Rice University’s Department of Statistics and Data to Knowledge (D2K) is launching a new suite of artificial intelligence courses designed to expand AI literacy across campus, deepen technical expertise, and prepare students to engage responsibly with rapidly evolving AI technologies. As leaders in data science research, D2K faculty have been at the forefront of developing cutting-edge AI tools for the past few decades.
Supported by university funding and aligned with Rice’s Momentous 10-year strategic plan, the initiative includes three new AI courses—ranging from introductory to advanced—as well as a faculty learning community focused on integrating AI with physical systems such as robotics and engineering design.
Led by D2K Director Chad Shaw and teaching professors Arko Barman, Xinjie Lan, and Lorenzo Luzi, who are faculty at Rice's George R. Brown School of Engineering and Computing, the effort responds to growing student demand for AI education and a clear institutional need: ensuring students across disciplines can not only use AI tools, but also understand their limitations, ethical implications, and real-world impact.
“Our goal is to ensure students don’t just learn how to use AI tools, but understand how they work, where they fail, and how they can be applied responsibly in real-world settings,” said Chad Shaw, D2K director. “This coordinated set of courses allows us to meet students where they are and guide them toward deeper, more thoughtful engagement with AI.”
The first course, “AI Tools Survey & Applications,” launches on Jan. 12, 2026, and is open to all Rice students. Taught by Lorenzo Luzi, the experiential, project-based course introduces students to specialized AI technologies in their area of interest, such as art, science, engineering, business, heath, wellness, or productivity. Students will research, evaluate, and demonstrate these tools while critically assessing their strengths, weaknesses and appropriate use cases.
“While most students are familiar with ChatGPT and other general AI models, many are not aware of specialized AI solutions that are now available for specific disciplines,” Luzi said. “This course will allow students to explore them. In addition to building creative problem-solving and critical thinking skills, the students will also hone their verbal and written communication skills by creating presentations, reports, and a visual guide, which will be made publicly available to the broader Rice community.”
Two additional courses launching in Fall 2026 extend the learning pathway for students seeking deeper engagement. “Statistical Foundations of Generative AI,” an intermediate level course taught by Xinjie Lan, is designed for students from all disciplines who want to understand the mathematical and statistical principles behind modern generative AI systems.
“While generative AI tools can be very helpful and are being used increasingly in every domain, they are inherently imperfect,” Lan said. “This course will expose the students to the security, transparency, bias, and sustainability issues of various AI models so they can go beyond simply deploying AI tools to understanding how to design systems that are more equitable, trustworthy, efficient, and aligned with human values.”
At the advanced level, “Modern Artificial Intelligence Models and Algorithms” taught by Arko Barman, will offer hands-on experience building and evaluating contemporary AI models used in real-world applications. The course combines lectures, team-based projects, and student-led discussions of current AI research, with priority enrollment for students in statistics and data science programs.
“Many existing courses focus on earlier generations of machine learning models,” Barman said. “This course is designed to help students engage directly with the models driving today’s AI applications and to understand both the technical and ethical challenges involved in building better, responsible systems.”
In addition to the student-focused courses, Chad Shaw will lead a faculty learning community to explore new educational opportunities at the intersection of AI, data science, and three-dimensional physical systems. His collaborators in this initiative include David Pynadath, executive director of Ken Kennedy Institute; Maria Oden, director of the Oshman Engineering Design Kitchen (OEDK), Sabia Abidi, assistant teaching professor in bioengineering, and Heather Bisesti, an OEDK lecturer.
“Applying AI to robotics or device-based engineering problems introduces constraints that don’t exist in purely digital environments,” Shaw said. “By collaborating across units, we’re working to develop new courses that help students integrate AI with physical systems in meaningful and responsible ways.”
By creating these new educational opportunities, D2K faculty are leading the way in preparing and empowering undergraduate students for promising careers in AI and further cementing Rice’s long-standing leadership in this area.