Optimal Transport Enhances Data Privacy in Diffusion-based Foundation Models
Drs. Mi Jung Park (Computer Science) and Young-Heon Kim (Math) have been awarded the DSI Postdoctoral Matching Fund for their project "Optimal Transport Enhances Data Privacy in Diffusion-based Foundation Models".
Summary
Application of untrained machine learning analysis of multivariate sediment provenance data to critical metals exploration
Drs. Joel E. Saylor (EOAS) and Michael Friedlander (Computer Science) have been awarded the DSI Postdoctoral Matching Fund for their project "Application of untrained machine learning analysis of multivariate sediment provenance data to critical metals exploration".
Summary
Prediction and management of the long-term environmental risk of mine waste rock piles via 5G-enabled instrumentation and monitoring
Drs. Wenying Liu (Materials Engineering) and Roger Beckie (Earth, Ocean and Atmospheric Sciences) are the latest recipients of the DSI Postdoctoral Matching Fund for their project "Prediction and management of the long-term environmental risk of mine waste rock piles via 5G-enabled instrumentation and monitoring".
Summary
Leveraging data science to measure educational equity in Canadian post-secondary science
The Data Science Institute is pleased to announce a research team led by Drs. Joss Ives (Physics & Astronomy) and Jackie Stewart (Chemistry) has been awarded the DSI Postdoctoral Matching Fund. The multi-institutional research applies critical research methodologies to identify systemic and structural barriers to achievement, and to identify relationships between the instructor-created classroom climate and students’ learning, sense of belonging and persistence in STEM.