Summary
Accomplished Computer Science senior at York University, excelling in software engineering fundamentals and innovative AI development. Proficient in Python, Java, C/C++, and JavaScript, I've engineered production-ready applications using machine learning and NLP to address complex challenges and deliver tangible business outcomes. With hands-on experience in scalable web services, I'm poised to drive high-impact solutions in dynamic tech environments.
Experience
Researcher
Cognora
- •Spearheaded the strategic vision and product development for the StudyBuddy AI chat interface, from initial concept to market launch.
- •Engineered the complete backend architecture for the StudyBuddy AI platform. Led the comprehensive redesign and overhaul of the platform's frontend interface.
- •Architected a versatile agentic framework compatible with all major AI models and providers.
- •Created an internal dashboard to measure and track key user metrics.
- •Analyzed user data and educational outcomes to refine routing models, improving engagement and conversational effectiveness.
- •Evaluated the ethical implications of AI in education.
Education
York University
Bachelor of Science, Computer Science
Toronto, ON
Dalhousie University
Bachelor of Science, Applied Computer Science
Halifax, NS
Projects
StudyBuddy (Full-Stack Educational Platform)
Studdybuddy.ca →- •Led the end-to-end development of a scalable AI-powered learning platform, growing the user base to over 1,000 active users and enhancing engagement through real-time collaboration features.
- •Integrated advanced AI models via a custom Node.js based framework, achieving a 40% improvement in system performance through optimized caching and WebSocket-based interactions.
- •Built with React for the front-end and Cloudflare Workers for the back-end, ensuring sub-100ms response times and seamless handling of high-concurrency loads, demonstrating expertise in AI integration, scalability, and modern tech stacks.
ReactCloudflare WorkersWebSocketsNode.jsPythonLLM APIsRedisPostgreSQLConvexPostHog
Sentiment Analysis of Movie Reviews
github.com/sportynest/setiment-analysis-model →- •Designed and deployed a machine learning pipeline for sentiment analysis on a large movie review dataset, boosting prediction accuracy by 15% using NLP techniques like TF-IDF and LSTM models.
- •Utilized Python, Scikit-learn, and TensorFlow for end-to-end development, including data preprocessing, model training, and evaluation—highlighting proficiency in ML workflows and delivering actionable insights for real-world applications.
- •(GitHub: https://github.com/sportynest/setiment-analysis-model)
PythonScikit-learnTensorFlowLSTMPandasNLP
Moodle Email Scraper
github.com/sportynest/Moodle-Email-Scrapper →- •Engineered a Python-based web scraping tool using BeautifulSoup to extract and manage student emails from Moodle platforms, incorporating parallel processing with ThreadPoolExecutor for a 50% speed increase.
- •Enhanced efficiency with rate limiting and error handling, streamlining communication for educational settings—exemplifying skills in automation, data extraction, and scalable scripting.
- •(GitHub: https://github.com/sportynest/Moodle-Email-Scrapper)
PythonBeautifulSoupThreadPoolExecutorWeb Scraping
Skills
PythonJavaScriptTypeScriptReactTensorFlowMachine LearningNatural Language ProcessingNode.jsProblem SolvingWeb ScrapingData Analysis