May 7, 2024
Xiaowei Jia, an assistant professor in SCI’s Department of Computer Science, explored knowledge-guided machine learning at the fourth and final lecture of the Dean’s Spotlight Series 2024 on April 25.
Jia presented his research on knowledge-guided machine learning and its real-world applications, with his research interests lying in artificial intelligence (AI), data mining and data science, and machine learning.
Machine learning (ML) refers to AI that analyzes and identifies patterns in datasets, often used in scientific fields. Where many ML models fail due to under-constrained datasets, knowledge-guided ML models are more customizable, allowing researchers to solve complex scientific problems more effectively, accurately, and reliably.
“Using a knowledge-guided architecture, we can greatly enhance the ability of models to assimilate different types of variables. These are very important, critical properties of scientific modeling,” said Jia.
Jia discussed how knowledge-guided ML is a useful tool in addressing issues like energy conservation and environmental pollution across geographical regions. When ML is guided by complete scientific knowledge, it can transform the way scientists conduct research and create meaningful change in the natural world.
This talk was presented by the Department of Computer Science.
Watch the recording of Jia’s presentation here.
--Alyssa Morales
