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TRIPODS: Transdisciplinary Research Institute for Advancing Data Science (TRIAD)

TRIPODS：推进数据科学跨学科研究所 (TRIAD)

基本信息

批准号：
1740776
负责人：
Xiaoming Huo
金额：
$ 150万
依托单位：
Georgia Tech Research Corporation
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2017
资助国家：
美国
起止时间：
2017-09-01 至 2024-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1740776&HistoricalAwards=false
关键词：
TRIPODS Transdisciplinary Research Institute Advancing

项目摘要

This project creates the Transdisciplinary Research Institute for Advancing Data Science (TRIAD) at the Georgia Institute of Technology. TRIAD aims to integrate research and education in mathematical, statistical, and algorithmic foundations for data science. Analysis of massive, dynamic, noisy, and complex data arising in virtually every sphere of human activity is a pressing challenge of our time, and an area of great importance for its economic and societal impact. TRIAD will address the growing challenges in establishing the foundations of data science, much of which lies at the intersection of computer science, statistics, and mathematics. TRIAD's intellectual focus is to design and build transdisciplinary research programs that provide an enabling and cross-fertilizing platform of ideas and stakeholders (including theoreticians/scientists from domain sciences and users of technology). TRIAD hosts focused working groups, national and international workshops, and organized innovation labs. Participants include senior, mid-career, and junior faculty members, postdoctoral fellows, graduate and senior undergraduate students, and data science practitioners at large. All TRIAD activities involve interdisciplinary personnel from the three foundational disciplines. TRIAD deploys information technology and communication infrastructure to quickly and efficiently disseminate its research and activities, while the research community at large can easily access and comment/critique TRIAD's choice of research programs and topics. The institute aims to create an intellectual atmosphere that connects theoreticians and practitioners, scientists, and engineers from across the nation and worldwide on a regular basis.TRIAD enriches careers of participants ranging from undergraduate students to senior researchers from around the nation. Postdoctoral fellows and graduate students are introduced to collaborative research in the institute activities and through workshops. TRIAD makes prudent efforts to reach out to diverse communities, including participants from smaller colleges and institutions serving under-represented minorities. TRIAD actively engages in outreach through public lectures, press releases, and dissemination via other internet channels. TRIAD works with associated professional societies to provide stimulus to data-science-related initiatives. Additional activities (such as customized workshops) will combine interactive projects and field trips to acquaint undergraduate and/or high school students from all over the U.S. with data-science-related techniques and the themes of TRIAD's year-long programs. Every effort will be made to make products and lectures available online and to enable remote participation. Funds for the project come from CISE Computing and Communications Foundations and MPS Division of Mathematical Sciences.

该项目在格鲁吉亚理工学院创建了推进数据科学的跨学科研究所（TRIAD）。 TRIAD旨在整合数据科学的数学，统计和算法基础的研究和教育。分析人类活动几乎每个领域中产生的大量、动态、嘈杂和复杂的数据是我们这个时代的一个紧迫挑战，也是一个对经济和社会影响非常重要的领域。TRIAD将解决建立数据科学基础方面日益增长的挑战，其中大部分位于计算机科学，统计学和数学的交叉点。TRIAD的智力重点是设计和建立跨学科的研究计划，为思想和利益相关者（包括领域科学的理论家/科学家和技术用户）提供一个使能和跨学科的平台。TRIAD主办重点工作组，国家和国际研讨会，并组织创新实验室。参与者包括高级，职业中期和初级教师，博士后研究员，研究生和高年级本科生以及数据科学从业者。所有三合会活动涉及来自三个基础学科的跨学科人员。TRIAD部署信息技术和通信基础设施，以快速有效地传播其研究和活动，而广大的研究界可以很容易地访问和评论/批评TRIAD的研究计划和主题的选择。该研究所旨在创造一种学术氛围，定期连接来自全国和世界各地的理论家和实践者，科学家和工程师。TRIAD丰富了来自全国各地的参与者，从本科生到高级研究员的职业生涯。博士后研究员和研究生通过研究所活动和讲习班进行合作研究。TRIAD谨慎地努力接触不同的社区，包括来自较小的学院和为代表性不足的少数民族服务的机构的参与者。三合会通过公开讲座、新闻稿和通过其他互联网渠道传播积极参与外联活动。TRIAD与相关的专业协会合作，为数据科学相关的举措提供激励。其他活动（如定制研讨会）将结合联合收割机互动项目和实地考察，以熟悉来自美国各地的本科生和/或高中生与数据科学相关的技术和TRIAD长达一年的课程的主题。将尽一切努力在网上提供产品和讲座，并使远程参与成为可能。该项目的资金来自CISE计算和通信基金会以及MPS数学科学部。