeling, and UMAP. Generates Sankey diagrams, topic distributions, and similarity scatterplots to reveal linguistic patterns and thematic evolution across political systems.
Superfoods or Super Marketing? - ML Nutritional Analysis Collected 2000+ food profiles from USDA API, trained perceptron and SGDClassifier models hitting 96.8% accuracy. Used confusion matrices to separate actual nutrition from marketing hype.
spotify-insight - Music Analysis
Feature engineering on song titles and audio data to predict popularity through exploratory analysis of audio features like danceability, energy, and valence. Built models using Linear Regression, KNN, and Random Forest to understand what makes songs resonate.
mastodon-moderation - Community Detection Network analysis of moderator behavior using Louvain community detection and cosine similarity. Visualized patterns in how communities self-organize.
geography-of-disaster - Interactive Visualization
Web app with spatial analysis and interactive visualizations exploring disaster patterns across regions.
Languages & Frameworks: Python, SQL, HTML, CSS, JavaScript/TypeScript, Flask
Data Science: Pandas, NumPy, Scikit-Learn, Matplotlib, Seaborn, Plotly, NetworkX, SciPy
Development: Flask, Beautiful Soup, Selenium, REST APIs, VS Code Extensions, Tree-sitter, Three.js
Tools: Git/GitHub, PostgreSQL, Supabase, Google ADK, Tableau, Jupyter Notebook
Methods: Machine Learning, Network Analysis, Graph Theory, Feature Engineering, Web Scraping
Northeastern University, Khoury College of Computer Sciences
B.S. in Data Science, GPA: 3.70 | Class of 2028
Coursework: Machine Learning, Algorithms and Data, Advanced Programming with Data, Probability and Statistics