Ten Projects Selected for GAIRE Program
The Generative AI Research for Education (GAIRE) Program is a collaboration between Texas A&M’s Institute of Data Science (TAMIDS) and Center for Teaching Excellence, and is supported through OpenAI’s NextGenAI Consortium. GAIRE operates under the Generative AI Literacy Initiative at TAMIDS and aims to create AI literacy materials, integrate generative AI (GenAI) tools into course design and classroom activities, and understand GenAI’s impact on learning. This program provides OpenAI API credits and additional support to projects that align with GAIRE’s mission to cultivate responsible usage of generative AI and a robust understanding of it throughout Texas A&M.
In the 2025 cycle, ten projects were selected that will transform the way knowledge of generative AI is acquired and applied at all levels. Congratulations to these project teams!
AI Literacy Platform for the Built Environment: Integrating Multi-Modal GenAI Across Architecture, Landscape, Urban Planning, and Construction Science Education
Project Lead: Benjamin Ennemoser, Associate Professor, Department of Architecture
Developing a comprehensive AI Literacy class for the College of Architecture to provide students who use GenAI with structured guidance across architecture, engineering, and construction.
AI-Enabled Laboratory Tutor: A Generative AI System for Teaching Experimental Design, Data Interpretation, and Troubleshooting in Biomanufacturing and Food Science
Project Lead: Reza Ovissipour, Assistant Professor, Department of Food Science and Technology & AgriLife Research
Team Members: Setareh Shiroodi, Suresh Pillai, Wasitha Thilakarathna – Department of Food Science and Technology & AgriLife Research
Developing an AI-Enabled Laboratory Tutor designed to improve student literacy in generative AI while enhancing learning in biomanufacturing and food science laboratory courses
BranchMind – A Multi-Threaded AI Tutor with Cognitive Branching and Flow-Protected Conversations
Project Lead: Eman Hammad, Assistant Professor, Department of Engineering Technology and Industrial Distribution
Team Members: Jaewon Kim (Texas A&M Global Cyber Research Institute), Omar Al-Refai (Department of Electrical and Computer Engineering), Noemi Mendoza Diaz (Department of Engineering Technology and Industrial Distribution)
BranchMind is a multi-threaded AI tutoring system that preserves instructional continuity while supporting rich, learner-driven dialogue, thereby advancing students’ generative AI literacy.
Building Domain-Specific Retrieval-Augmented Generation (RAG) Systems for Research: A Hands-On Tutorial to Advance Generative AI Literacy at Texas A&M
Project Lead: Jian Tao, College of Performance Visualization & Fine Arts
Team Members: Luis Tedeschi (Department of Animal Science), Yassin Hassan (College of Engineering), Karun Kaniyamattam (Department of Animal Science), Raymundo Arroyave (Department of Materials Science and Engineering)
Developing and piloting a hands-on tutorial that teaches researchers and advanced students how to design, implement, and critically evaluate domain-specific retrieval-augmented generation (RAG) systems for research tasks such as literature exploration, code/documentation support, and methodological synthesis.
Generative AI Integration in Veterinary Education: AI Data Entry, AI Tutor, and AI Literacy Outcomes
Project Lead: Candice Chu, Assistant Professor, Department of Pathobiology
Team Members: Armanto Sutedjo, Educational Consultant, Center for Teaching Excellence
Transforming veterinary medicine through responsible and effective generative AI usage among students enrolled in the College of Veterinary Medicine & Biomedical Sciences’s first AI literacy course.
Generative AI Learning Assistance for Improving Students’ Construction Plan Reading Skills
Project Lead: Namgyun Kim, Assistant Professor, Department of Construction Science
Team Members: Yalong Pi, Associate Research Scientist, Texas A&M Institute of Data Science
Developing a web-based, GenAI-assisted learning platform that extracts visual and textual information from construction plans and generates accurate, pedagogically aligned explanations.
GIScholarBench: A Systematic Evaluation of Generative AI for Literature Retrieval and Knowledge Discovery in GIScience and Beyond
Project Lead: Lei Zou, Associate Professor, Department of Geography
GIScholarBench proposes the first systematic, domain-informed evaluation of Generative AI tools for literature retrieval and knowledge discovery in GIScience, using a workflow designed to be transferable to other scientific domains.
Preparing Next-Generation Urban Planners: A Living Pedagogical Experiment of Building GenAI Literacy and Applied Skills in Urban Planning Methods Courses
Project Lead: Xinyu Fu, Assistant Professor, Department of Landscape Architecture and Urban Planning
Team Members: Thomas Sanchez, Galen Newmann – Department of Landscape Architecture and Urban Planning
Developing foundational GenAI resources and exploring their integration into core urban planning methodology courses taught by Dr. Xinyu Fu
Protocol-Driven Human-LLM Co-Design for Analog IC Education with Explain-Your-Design GenAI Literacy
Project Lead: Aydin Karsilayan, Associate Professor, Department of Electrical & Computer Engineering
Team Members: Antonio Bujana, PhD Student, Department of Electrical & Computer Engineering
Introducing a protocol-driven human–LLM co-design workflow within an analog integrated circuit design module using Cadence Virtuoso/Spectre, a professional environment for designing and simulating semiconductor circuits.
ThreatLens@TAMU: Advancing Generative AI Literacy through an Augmented Reality + GenAI Cybersecurity Learning Environment
Project Lead: Donggil Song, Associate Professor, Department of Engineering Technology & Industrial Distribution
ThreatLens@TAMU is an augmented reality and GenAI platform designed to simulate real-world cyberattacks, integrating ethical and technical AI analysis.