AI Technical Team

The AI Technical Team is one of the main development units responsible for engineering applied AI solutions across campus. Our primary purpose is to transform teaching, learning and operational efficiency by building custom applications, intelligent agents and conversational assistants. We partner directly with faculty, students and staff to leverage AI for specific, high-impact use cases that enhance the academic experience and streamline campus operations.

Enhancing Teaching and Learning

Our goal is to integrate AI tools that directly support faculty instruction and student success.

We have developed NotebookLM Teaching Assistants that use course materials to help students study and review, and a Grading Assistant that uses transcripts and rubrics to make skill assessment grading more efficient and consistent for faculty. We are building a Scheduling Assistant to help students plan study blocks based on their assignments and calendar, and we are developing practical NotebookLM examples and documentation to inspire broader academic adoption of AI tools.

Streamlining Campus Operations

We have implemented several AI-driven solutions to improve administrative processes and enhance support across campus, including:

Built an IRB application assistant that provides structured feedback on submitted research proposals.
Deployed the AI Website Assistant and initiated development of a General Support Chatbot powered by the Appalachian Technology Knowledge Base to answer common IT questions.
Applied AI/ML in Campus Dining to support labor optimization and improve operational efficiency.

Planned projects include an Admissions Assistant to help prospective students navigate the application process, and several HR use cases leveraging Copilot Studio agents to assist recruiting teams.

Foundational Services and Secure Development

We provide the secure infrastructure and tools necessary for the entire campus to experiment with and deploy AI safely.

We are building out secure, flexible platforms, including custom Gemini examples and documentation for the community and a Confluence-Copilot Connector to leverage existing knowledge sources. We are also building out an on-premise model hosting solution.