REU/RET Site: Computational Mathematics for Data Science

埃默里大学本科生和教师研究经验网站侧重于计算数学及其在数据科学中的应用。数据科学对美国具有基础性和战略性的重要性，影响着几乎所有的科学领域。然而，学术培训机会和熟练工人的数量并没有跟上私营和公共实体需求的快速增长。该网站强调发展研究和专业技能，这将提高参与者在数据科学和计算数学方面理解、实施和有效沟通研究的能力。该项目为期三年，每年将培训12名本科生和4名教师，为期6周。埃默里大学数学系和计算机科学系的教员将对参与者进行监督和指导。该网站的活动将使本科生具备在该领域开展职业所需的数学和计算技能，并将激励他们攻读研究生学位。招生将在全国范围内进行，重点关注代表性不足的群体和在该领域研究机会有限的大学入学的学生。通过让在职的K-12教师参与研究经验，该网站将扩大其对高中生的影响，并帮助创新课程设计和改善职业咨询。这些教师将从亚特兰大大都会区和全国其他地区招聘。REU/RET网站将向本科生和教师介绍从数据同化到机器学习等应用中使用的数学理论和计算工具，并使他们能够通过团队解决研究问题来推进这些领域。该网站的活动将围绕一个共同的主题，每年都有所不同。该网站的年度研究主题将分别是“从图像中学习”、“将模型与数据结合”和“数据科学促进社会正义”。在每个主题中，教师导师将提出至少四个研究问题，并建议学生-教师团队研究创新的解决方案。与更广泛的科学界相关的新见解将在学生/教师撰写的出版物、开源软件和在线博客中被创造和传播。教师们还将制作和提供课堂免费使用的材料。这些研究项目将使参与者超越标准课程。该网站的教育部分将向参与者介绍一系列数学技术，包括机器学习、深度神经网络、数值线性代数、优化、偏微分方程和统计学。教师导师还将为他们的学员提供专业和计算技能，包括科学写作、口头和海报展示以及云计算。每周的研讨会将以小组活动和教师主导的关于数据和伦理、算法偏见、公共奖学金的演讲为特色。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 Emory Research Experience for Undergraduates and Teachers site focuses on computational mathematics and its applications in data science. Data science is of fundamental and strategic importance to the US and impacts nearly every field of science. However, the number of academic training opportunities and skilled workers has not kept pace with the rapid growth in demand from private and public entities. The site emphasizes developing research and professional skills that will increase the participants' ability to understand, conduct, and effectively communicate research in data science and computational mathematics. The three-year program will train twelve undergraduates and four teachers annually for six weeks. Faculty members from Emory's Departments of Mathematics and Computer Science will supervise and mentor the participants. The site's activities will equip undergraduate students with the mathematical and computational skills required to launch careers in this area and will motivate them to pursue a graduate degree. Student recruitment will be nationwide, with a strong focus on underrepresented groups and students enrolled in colleges with limited research opportunities in this area. By involving in-service K-12 teachers in the research experience, the site will extend its impact to high-school students and help innovate curricula design and improve career counseling. The teachers will be recruited from the diverse Atlanta metro area and other districts nationwide.The REU/RET site will introduce undergraduate students and teachers to the mathematical theory and computational tools used in applications ranging from data assimilation to machine learning and enable them to advance these fields by solving research problems in teams. The site's activities will be centered around a common theme that differs each year. The site's annual research themes will be Learning from Images, Combining Models with Data, and Data Science for Social Justice, respectively. Within each theme, faculty mentors will pose at least four research problems and advise student-teacher teams to work on innovative solutions. New insights of relevance to the broader scientific community will be created and disseminated in student/teacher-authored publications, open-source software, and online blogs. The teachers will also create and make freely available materials for classroom-use. The research projects will take participants beyond standard coursework. The site's educational component will introduce the participants to a range of mathematical techniques, including machine learning, deep neural networks, numerical linear algebra, optimization, partial differential equations, and statistics. The faculty mentors will also provide their mentees with professional and computational skills, including scientific writing, oral and poster presentations, and cloud computing. The weekly seminar will feature group activities and faculty-led presentations on data and ethics, algorithmic bias, public scholarship.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.