I’m a fourth-year Honours Computer Science student at the University of Waterloo, passionate about turning innovative ideas into impactful technology. My interests lie at the intersection of AI and full-stack development, where I strive to build solutions that make a meaningful difference.
Outside of coding, I’m an avid musician who plays piano, violin, drums, guitar, and bass, and I perform with my school’s jazz ensemble. I also enjoy sports like Ultimate Frisbee, which have strengthened my teamwork and strategic thinking.
I bring a strong foundation in programming with Python, JavaScript, Java, C, C++, SQL, R, Bash, and HTML/CSS, which allows me to adapt to a wide range of technical challenges. My experience extends across frameworks and technologies such as TensorFlow, PyTorch, React, Node.js, Express, Django, and MongoDB, where I’ve applied them to build scalable applications and machine learning solutions. I also leverage tools like Git, AWS, Firebase, Jupyter, Jira, Postman, and Figma to support efficient development and collaboration.
This versatile toolkit enables me to design and deploy dynamic applications, train and fine-tune machine learning models, and continuously improve the software development lifecycle.
Most recently, I worked as a Machine Learning Engineer Intern at StackAdapt, where I improved ad performance prediction models, streamlined A/B testing pipelines, and automated infrastructure tasks to cut down on overhead. At Huawei, I focused on computer vision and natural language processing, building models for ID detection and multilingual privacy protection, and deploying them for scalable, cross-platform use.
Previously, as a Lead ML Engineer at WAT.ai, I developed multimodal encoder-decoder models that converted website screenshots into functional HTML/CSS and presented this research at a national AI conference. I also gained full-stack development experience at PointClickCare, where I enhanced enterprise reporting systems and automated testing workflows to support thousands of end users.