On October 1, 2023, Prof. Michael "Misha" Chertkov was awarded the NSF-Innovation in Graduate Education (IGE) grant. This award will revolutionize the graduate program in Applied Mathematics (AM) by integrating Artificial Intelligence (AI) and enabling non-traditional research careers in National Laboratories (NLs) and Industrial Laboratories (ILs).
This National Science Foundation Innovations in Graduate Education (IGE) award to the University of Arizona will revolutionize the graduate program in Applied Mathematics (AM) by integrating Artificial Intelligence (AI) and enabling non-traditional research careers in National Laboratories (NLs) and Industrial Laboratories (ILs). AM is a versatile science that plays a crucial role in cutting-edge research across all STEM disciplines. By infusing AI into AM, this research project team aims to take the ongoing AI revolution to new heights, solving emerging national and global challenges. The Applied Mathematics Graduate Interdisciplinary Program at the University of Arizona (AM@UA) will serve as a testing ground for this innovative graduate training model, in partnership with NLs and ILs. The overarching goal is to create a pipeline of researchers equipped with the skills needed to address complex issues and foster solutions that benefit society as a whole. By modernizing the AM curriculum and aligning it with national security needs, we not only advance the field of study but also attract and retain a diverse group of students, including women and underrepresented minorities, to pursue non-academic STEM careers. This project will provide a blueprint for other AM Ph.D. programs nationwide, forging a path towards a diverse, competitive, and future-ready workforce capable of thriving in the era of AI.
The AM@UA project is driven by the vision of transforming STEM graduate education through an integrated approach that bridges the gap between classic AM and novel AI disciplines. The project seeks to understand and address the challenges of crossing disciplinary divides between academia and non-academic STEM domains. With the current national focus on areas of priority, we aim to explore effective strategies for crossing these divides to meet the growing demand for specialized skills. The proposed social science research will evaluate the effectiveness of these approaches and delve into the underlying processes responsible for their success. The project will introduce innovative triadic collaborations involving a PhD student, their university advisor, and a co-advisor from a national or industrial laboratory. This collaboration model will offer long-term research opportunities and internships, nurturing students' expertise in both traditional and contemporary AM, including data science and AI.
At its core, the project will generate new knowledge in STEM graduate education, advancing the field by integrating AI into AM to create a workforce capable of tackling AI-driven and mathematics-enabled challenges. Through its emphasis on diversity and inclusion, the project aims to attract and retain a talented pool of students, ensuring they are well-prepared for a variety of non-academic STEM careers. By collaborating with esteemed partners like Raytheon and Department of Energy laboratories, the project team will further bridge the academic-industry gap, facilitating seamless transitions for graduate students between these settings. The outcomes of this project will pave the way for generalized models of graduate applied mathematics workforce training, applicable to other AM Ph.D. programs and national and industrial laboratories. Ultimately, this endeavor will make significant contributions to society by nurturing a diverse and globally competitive workforce equipped to address the most pressing challenges of today.
The Innovations in Graduate Education (IGE) program is focused on research in graduate education. The goals of IGE are to pilot, test and validate innovative approaches to graduate education and to generate the knowledge required to move these approaches into the broader community.
- Michael Chertkov (Principal Investigator)
- Sanlyn Buxner (Co-Principal Investigator)
- Erin Leahey (Co-Principal Investigator)
- Charles Gomez (Co-Principal Investigator)
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