Three HMC Math 教师 Receive NSF 格兰特s

奖s from the National Science Foundation were granted to three members of the faculty in the Department of 数学 at Harvey Mudd College. The grants will allow them to further research ranging from studying networks using mathematical models to determining best practices for in-class group work monitoring in K-12 education.

希瑟·辛-布鲁克斯的项目, “Advances in bounded-confidence models on networks,” was funded by an NSF RUI grant, which is intended to facilitate research at primarily undergraduate institutions. Her three-year project focuses on the analysis of mathematical models for opinion dynamics on social networks. This work will provide a framework to connect the theoretical study of these mathematical models with real data from online social networks. The project will provide research opportunities for HMC students (two each summer for the next three years, with potentially one or two more each summer from faculty startup funds). Zinn-Brooks is assistant 数学教授.

Darryl勇, 96年, 数学教授, is a co-principal investigator on the project, “Teaching Amidst Uncertainty: Developing 数学 Teachers’ & Groupwork Monitoring Practices,” a $2.600万年, four-year award funded by the NSF Division of 研究 on Learning in Formal and Informal Settings. This project (building upon previous work by 勇 and fellow researchers) is focused on trying to ascertain best practices for in-class group work monitoring in K-12 education (e.g., how do teachers promote productive mathematical talk in groups, how do they ensure equitable participation of group members?). Along with lead PI Ilana Horn (Vanderbilt University), 勇, who is currently director of the 数学 诊所, 会和博士后一起工作吗, graduate students and undergraduate students on the project.

杰米黑线鳕 joins the Harvey Mudd faculty July 1 after serving as a computational and applied mathematics assistant professor (帖子doc) in the UCLA 数学 Department, where she received a three-year NSF grant for computational mathematics. The award will support the project “Tensor Models, 方法, 和医学,” which could lead to tools for tensor topic modeling that treat large-scale, 复杂的, multi-modal data in its natural form and may advance the theoretical understanding of these models, their training methods and the 复杂的 tensor data to which they are applied. Haddock and fellow researchers will partner with collaborators in the Harbor-UCLA Medical Center Department of Cardiology to apply their findings to case study cardiac imaging data and will fund summer undergraduate research student support and a summer workshop connecting application domain experts with mathematical experts and summer undergraduate students.

NSF grants are the largest share of external support for faculty research at Harvey Mudd.