Below are just a few of the AI related projects at the University. If you would like to see your work listed here, please contact us.
Gen AI Use Case: Using Generative AI for text and language generation

Text generation is being used to generate speech-to-text from audio and video files that occurred in the past. In fact, this project will be looking back 10+ years. This work being performed with this effort is possible due to available generative AI tools. The language generation comes into play when summarizing previous audio/video meetings to find action items and a summarization of what took place during those meeting.
Status: In Progress
Technology: AWS Amazon Bedrock using the Titan foundation model.
Another aspect of the project is to generate text and meeting summaries for meetings going forward. To address this need, Microsoft Teams premium licenses are being purchased. This is a nice solution in that many departments across the University use MS Teams for meetings and the premium license costs are affordable at $2 per person per month.
Technology: Microsoft Teams – premium licenses, using Intelligent Meeting Recap
Gen AI Use Case: Using Generative AI and Emerging Technologies to improve Health Care

The Emerging Technologies Team in ITS Campus Solutions collaboration with Professor Kowalski-Muegge from DMS’s Oncology Department has been a remarkable journey in AI and precision oncology. We’ve supported the launch of DMS’s first digital health applications in oncology, synergizing with AWS to streamline her groundbreaking research workflows. Prof. Kowalski-Muegge recently earned a $23K AWS grant, reflecting her leadership in AI-enhanced clinical treatment decision support. Her joint efforts with the ITS Campus Solutions Emerging Technologies team initiated myCMIE (my Cancer Molecular Information Exchange), a digital tool for informed clinical decisions. Venturing further, she’s innovating cancer detection with novel DNA motif biomarkers. She is leveraging AWS technology to craft a comprehensive health omics data lake, driven by clinical grade sequencing data, and integrated with existing medical records and public data. This initiative, ourCMIE (our Cancer Molecular Information Exchange) includes her partnership with Mays Cancer Center and sequencing companies and is the next key part of a broader grant proposal. Her profound impact in AI and oncology has not only placed her on the AI in Precision Oncology editorial board but also spotlighted her as a speaker at the upcoming Texas Society for Oncology, influencing state-level cancer care policies. Her lab’s website stands as a testament to these cutting-edge applications and their potential in revolutionizing cancer care. We eagerly anticipate continuing our journey with Dr. Kowalski-Muegge, supporting her visionary projects in transforming cancer care.
Status: Pending ISO approval
Technology Planned: AWS Text Extraction, PII Removal, Key Data Extraction, REDCap, AWS HealthLake
Gen AI Use Case: Using language generation to glean data from course Syllabi

The use case is to use Generative AI to review course syllabi with the expected outcome of generating key deliverables for each syllabus such as summaries and other criteria. This project is expected to save University of Texas professors hundreds of hours of person hours by leveraging Generative AI tools to perform syllabi reviews and to glean out needed data points. The time required for professors will be reduced to reviewing results.
Status: Planning, work just getting started