About Me
I'm a passionate Statistics and Machine Learning student at the University of Waterloo, driven by the power of data to solve real-world problems. My journey in data science combines rigorous statistical foundations with cutting-edge machine learning techniques.
Beyond the classroom, I serve in the Royal Canadian Naval Reserve, where I’ve developed critical skills in first aid, firefighting, flood control, sea survival, and tactical operations. This experience has strengthened my ability to stay calm under pressure, work effectively in diverse teams, and adapt quickly in high-stakes environments.
When I’m not analyzing data or exploring new AI tools, I enjoy hiking in nature, playing soccer, and experimenting in the kitchen. I also follow the latest breakthroughs in AI and contribute to open-source projects, always looking for ways to bridge the gap between theory and real-world impact.
Programming
Python, R, SQL, JavaScript, C, C++, TypeScript, HTML, CSS
Machine Learning
TensorFlow, PyTorch, Scikit-learn, Deep Learning, NLP, SVM, CNN
Data Science
Pandas, NumPy, Power BI, Databricks, Spark, Statistical Analysis
Cloud & Tools
Azure, Git, Docker, Kubernetes, Django, Databricks, Cursor
Featured Projects
Here are some of my recent projects that showcase my skills in data science, machine learning, and full-stack development.
Cross-Platform Malware Detection
Designed a CNN to detect malware by converting binary files into grayscale images and classifying them as benign or malicious. Built a secure dataset of macOS and Windows binaries using isolated VMs. Trained and optimized the model for cross-platform generalization and detection accuracy.
Web Scraper and Sentiment Analysis ML Model
Developed a sentiment analysis model using SVM with a linear kernel, achieving 81% accuracy on a test dataset of 2,748 samples. Optimized data preprocessing with custom stopword removal, TF-IDF feature extraction, and hyperparameter tuning. Integrated the model into a Python app for real-time sentiment analysis of both manual and web-scraped text.
Experience
My journey through various roles in data science, machine learning, and research.
Data Analyst Intern
- Optimized data pipelines in Azure Databricks, improving run-time by 92% through efficient transformation logic and pipeline tuning.
- Developed optimized SQL queries, Python scripts, and DAX expressions to analyze and model data, driving actionable insights.
- Designed and built interactive Power BI dashboards and reports to support data-driven decision-making across the organization.
Naval Combat Information Operator
- Completed Basic Military Qualification, mastering advanced time and stress management techniques through rigorous operational training.
- Enhanced team efficiency and readiness under high-pressure scenarios.
Data Science Intern
- Applying NLP and machine learning techniques to support national defence initiatives.
- Collaborated with cross-functional teams to deliver actionable insights for national security.