REU in Extremal Graph Theory and Dynamical Systems

Rochester Institute Of Tech, Rochester NY

Investigators

Abstract

The NSF-REU Site in Extremal Graph Theory and Dynamical Systems at the Rochester Institute of Technology (RIT) will actively engage ten students in each of the summers 2014, 2015, and 2016 in a research experience in mathematics. Research projects will be in the areas of graph theory and dynamical systems, some of which are linked to mathematical biology. Projects will include both applied and theoretical topics. Applied projects will include development and analysis of functional connectivity models of the human brain, and modeling of cardiac arrhythmia. Projects with a theoretical focus will include problems from extremal graph theory, graph labeling, and delay differential equations. All students will work directly with RIT faculty for the entirety of the program and will receive mentoring in mathematical research practices, as well as in written and oral communication. The program will have a heavy emphasis on networking with other mathematicians and will include a "Researcher in Residence," where an expert from outside of our university visits the program and works with the students. Results from research projects will be disseminated through publications in refereed journals, presentations at national and regional mathematical meetings, and at the students' home institutions. Students will be encouraged to pursue graduate studies and employment in the mathematical sciences. During the program students will participate in an Ethics in Science Workshop. The REU program will intersect with RIT's Summer Mathematics Institute where each of the REU students will present to more than 50 mathematics high school teachers from New York State. The recruitment efforts will target students from universities, liberal arts colleges, and community colleges. The PI aims to have 80 percent of the participants from outside of the host institution, with an emphasis on drawing students from colleges without Ph.D. programs or have limited research opportunities.