REU Site: Georgia Institute of Technology Mathematics Research Experiences for Undergraduates

这个数学REU项目的主要目的是：(i)为不同的本科生群体提供高质量的研究经验，以及专业发展活动；（ii）激励有才华的本科生追求研究生学习并取得成功；（iii）招收不同种类的本科生；（iv）从研究活动有限的院校吸引学生；（五）在暑期项目结束后，当学员们回到自己的学校后，继续与他们接触。参与者将与指导他们完成研究体验的个别教师单独或团队合作。每周进行团队建设和专业发展活动，包括研究生院的广泛指导，并在所有参与者的海报会议中达到高潮。学员毕业后，将准备在全国会议上展示他们的作品，并牢牢把握研究生院的好处，以及申请研究生院的时间表。本科生将参与各种各样的数学项目，从探索映射类小组到现代数据科学的主题。所有主题都反映了当前数学研究的重要趋势。从建筑到流体混合，再到现代信号分析，许多人都受到应用的强烈推动。例如，映射类组是根据曲面的所有变形的集合构建的。物体本身有额外的结构，继承自表面，但用完全不同的语言表达。这些特性反过来又使我们对如何最有效地混合两种非常坚硬的流体有了深入的了解。其他例子来自数据科学，这是一个非常广泛的主题，应用程序不断增加，包括模式的自动检测，从手写数字到社区结构。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The primary aims of this REU program in mathematics are to: (i) provide high-quality research experiences, together with professional development activities, for diverse cohorts of undergraduates; (ii) motivate talented undergraduates to pursue, and succeed in, graduate study; (iii) recruit a diverse cohort of undergraduates; (iv) attract students from institutions that have limited research activities; and (v) continue engagement of the participants beyond the summer program when they return to their home institutions. Participants will work individually or in teams with individual faculty members who guide them through a research experience. Weekly team-building and professional development activities take place, including an extensive guide to graduate school, and culminating in a poster session for all participants. The participants leave the program prepared to present their work at conferences nationwide and with a firm grasp of the benefits of graduate school as well as a timeline for applications to graduate school.Undergraduates will participate in a diverse array of projects in mathematics, ranging from explorations in mapping class groups to topics in modern data science. All topics reflect important current trends in mathematics research. Many are strongly motivated by applications, ranging from architecture, to mixing of fluids, to modern signal analysis. For example, mapping class groups are built from the collection of all deformations of a surface. The object itself has additional structure, inherited from the surface, but expressed in an entirely different language. Those properties in turn yield insights into, for instance, how to most efficiently mix two types of very stiff fluids. Other examples come from data science, a very broad subject with an ever-increasing set of applications, including automatic detection of patterns, from hand written digits to community structures.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.