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RTG: Networks: Foundations in Probability, Optimization, and Data Sciences

RTG：网络：概率、优化和数据科学基础

基本信息

批准号：
2134107
负责人：
Amarjit Budhiraja
金额：
$ 232.18万
依托单位：
University of North Carolina at Chapel Hill
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2022
资助国家：
美国
起止时间：
2022-05-15 至 2027-04-30
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2134107&HistoricalAwards=false
关键词：
RTG Networks Foundations Probability Optimization

项目摘要

This research training group (RTG) project will develop a comprehensive training and mentoring program for undergraduate and graduate students and postdoctoral associates, centered around the theme of theory and applications of networks. Faculty team members bring a broad range of expertise to this effort, including stochastic analysis, random discrete structures, discrete and continuous optimization, time series and mathematical statistics, and machine learning. The training of undergraduates, graduate students, and postdocs will contribute to the readying of the workforce in academia and industry in this high-demand field. The engagement of undergraduates in research will form pathways for these students to pursue graduate studies and careers in research. Educational materials and mentoring mechanisms developed as part of RTG activities will have impact on the overall curriculum and training practices in the department as well as on the pan-campus data science initiative. The research intersects with many other fields, such as engineering, social sciences, business, biological and medical sciences, epidemiology, and ecology, and is expected to have impact in these disciplines. Research from the RTG activity will be widely disseminated through posters, meetings, workshops, colloquia, conference proceedings and journal articles. Two key initiatives enabled through this effort are: (1) a set of ten three-week minicourses, taught by international leaders in the field, designed for graduate students and other trainees, which will be broadly disseminated to the community in network science; (2) a weekly ideas seminar that will serve as a central platform to bring undergraduate, graduate, and postdoc trainees together with faculty mentors, and which will serve as a launching pad for undergraduate research projects as well as for identifying topics for Ph.D. dissertations and postdoctoral research. This platform will also provide valuable undergraduate research mentoring opportunities for graduate students and postdocs, and its activities will be instrumental in developing presentation and technical writing abilities of trainees at all levels. Other planned initiatives include (a) a summer boot-camp for incoming graduate trainees; (b) a first year graduate course on research directions in networks that brings together elements of a seminar and an independent reading course; (c) a freshman seminar and a capstone course in networks to form a well-structured pathway for undergraduates, from the freshman year to the senior year, to engage in meaningful and sustained research activity; and (d) a data science lab for organizing undergraduate research activities. The research themes of this RTG will span a broad range of topics, including: development of foundational large network asymptotics using tools from stochastic analysis, percolation theory, and large deviations theory; algorithmic approaches to detection and reconstruction, resource allocation, and computational questions on networks, using tools from applied probability and optimization theory; and approaches to estimation and learning questions using tools from statistics and machine learning.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.

这个研究培训小组(RTG)项目将围绕网络理论和应用这一主题，为本科生和研究生以及博士后助理制定一个全面的培训和指导计划。教员团队成员为这项工作带来了广泛的专业知识，包括随机分析、随机离散结构、离散和连续优化、时间序列和数理统计以及机器学习。对本科生、研究生和博士后的培训将有助于为这一高需求领域的学术界和工业界的劳动力做好准备。本科生参与研究将为这些学生继续研究生学习和从事研究工作提供途径。作为技术指导小组活动的一部分编制的教材和辅导机制将对该部的整体课程和培训做法以及泛校园数据科学倡议产生影响。这项研究涉及许多其他领域，如工程学、社会科学、商学、生物和医学、流行病学和生态学，预计将对这些学科产生影响。将通过海报、会议、讲习班、座谈会、会议记录和期刊文章广泛传播RTG活动的研究成果。通过这一努力实现的两个关键举措是：(1)一套为期三周的迷你课程，由该领域的国际领袖讲授，面向研究生和其他实习生，将在网络科学中广泛传播给社会；(2)每周一次的IDEAS研讨会，将作为一个中心平台，将本科生、研究生和博士后实习生与教师导师聚集在一起，并将作为本科生研究项目的起点，以及确定博士论文和博士后研究的主题。该平台还将为研究生和博士后提供宝贵的本科生研究指导机会，其活动将有助于培养各级受训人员的陈述和技术写作能力。其他计划的举措包括：(A)为即将毕业的学员举办暑期新兵训练营；(B)举办一年级研究生网络研究方向课程，汇集研讨会和独立阅读课程的内容；(C)举办新生研讨会和网络课程，为本科生从大一到大四提供一条结构合理的途径，从事有意义和持续的研究活动；(D)建立数据科学实验室，组织本科生的研究活动。这个RTG的研究主题将涵盖广泛的主题，包括：使用随机分析、渗流理论和大偏差理论的工具发展基础大型网络渐近性；使用应用概率和最优化理论的工具对网络进行检测和重建、资源分配和计算问题的算法方法；以及使用统计学和机器学习工具估计和学习问题的方法。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。