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| Funder | National Science Foundation (US) |
|---|---|
| Recipient Organization | Texas A&M University |
| Country | United States |
| Start Date | Sep 01, 2024 |
| End Date | Aug 31, 2029 |
| Duration | 1,825 days |
| Number of Grantees | 5 |
| Roles | Principal Investigator; Co-Principal Investigator |
| Data Source | National Science Foundation (US) |
| Grant ID | 2345874 |
Artificial Intelligence (AI) is fundamentally reconfiguring the engines of scientific discovery, technological innovation, and industrial manufacturing that fuel modern economies. Excitement for revolutionary advances in this domain is tempered, however, by unsettling changes to the nature of human work and fears of compounding social inequities. Additionally, current AI is founded on ad hoc designs, sub-optimal links to foundational mathematics and computing theory, and poorly considered demands on energy sources.
This National Science Foundation Research Traineeship (NRT) award to Texas A&M University will address these shortcomings and demands by training graduate master’s and doctoral students in the interdisciplinary fields of the mathematical, molecular, and materials foundations of AI. This effort anticipates training adaptive changemakers who will design AI to work with people and educate people to work with AI.
The project anticipates fostering a culture of team science and community engagement by training sixty-seven (67) MS and PhD students, including nineteen (19) funded trainees, from graduate programs in statistics and mathematics, electrical and computer engineering, computer science, chemistry, materials science and engineering, mechanical engineering, and interdisciplinary education.
Trainees will work at the intersection of foundational theory, AI algorithms, neuromorphic (human brain-inspired) materials discovery, and analog circuit design to close the AI for Materials & Circuits with the Materials & Circuits for AI loop. The traineeship will exponentially amplify the impact of AI by designing and creating new materials and computing architectures.
Through close interactions within a rich ecosystem and communities, this project will help attain the full potential of AI to uplift communities, democratize scientific and technological discoveries, empower a more equitable information economy, and build societal trust by emphasizing the theme of “better together,” i.e., humans and AI working in concert to realize human potential. Furthermore, the traineeship will serve as a test bed for a transformative doctoral education model with essential components for innovative graduate education that will be customized, iterated, refined, scaled, and sustained.
The project will develop a new graduate professional certificate and will further devise a Skills and Experiences Pathway that will be expanded across graduate and professional programs. Ultimately, this project will advance new M.S. and Ph.D. training models steeped in a rich and diverse regional innovation ecosystem related to AI and Semiconductor Manufacturing that will serve as a blueprint for other institutions.
The NSF Research Traineeship (NRT) Program is designed to encourage the development and implementation of bold, new potentially transformative models for STEM graduate education training. The program is dedicated to effective training of STEM graduate students in high priority interdisciplinary or convergent research areas through comprehensive traineeship models that are innovative, evidence-based, and aligned with changing workforce and research needs.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Texas A&M University
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