Nicholas Taylor, a recipient of the Centre for Quantum Information and Quantum Control’s (CQIQC) Undergraduate Summer Research Program, was recognized at this year’s Summer Undergraduate Data Science (SUDS) Showcase.

This poster session was held on August 10, 2023, and was organized by the University of Toronto’s Data Science Institute (DSI) as part of their SUDS Opportunities Program. The program equips undergraduate students with data science techniques to conduct research in various fields, such as humanities, life sciences, engineering, and public health.

During this showcase, 37 students presented and shared their research, ranging from genetic covariance analysis in fruit flies to school dropout prediction using machine learning.

Taylor presented his project, which was funded by CQIQC, on Quantum Machine Learning for Regression Tasks in Computational Chemistry. His project focused on tackling the challenge of balancing accuracy and computational cost in chemical property predictions. Impressing many people at the showcase, he was voted as one of the top posters.

“Such information holds significant implications for drug discovery and material science,” says Taylor, reflecting on his project and his experience with the SUDS Opportunities program. “From not knowing the first thing about academic research to building quantum machine learning methods, I’ve learned a lot that I can take with me to future applications.”

Taylor also presented his project at the Faculty of Applied Science and Engineering’s Undergraduate Engineering Research Day (UnERD).