Award Abstract # 2136198
RTG: Optimization and Inversion for the 21st Century Workforce

NSF Org: DMS
Division Of Mathematical Sciences
Recipient: UNIVERSITY OF UTAH
Initial Amendment Date: June 21, 2022
Latest Amendment Date: June 30, 2024
Award Number: 2136198
Award Instrument: Continuing Grant
Program Manager: Stacey Levine
slevine@nsf.gov
 (703)292-2948
DMS
 Division Of Mathematical Sciences
MPS
 Directorate for Mathematical and Physical Sciences
Start Date: July 1, 2022
End Date: June 30, 2027 (Estimated)
Total Intended Award Amount: $2,498,692.00
Total Awarded Amount to Date: $1,472,939.00
Funds Obligated to Date: FY 2022 = $911,075.00
FY 2023 = $30,400.00

FY 2024 = $531,464.00
History of Investigator:
  • Kenneth Golden (Principal Investigator)
    golden@math.utah.edu
  • Elena Cherkaev (Co-Principal Investigator)
  • Fernando Guevara Vasquez (Co-Principal Investigator)
  • Christel Hohenegger (Co-Principal Investigator)
  • Akil Narayan (Co-Principal Investigator)
Recipient Sponsored Research Office: University of Utah
201 PRESIDENTS CIR
SALT LAKE CITY
UT  US  84112-9049
(801)581-6903
Sponsor Congressional District: 01
Primary Place of Performance: University of Utah
155 S 1400 E RM 233
SALT LAKE CITY
UT  US  84112-8930
Primary Place of Performance
Congressional District:
01
Unique Entity Identifier (UEI): LL8GLEVH6MG3
Parent UEI:
NSF Program(s): APPLIED MATHEMATICS,
WORKFORCE IN THE MATHEMAT SCI
Primary Program Source: 01002526DB NSF RESEARCH & RELATED ACTIVIT
01002324DB NSF RESEARCH & RELATED ACTIVIT

01002425DB NSF RESEARCH & RELATED ACTIVIT

01002627DB NSF RESEARCH & RELATED ACTIVIT

01002223DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 9251, 7301, 079Z
Program Element Code(s): 126600, 733500
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.049

ABSTRACT

This research training group (RTG) aims to develop a new generation of applied mathematicians who are experts in the areas of mathematical optimization, inversion, and data science. Trainees will gain cutting-edge knowledge and experience in visualizing, analyzing, and learning from real-world data. The RTG will strengthen the graduate and postdoctoral programs to attract top students in the nation and place them in top jobs. The investigators will diversify the recruitment with efforts at the high school and early undergraduate levels, geared towards underrepresented groups to broaden participation in mathematics. The RTG will introduce novel transformative experiences for students and emphasize on critical career transition points to attract and retain students into math-related careers. The RTG project will encourage interaction, collaboration, and mentorship between participants at different stages of their academic careers. Core examples include working with junior high and high school teachers to make math more accessible and exciting to students, vertically integrated Focused Reading/Research Groups, a Science Research Initiative to significantly increase the number of first-year undergraduates involved in research, and Polar Research Experiences on Arctic Sea ice that provide a unique hands-on opportunity for students to gather, analyze, and model their own data, closing the loop between theory and practice.

Mathematical optimization, inversion, and data science play a crucial role in applications across the sciences, engineering, and medicine. This RTG leverages the expertise of mathematics faculty in these and related areas to train and mentor students across levels ranging from high school to doctoral and postdoctoral scholars. Some of the core projects will include optimal design of metamaterials, porous media, photonics, climate modeling, machine learning, remote sensing, polar ecology, medical imaging, geophysical exploration, drug delivery and discovery, and uncertainty quantification. The RTG will introduce a new optimization-centered graduate curriculum, offer trainees at all levels significant experience working on important interdisciplinary problems in vertically integrated settings, and, mimicking successful engineering classes, a mathematical design competition to motivate students, and a thematic RTG conference to provide collaborative mechanisms between RTG participants and internationally renowned researchers. This RTG project will benefit the broader math community and beyond as the involved students and postdocs assume leading roles as researchers and educators in the 21st-century workforce.

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.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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(Showing: 1 - 10 of 54)
Abedin, Farhan and Feldman, William M "Quantitative convergence of the bulk free boundary in an oscillatory obstacle problem" Interfaces and Free Boundaries, Mathematical Analysis, Computation and Applications , v.26 , 2024 https://doi.org/10.4171/ifb/501 Citation Details
Alishahi, Meysam and Little, Anna and Phillips, Jeff M "Linear Distance Metric Learning with Noisy Labels" Journal of Machine Learning Research , 2024 Citation Details
Arehart, Emerson and Reimer, Jody R. and Adler, Frederick R. "Strategy maps: Generalised givingup densities for optimal foraging" Ecology Letters , v.26 , 2023 https://doi.org/10.1111/ele.14160 Citation Details
Armstrong, Scott and Venkatraman, Raghavendra "Optimal Convergence Rates for the Spectrum of the Graph Laplacian on Poisson Point Clouds" Foundations of Computational Mathematics , 2025 https://doi.org/10.1007/s10208-025-09696-9 Citation Details
Baker, J and Cherkaev, E and Druskin, V and Moskow, S and Zaslavsky, M "Regularized reduced order Lippmann-Schwinger-Lanczos method for inverse scattering problems in the frequency domain" Journal of Computational Physics , v.525 , 2025 https://doi.org/10.1016/j.jcp.2025.113725 Citation Details
Baker, Justin and Cherkaev, Elena and Narayan, Akil and Wang, Bao "Learning Proper Orthogonal Decomposition of Complex Dynamics Using Heavy-ball Neural ODEs" Journal of Scientific Computing , v.95 , 2023 https://doi.org/10.1007/s10915-023-02176-8 Citation Details
Banwell, Alison F. and Burton, Justin C. and Cenedese, Claudia and Golden, Kenneth and Åström, Jan "Physics of the cryosphere" Nature Reviews Physics , 2023 https://doi.org/10.1038/s42254-023-00610-2 Citation Details
Bhattacharya, Debdeep and Evans, Tyler P and Cherkaev, Andrej "Design of resilient structures by randomization and bistability" International Journal of Engineering Science , v.215 , 2025 https://doi.org/10.1016/j.ijengsci.2025.104296 Citation Details
Boyd, Zachary M and Fraiman, Nicolas and Marzuola, Jeremy L and Mucha, Peter J and Osting, Braxton "An Escape Time Formulation for Subgraph Detection and Partitioning of Directed Graphs" SIAM Journal on Matrix Analysis and Applications , v.45 , 2024 https://doi.org/10.1137/23M1553790 Citation Details
Cheng, Nuojin and Malik, Osman Asif and Xu, Yiming and Becker, Stephen and Doostan, Alireza and Narayan, Akil "Subsampling of Parametric Models with Bifidelity Boosting" SIAM/ASA Journal on Uncertainty Quantification , v.12 , 2024 https://doi.org/10.1137/22M1524989 Citation Details
Chen, Haoyu and Little, Anna and Narayan, Akil "Largest Angle Path Distance for Multi-Manifold Clustering" International Conference on Sampling Theory and Applications , 2023 https://doi.org/10.1109/SampTA59647.2023.10301401 Citation Details
(Showing: 1 - 10 of 54)

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