At TheScooter.ai, I contributed to a key feature enhancement for a production web application, working across backend and frontend components to support development and deployment. I also participated in code reviews and sprint planning as part of the engineering team.
I built PhishCatcher, a Chrome extension that detects phishing and spoofed login pages in real time using a Random Forest classifier. It achieved 98.5% accuracy and precision on 800 test URLs, with classification running client-side to preserve user privacy.
I also developed an NLP-based fake news detection system that achieved about 93% classification accuracy using TF-IDF and a Scikit-learn classifier. I'm a Computer Science undergraduate with a working interest in cybersecurity and hands-on experience in Python, web development, and machine learning.
