Mobile application that simplifies financial analytics by transforming market data into accessible insights using AI and machine learning techniques. Features include stock trend analysis, visual data representations, and an AI assistant that explains market concepts in plain language—a practical project developed to explore the intersection of finance and artificial intelligence.
Skills Used: Flutter, Dart, Machine Learning, LLM Integration, Financial Analysis, Mobile Development
Inspired by Michael Lewis's Moneyball, this project analyzes MLB team spending efficiency through statistical modeling and data analysis.
Skills Used: SQL Lite, Data Science, Python, Statistical Analysis
Machine learning model that predicts MLB game winners using team and player statistics with a focus on feature engineering and predictive modeling techniques.
Skills Used: Machine Learning, Feature Engineering, Python, Data Science, Predictive Modeling
Scraped and combined data from NASA and SpaceWeatherLive.com to record and analyze significant solar flare occurrences.
Skills Used: Web Scraping, Data Cleaning, Python, Data Science, Plotting
Analyzed company sentiment trends on Twitter and compared these trends to corresponding stock price movements using machine learning.
Skills Used: Machine Learning, Text Analysis, Natural Language Processing, Financial Analysis, Python
2019 - Internship Experience
Developed a data visualization component for the Canterbury Roll, an ancient historical text, at the University of Canterbury's Arts Lab.
Note: I worked on a phase of this project that has not been published yet.
Developed a systematic approach to coastal protection by identifying optimal tree planting locations using geospatial analysis and graph theory.
Skills Used: Geospatial Data, Matplotlib, Shapefiles, Mapping, Graph Theory
An analysis of how Jeff Bezos and Elon Musk are inspiring a new generation of space exploration visionaries.
An examination of economic growth metrics and their limitations, written during the COVID-19 pandemic.