I am a Master’s student in Computing Science at the University of Alberta, my research focuses on the application of machine learning techniques to software engineering problems. Currently I am working on a bug detection model to detect bugs at the level of cells in notebook code.

I am entering my fourth year of Computing Science and Applied Mathematics at the University of Alberta. My current research explores how large language models respond to non-buggy code snippets when explicitly prompted to "fix" them. I hope this research contributes to a better understanding of how AI models process code and supports the future development of more reliable automated software repair.

I am entering my second of Computing Science at the University of Alberta. My research explores how self-supervised learning (SSL) techniques—like masked language modeling and contrastive learning—can adapt large language models (LLMs) to quantum computing tasks where labeled data is scarce. The goal is to improve AI’s ability to generate quantum algorithms, explain quantum phenomena, and process technical texts with minimal supervision.

I am a fourth-year student majoring in Computing Science and Applied Mathematics at the University of Alberta. My current research applies computational methods to analyze how Canadian news media represent Missing and Murdered Indigenous Women and Girls (MMIWG). By integrating data science methods with discourse analysis, I hope to identify systemic biases and trends in Canadian news coverage.

I'm a fourth-year Computing Science and Mathematics major with a research focus on large language models (LLMs). I was awarded The Mazankowski Award by the Augustana Research Committee in support of my ongoing work to enhance LLMs’ ability to manage ambiguous coding-related user input. My research aims to improve their capacity to ask meaningful, context-aware clarification questions to better interpret user intent.