Texas A&M Hosts Inaugural AI Workshop For Science And Engineering
The first-ever Research in AI for Science and Engineering (RAISE) Workshop, held at the Zachry Engineering Education Complex, highlighted bold initiatives already in motion.
Texas A&M brought together a high-powered crowd of researchers, faculty, students, and at least one curious AI model recently for the first-ever Research in AI for Science and Engineering (RAISE) Workshop, held at the Zachry Engineering Education Complex. The day-long event explored how artificial intelligence — especially those mysterious “foundation models” and ambitious AI agents — can accelerate scientific discovery and engineering breakthroughs.
Organized by Dr. Shuiwang Ji, Professor of Computer Science and Engineering and a core leader of the RAISE Initiative, the workshop drew nearly 200 participants and was a clear expression of Leadership in an era where scientific progress increasingly requires teamwork between code and curiosity.
Dr. Costas Georghiades, Interim Vice President for Research, opened the event by underscoring the Excellence and Integrity Texas A&M brings to cutting-edge research. “This is a grassroots effort,” he said. “The kind of collaborative, interdisciplinary event I believe is critical for the future of research.”
He highlighted bold initiatives already in motion — including a proposed quantum program and the $45 million investment in the new SuperPOD computing system. Clearly, Texas A&M is betting on big data.
“We are just beginning. The real vision of RAISE is to use computation not just to simulate, but to discover.
The morning featured tutorials that aimed to demystify foundational AI models — those multi-billion-parameter behemoths like ChatGPT and Gemini. Dr. Ji explained how these models generalize across tasks, acting as the “Swiss Army knives” of modern research tools.
And yet, despite their immense capabilities, these models still lack a proper understanding of physics — something every Aggie learns early in ENGR 102. Dr. Ji emphasized that embedding scientific knowledge into AI is one of our greatest opportunities, and a challenge that demands both Respect for domain expertise and the Excellence of rigorous science.
Afternoon sessions spotlighted projects using AI in atomic simulations, drug design, turbulence modeling, semiconductor analysis, and more. Across disciplines, one theme kept surfacing: AI can accelerate discovery, reduce simulation time, and guide experiments—but only when paired with expert human judgment.
Speakers imagined a future where AI agents autonomously design materials, generate hypotheses, and even run experiments (under close Aggie supervision, naturally). As much as these agents impress, there was a shared recognition that Loyalty to scientific rigor and Integrity in data use are essential. No one wants an AI that hallucinated its way into your carbon capture pipeline.
Panelists didn’t shy away from tough topics, including the risk of unverifiable claims and the rise of “AI-washing” in scientific literature. The solution? Open science practices, peer review, and the kind of Selfless Service that defines the Aggie spirit — sharing tools, data, and insights to build a better research community.
At lunch, attendees got a first look at the new Texas A&M SuperPOD — one of the university’s largest investments in research infrastructure to date. This GPU-powered giant is built for both traditional high-performance computing and fast-paced AI workflows. It’s designed to empower researchers system-wide — and it doesn’t even need a midnight taco run.
As the first official event of the RAISE Initiative, the workshop sets a strong foundation for future efforts. Dr. Ji announced plans for a multiday bootcamp and expanded partnerships with institutions across Texas and beyond.
“We are just beginning,” he said. “The real vision of RAISE is to use computation not just to simulate, but to discover.”
Leading with its Core Values as a compass, Texas A&M is charting a bold course into AI-powered science — where Leadership meets innovation, and Respect for both human insight and machine intelligence drives real-world impact.
The Research in AI for Science and Engineering (RAISE) Workshop was sponsored by The Texas A&M Institute of Data Science and The Texas A&M University System Office of Research.
