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Mar 17 11:00 am

Communicating High-Dimensional Data through Dimensionality Reduction and Interactive Visualizations at McKelvey 1020

Mar 19 11:00 am

Thinking Outside the Ballot Box at McKelvey 1020

Mar 21 11:00 am

Seamlessly Supporting Multi-Context Data Visualization at Jubel 120

Study led by Chenyang Lu explores the potential of large language models to predict postoperative complications by analyzing preoperative assessments and clinical notes. (Photo: iStock)

Foundation AI model predicts postoperative risks from clinical notes

AI for Health Institute team unveils a versatile large language model to enhance perioperative care.

03.03.2025

The TaxaBind framework creates a unified database by distilling information from five different modalities into one binding modality. In TaxaBind’s case, the binding modality is ground-level images of species (center) with (clockwise from top) global environmental features, satellite imagery, audio, text-based taxonomy and geographic location data feeding into the model’s capabilities for ecological applications. (Credit: Srikumar Sastry)

Multimodal AI tool supports ecological applications

Computer scientists led by Nathan Jacobs developed TaxaBind, an artificial intelligence tool that combines six information streams to address ecological problems.

03.03.2025

TRACE-cs tool can help students reliably optimize course scheduling and explain why it makes the recommendations it does. (Image: iStock)

AI tool helps make trustworthy, explainable scheduling decisions

William Yeoh and Stylianos Vasileiou developed TRACE-cs, a hybrid system that combines symbolic reasoning with large language models to solve course scheduling problems.

02.28.2025