RTG: Vertically Integrated Interdisciplinary Training in Mathematics for Human Health

University Of Texas At Arlington, Arlington TX

Investigators

Abstract

The UTA-RTG: Vertically Integrated Interdisciplinary Training in Mathematics for Human Health program at the University of Texas at Arlington (UTA) will train and mentor three multi-level cohorts of interdisciplinary researchers (a total of nine undergraduates, six Ph.D. students, and two postdoctoral researchers). The Research Training Group (RTG) will leverage on the fact that UTA is a Hispanic Serving Institution with a large population of veterans that offers a diverse recruitment pool with many groups historically underrepresented in the sciences. RTG teams will conduct research applying mathematical modeling to answer questions on topics in cancer biology, computational neurology, and vector-borne diseases. RTG scholars will be trained in mathematical theory and computational methods for diagnosis, assessment, prevention, and treatment of chronic and infectious diseases. Program activities will be led by a group of ten UTA Mathematics faculty, in collaboration with researchers from UTA Nursing, Bioengineering, Biology, and Psychology, as well as the University of Texas Southwestern Medical Center, the University of North Texas Health Science Center, and the VA North Texas Health Care System. The program’s experienced mentors draw on a best-practices model of multi-level mentoring in which faculty and trainees at all levels work together to share their own levels of expertise, producing researchers who are also ready to act as mentors, and in teams in biotechnology companies and health organizations as well as academia. This RTG program integrates mentoring, interdisciplinary research, and coursework. The program research, guided by experimental work, will advance mathematics by developing state-of-the-art stochastic modeling and optimal control frameworks for the dynamics of cancer biomarkers, neuronal physiology, and immunological interactions between co-circulating vector-borne viruses; and efficient and accurate computational methodologies for solving differential and integral equations, as well as integrating modern data science and machine learning methods with the aforementioned classical techniques for analyzing data and solving the proposed mathematical problems. The program’s research experiences include: a weekly program seminar and group roundtables that develop research, teaching, and collaborative skills, while also providing exposure to ongoing interdisciplinary research work at UTA; hands-on research experiences and internships at off-campus RTG partner sites and UTA labs; and writing reports and presenting research results at conferences. The UTA-RTG program naturally builds on several federally funded mentoring and training programs at UTA and aligns well with institutional goals of enhancing interdisciplinary research, education, and community engagement in Health and the Human Condition. This award is co-funded by the Workforce program and the Mathematical Biology program at the Division of Mathematical Sciences. 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.