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NOBEL PRIZE 2026

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NSFDirectorate for Mathematical and Physical Sciences

REU Site: Undergraduate Research in the Mathematical Sciences and their Applications

Active
Institution
Texas A&M University, TX
Principal investigator
J Maurice Rojas
Funding
$298K
Duration
2026–2029
Open portfolio

Moonbase score

Still being scored

Abstract

The Research Experience for Undergraduates (REU) site in the Department of Mathematics at Texas A&M University will host twelve talented undergraduates for research training for eight weeks each summer. The REU faculty will specifically seek talented students who lack or have been isolated from research opportunities at their home institution. Students will have the opportunity to learn cutting-edge mathematical ideas from scratch and contribute to solving challenging problems underlying many real-world problems from algorithmic complexity, biochemistry, cryptography, optimization, and physics. Students will receive free housing, reimbursement for travel, and a stipend. The REU program will have three research tracks per summer. These are chosen on a rotating basis from six choices: (1) Algebraic Methods in Mathematical Biology, (2) Algorithmic Algebraic Geometry, (3) Semi-Algebraic Geometry in Nonlinear Schrodinger Equations, (4) Interpolation in Zonoids, (5) Matrix Schubert Varieties, and (6) Algebraic and Enumerative Combinatorics. The first track will investigate the problem of parameter identifiability in models arising in biology. The second track includes topics such as A-discriminants, tropical approximation of algebraic sets, and applications to optimization and number theory. The third track will explore the long-time behavior of solutions of models arising in mathematical physics. The fourth track concerns questions related to high-dimensional probability and statistics. The fifth track is on determinantal ideals (objects key to recent speed-ups for certain algorithms in data science). Finally, the sixth track will investigate combinatorial models of parking functions (a central technique in enumeration). Tracks (2), (4), (5), and (6) approach foundational problems adjacent to reinforcement learning (which is a part of NSF's Artificial Intelligence initiative), while Tracks (1) and (3) respectively approach foundational problems connected to the Biotechnology and Quantum initiatives of NSF. 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.

Research team

  • J Maurice RojasPI
  • Anne J ShiuCo-PI

LOADING MOONBASE SCORE

Directorate for Mathematical and Physical Sciences01002627DB NSF RESEARCH & RELATED ACTIVITRSCH EXPER FOR UNDERGRAD SITESuniversityreviewstatisticsequationshousinginitiativecriteriameriteightparking

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