Collaborative Proposal: REU Site: North Carolina A&T State University and Elon University Joint Summer REU in Mathematical Biology
合作提案:REU 地点:北卡罗来纳州 A
基本信息
- 批准号:1851981
- 负责人:
- 金额:$ 9.64万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2019
- 资助国家:美国
- 起止时间:2019-09-01 至 2023-08-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The North Carolina A&T State University and Elon University Joint REU in Mathematical Biology is a 10-week residential summer program in which 10 undergraduate participants will conduct research on a variety of topics within the field of mathematical biology in small groups of two to three students. A team of faculty members from both host institutions will be involved with the planning and execution of the REU program and the location of the program will alternate between the host institutions. The primary objective of the program is to provide students an opportunity to conduct and present research with a diverse group of peers. Students will be recruited from a variety of institutions, including those with similar demographics to the host institutions. A heavy emphasis will be placed on recruiting students from underrepresented minorities, women, and individuals whose home institution have limited research opportunities in STEM (including community colleges and advanced high schools). At the conclusion of the summer program, each participant will have produced an oral presentation, a poster, and a manuscript. Participants will be encouraged to present their research at regional and national conferences, and to submit their manuscripts for publication in appropriate peer-reviewed journals. Each year, participants in this REU program will conduct research at the interface of mathematics and biology under the guidance of a group of dedicated faculty mentors. Research topics are drawn from a variety of fields, including pharmacokinetics, pharmacodynamics, epidemiological and ecological modeling, and biostatistics. A variety of modeling techniques will be employed, including differential equations modeling, agent-based modeling, stochastic equations, and regression analysis. Through participation in the REU program, participants will improve their oral and written communication skills, gain exposure to higher level proof-based mathematical topics, learn how to use software that is commonly used in mathematical research (such as MATLAB, LaTeX, and R), and participate in a variety of workshops aimed at career preparation and professional development. Through participation in the REU, students will have regular meetings with a faculty research mentor and a graduate assistant mentor. Students will give a weekly "work in progress" presentation, and twice a week, they will attend a mathematical proof course. Participation in the REU program will help students to be better prepared for graduate school or a career in the mathematical sciences. Results from the research conducted as a part of the program, and experiences from the planning and execution of the program will be disseminated through conference presentations and peer-reviewed publications.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.
在北卡罗来纳州AT州立大学和埃隆大学联合REU数学生物学是一个为期10周的住宅暑期课程,其中10名本科生参与者将进行各种主题的研究在数学生物学领域内的两个到三个学生的小组。来自两个主办机构的教师团队将参与REU计划的规划和执行,该计划的地点将在主办机构之间交替。该计划的主要目标是为学生提供一个机会,进行和目前的研究与不同群体的同龄人。学生将从各种机构招募,包括那些与主办机构相似的人口统计数据。重点将放在招收来自代表性不足的少数民族,妇女和个人的家庭机构在STEM(包括社区学院和高级高中)的研究机会有限的学生。在暑期课程结束时,每位参与者将制作一份口头报告,一张海报和一份手稿。将鼓励参与者在区域和国家会议上介绍他们的研究,并提交他们的手稿在适当的同行评审期刊上发表。每年,这个REU计划的参与者将在一组专门的教师导师的指导下,在数学和生物学的接口进行研究。研究主题来自各个领域,包括药代动力学,药效学,流行病学和生态学建模,以及生物统计学。将采用各种建模技术,包括微分方程建模,基于代理的建模,随机方程和回归分析。通过参与REU计划,参与者将提高他们的口头和书面沟通技巧,接触更高级别的基于证明的数学主题,学习如何使用数学研究中常用的软件(如MATLAB,LaTeX和R),并参加各种旨在职业准备和专业发展的研讨会。通过参与REU,学生将定期与教师研究导师和研究生助理导师会面。学生将每周进行一次“正在进行的工作”演示,每周两次,他们将参加数学证明课程。参加REU计划将帮助学生更好地为研究生院或数学科学职业做好准备。作为该计划的一部分进行的研究的结果,以及计划的规划和执行的经验将通过会议演示和同行评审的出版物传播。该奖项反映了NSF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。
项目成果
期刊论文数量(2)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
A Comparative Study of Penalized Regression and Machine Learning Algorithms in High Dimensional Scenarios
- DOI:10.1137/22s1538302
- 发表时间:2023
- 期刊:
- 影响因子:0
- 作者:Connor Shrader;Gabriel Ackall
- 通讯作者:Connor Shrader;Gabriel Ackall
Lessons Learned from a Virtual Summer Undergraduate Research Program
从虚拟暑期本科生研究计划中汲取的经验教训
- DOI:10.18833/spur/4/1/11
- 发表时间:2020
- 期刊:
- 影响因子:0
- 作者:Yokley, Karen;Luke, Nicholas
- 通讯作者:Luke, Nicholas
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