Ali Bagheri
a6bagher [at] uwaterloo.ca
I am a Master's student in Computer Science at the University of Guelph, specializing in Computer Graphics and Human-Computer Interaction.
I earned my Bachelor of Computer Science from the University of Waterloo and gained 4 years of industry experience in embedded systems programming and full-stack development.
Experience
I spearheaded the development of a custom radiology software solution for a healthcare clinic in Ontario, and later at Ford Motor Company, I engineered internal tools and optimized their Chromium-based web engine.
I've also gained experience through a variety of software engineering internships.
Check out my CV
Side Projects
Pro-Cam Makeup Simulation
Engineered a projector-camera (Pro-Cam) system that utilizes real-time facial feature tracking to dynamically map and project virtual makeup onto physical surfaces. This project involved integrating computer vision alignment algorithms with projection mapping technology, targeting applications in virtual cosmetic try-ons and interactive digital art. Technologies: Python, Projector, Camera
Distributed File System
Architected and implemented a distributed file system from scratch utilizing FUSE (Filesystem in Userspace). Enabled seamless, low-latency local access and real-time synchronization for multiple clients editing shared remote files. Technologies: C++, FUSE, Network Programming.
Non-Emergency Reporting & Email Automation System
Developed an end-to-end web application designed to streamline public non-emergency report submissions and automate structured email responses. Built a highly performant, type-safe backend integrated with a relational database, fully containerized for scalable deployment. Technologies: Rust, PostgreSQL, React, Docker.
Osteoporosis Predictive Analysis
Leveraged predictive modeling to analyze clinical health data. Engineered the data pipeline by cleaning and structuring complex datasets into optimized dataframes, performed granular exploratory data analysis, and trained evaluated Machine Learning models (kNN and Random Forest) to predict risk factors. Technologies: Python, Scikit-Learn, Pandas, Machine Learning.
HeroTyper
Designed and built an interactive typing game using native mobile or desktop architecture. Focused heavily on software engineering best practices, applying rigid architecture patterns and design principles to ensure a decoupled, easily extensible, and maintainable codebase. Technologies: Kotlin, Software Design Patterns.
Blog
Coming soon!