Recent External Grants

NSF Grants

Igor Erovenko is Co-PI on a 3-year $1 Million NSF grant for Project INSIGHT: INclusion of challenges from Social Isolation Governed by Human behavior through Transformative research in epidemiological modeling. It will address behavioral responses to social isolation during the COVID-19 pandemic. It will concentrate on two types of questions: (1) How does compliance with isolation policies drive disease mitigation outcomes? and (2) Does social isolation lead to unanticipated negative social outcomes, and if so, how? In project INSIGHT, four diverse institutions of higher education are collaborating to develop novel and transformative research aimed at incorporating human social, behavioral, and economic interactions in mathematical epidemiological models.

Tom Lewis received a three year NSF grant (2021-2024) for “Narrow-Stencil Numerical Methods for Approximating Nonlinear Elliptic Partial Differential Equations”.

Ratnasingham Shivaji received an \$80,000, one year NSF grant (2022-2023) for “Mathematical and Experimental Analysis of Competitive Predator-Prey Models: Conditional Dispersal on Patches to Landscapes”. This project will be an integration of mathematical modeling, mathematical analysis, and experimental analysis of an insect herbivore and predator system to explore the effects of habitat fragmentation, interspecific competition and predation on the population dynamics and coexistence of species from the patch to the landscape level.

Dan Yasaki received an \$87,650 three year NSF grant (2022-2025) for “Building Confidence through Culturally Relevant Co-requisite Mathematics Courses within Math Pathways”.

Yi Zhang received a three year NSF grant (2021-2024) for “Novel Discontinuous Galerkin Methods for Deterministic and Stochastic Optimization Problems with Inequality Constraints.” The research is on the design, implementation, and analysis of a new class of discontinuous Galerkin methods for PDE-constrained optimization problems with uncertain data.

Sat Gupta is Co-PI on a 5-year  \$3,348,469 NSF LSAMP ( Louis Stokes Alliances for Minority Participation) grant. Provost Debbie Storrs serves as the PI for this grant. Other Co-PIs are Malcolm Schug (Biology), Julia Mendez Smith (Psychology), Julie Voorhees (OSP) , and Associate Vice Provost of Student Affairs Andrew Hamilton. The Alliance includes five, four-year, mid-sized universities that enroll students from across North Carolina. The University of North Carolina Greensboro will be the lead institution, joined by faculty and students from Appalachian State University, East Carolina University, University of North Carolina Wilmington, and Western Carolina University.

Simons Foundation Grants

Xiaoli Gao received a five year Simons Foundation Grant (2021-2026). Robust analysis has become an important issue in the current Big Data analysis era. This collaborative grant is to study how to robustify existing machine learning methods with applications in the financial market and medical studies.

Dan Yasaki received a five year Simons Foundation Grant (2021-2026) for “Voronoi Theory over Number Fields and Applications to Arithmetic Groups”.

Cliff Smyth will be supported by a five year Simons Foundation Collaboration Grant (2022-2027). He will investigate questions on “determinantal identities and power series using methods of discrete mathematics”.

Maya Chhetri received a five year (2022-27) Simons Foundation Collaboration Grant to study “singular problems in bounded and unbounded domains”.


Scott Richter is Co-PI on a three year 1.4 Million NICHD grant with Maryanne Perrin from the UNCG Nutrition Department. The project uses a multi-site study with eight geographically diverse milk bank partners that will examine and compare a broad range of nutrients and bioactive factors in human milk to create comprehensive, geographically diverse nutrient profiles for donor human milk (DHM). This nutritional database will be used to simulate the impact of pooling donors to identify effective strategies that can be used by milk banks to create more consistent nutrient profiles in DHM.