Computer Science Graduate • Python & Java Developer • Cloud & Data Analytics Focus
View My WorkI spent my early career as a rock musician and record producer, learning to produce albums on shoestring budgets from a home studio, and playing small club and bar shows on the East Coast. Eventually, the seemingly limitless creative possibilities of technology and software development captured my interest and I began to explore the field.
After returning to school and graduating with a Computer Science degree from Columbia University, I've discovered that the same creativity and problem-solving skills that made me successful in music now enable me to explore complex systems and solve real world problems with code. I love building applications that sift through large datasets and uncover hidden insights that would be impossible to see otherwise.
Today, I enjoy exploring cloud technologies and harnessing the power of semantic analysis and big data to reveal patterns in databases.
This Python application scrapes live headlines from CNN.com, processes the text to identify the most common keywords, and applies sentiment analysis using TextBlob. It then generates visualizations of word frequency, polarity, and subjectivity trends, and highlights the most polarizing and subjective headlines. Finally, it also exports structured reports (CSV/Excel) and plots for further analysis. This project was a great opportunity to learn about web scraping, natural language processing, and data visualization with Python, BeautifulSoup, NLTK, Seaborn, and Pandas.
I developed an interactive Python tool to explore over one million 311 service request records from New York City’s open data platform, focusing on NYPD-related complaints between 2015–2024. In this second phase, the project evolved from static analysis into a dynamic data exploration system. Users can now select a borough and year range, prompting the program to automatically retrieve relevant data via the Socrata API, clean and structure it with Pandas, and generate multiple visualizations using Matplotlib and Seaborn. Each run produces a timestamped report folder containing charts and a cleaned CSV dataset. This project deepened my experience with API integration, data engineering, and automated reporting while enhancing flexibility and user interaction in large-scale data analysis.
I am developing a full-stack flashcard web application that combines the proven learning techniques of active recall and spaced repetition with modern social and collaborative features. Built with Flask, SQLAlchemy, and Bootstrap, the app already supports user accounts, deck creation, multimedia flashcards, and deck studying with various modes. Planned features include deck versioning (a Git-like branching system for collaborative study), public/private deck sharing, social ranking based on deck popularity, and rich study visualizations such as heat maps. Beyond building a powerful study tool, this project has been a way for me to deepen my experience with Git workflows, documentation, and long-term, team oriented project planning.
I had to opportunity to play guitar in a number of bands and do what I loved most: write music. Check out this video from one of my old projects, or click the button below to see more.
I worked as an audio engineer, record producer, and song writer for various artists. Check out this music video from one of my old clients, or click the button below to see more.
Playing live shows was always my favorite part of being a musician. During my time playing out, I was fortunate enough to open for bands like Suicide Silence, The Red Jumpsuit Apparatus, Born of Osiris, and more.
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