Collaborative Research: Expanding the Reach of Industrial Career Training for Graduate Students

合作研究：扩大研究生工业职业培训的范围

• 批准号: 2016099
• 负责人: Taras Lakoba
• 金额: $ 0.84万
• 依托单位: University of Vermont & State Agricultural College
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2022-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2016099&HistoricalAwards=false
• 关键词: Collaborative; Research; Expanding; Reach; Industrial

The 16th annual Graduate Student Mathematical Modeling Camp (GSMMC) will be held June 9–12, 2021 at the University of Delaware, followed the week after by the 36th annual Mathematical Problems in Industry (MPI) workshop, June 14–18, 2021 at the University of Vermont. GSMMC is a mentored, problem-solving workshop, at which small teams of Ph.D. students from across the U.S. are guided through successful mathematical modeling of real-world problems presented by faculty or experienced postdoctoral mentors. Under careful mentoring, student participants build their modeling, teamwork and presentation skills during the week: via the teamwork on modeling and simulating the problems; through the final team presentations made at the end of the week; and in writing the final reports that are produced. Training activities also include numerical simulations and the preparation of a final report outlining their discoveries. These skills are put to use and consolidated the following week at MPI, where industrial participants present immediate modeling challenges facing their industries, on which academic participants (faculty, postdocs, and the Ph.D. students from GSMMC) work. Significant progress on the industrial problems is usually made, and Ph.D. student participants take the lead in presenting the findings to the industrial participants from industry in final presentations at the week's end. In addition to building their skillsets and resumes, student participants are exposed to valuable networking interactions with a range of industrial participants.The GSMMC-MPI program is designed to integrate interdisciplinary research and education for graduate students. The GSMMC is focused on graduate student education and training: its chief intellectual merit lies in the development and analysis, by students, of the mathematical models for the problems presented. Problems are highly interdisciplinary, presenting students with a novel intellectual challenge. With the preparatory training provided by the GSMMC, students are ready for the more open-ended, research-level environment of MPI. The questions posed at MPI challenge participants to design new ways of modeling and analyzing industrial mathematics problems in emerging areas of technology. Mathematical modeling, analytical techniques, numerical simulations, and data analysis must all be used effectively. The collaborative approach to problem solving, which brings together mathematicians ranging from graduate students to experienced faculty, is central to the structure of MPI and provides significant additional training to graduate students, while promoting effective scientific communication. Full details for the Camp may be found at https://www.mathsci.udel.edu/events/conferences/gsmmc-2021, and for MPI at https://mpi2021.w3.uvm.edu/.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.

第16届年度研究生数学建模营（GSMMC）将于2021年6月9日至12日在特拉华州大学举行，随后的一周是第36届年度工业数学问题（MPI）研讨会，2021年6月14日至18日在佛蒙特大学举行。 GSMMC是一个指导，解决问题的研讨会，在小团队的博士。来自美国各地的学生通过由教师或经验丰富的博士后导师提出的真实世界问题的成功数学建模进行指导。在认真的指导下，学生参与者在一周内建立了他们的建模，团队合作和演示技巧：通过建模和模拟问题的团队合作;通过在周末进行的最终团队演示;并编写最终报告。培训活动还包括数值模拟和编写概述其发现的最后报告。 这些技能将在接下来的一周在MPI上得到使用和巩固，在那里，工业参与者提出了他们所在行业面临的直接建模挑战，学术参与者（教师，博士后和博士）将在此基础上进行建模。GSMMC的学生）工作。在工业问题上通常会取得重大进展，学生参与者在周末的最终演讲中带头向行业参与者展示研究结果。除了建立自己的技能和简历，学生参与者接触到有价值的网络互动与一系列的行业参与者。GSMMC-MPI计划旨在整合跨学科的研究和教育的研究生。GSMMC专注于研究生教育和培训：其主要智力价值在于学生对所提出问题的数学模型的开发和分析。问题是高度跨学科的，给学生带来了新的智力挑战。通过GSMMC提供的预备培训，学生已经为MPI的更开放的研究级环境做好了准备。MPI提出的问题挑战参与者设计建模和分析新兴技术领域工业数学问题的新方法。数学建模、分析技术、数值模拟和数据分析都必须有效地使用。协作解决问题的方法，汇集了从研究生到经验丰富的教师的数学家，是MPI结构的核心，并为研究生提供了重要的额外培训，同时促进了有效的科学交流。营地的全部细节可以在https：//www.mathsci.udel.edu/events/conferences/gsmmc-2021上找到，而MPI在https://mpi2021.w3.uvm.edu/.This上的奖项反映了NSF的法定使命，并被认为值得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来支持。