Texas A&M University has received a $3 million award from the National Science Foundation’s Research Traineeship (NRT) program to transform artificial intelligence (AI) education and research. Entitled “Enabling AI on the Fly,” the five-year project will train 67 graduate students in the interdisciplinary fields of AI’s mathematical, molecular, and materials foundations. The goal is to prepare adaptive changemakers across multiple disciplines to address the current shortcomings of AI research and education. The NRT Program encourages novel and potentially transformative STEM education models for graduate students in high-priority, interdisciplinary, or convergent research areas.
The grant’s principal investigator is Dr. Sarbajit Banerjee, a Professor and Davidson Chair in Science in the Department of Chemistry at Texas A&M. The project is a collaboration between the College of Arts & Sciences, the College of Engineering, Texas A&M Engineering Experiment Station, Texas Semiconductor Institute, the Center for Teaching Excellence, and TAMIDS.
Dr. Banerjee said, “We intend for our NRT to train a new generation of diverse, adaptive, agile, and entrepreneurial Aggies who can draw upon insights across disciplines and work in teams to shape AI and its evolving interface with society.”
Banerjee is joined by Co-PIs, Dr. Karen Butler-Purry, Professor in the Department of Electrical & Computer Engineering; Dr. Bani Mallick, Distinguished Professor and Susan M. Arseven `75 Chair in Data Science and Computational Statistics in the Department of Statistics; Dr. Nick Duffield, Director of the Texas A&M Institute of Data Science and Royce E. Wisenbaker Professor I in the Department of Electrical & Computer Engineering; and Dr. Clinton Patterson, Assistant Director of Mentoring and Graduate Education at the Center for Teaching Excellence.
Dr. Duffield, director of TAMIDS and leader of TAMIDS Knowledge Development Lab, will serve as Curriculum Coordinator for the project. Duffield said, “Recent innovations in research for new materials for semiconductor manufacturing present a compelling opportunity to cultivate the next generation of scientists and engineers who use AI methods to realize this potential. I look forward to building on the experience of the Institute’s Knowledge Development Lab in creating interdisciplinary programs for education and training in AI applications.”
This initiative will foster community engagement and build societal trust, emphasizing the “better together” theme – humans and AI working in concert. Trainees will learn in an innovation ecosystem at the intersection of AI and Semiconductor Manufacturing, exploring new materials and computing architectures that will exponentially amplify AI’s impact. The project will develop innovative doctoral education models and a new graduate professional certificate, setting a blueprint for other institutions.
More about the traineeship program and how to participate will be announced later.