课题基金 / 基金详情

IGERT: From Data to Solutions: A New PhD Program in Transformational Data & Information Sciences Research and Innovation

IGERT: From Data to Solutions: A New PhD Program in Transformational Data & Information Sciences Research and Innovation
IGERT:从数据到解决方案:一个新的转型数据博士项目
批准号:
1144854
负责人:
Julia Hirschberg
金额:
$300.0万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-07-01 至 2018-06-30

项目摘要

项目成果

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中文摘要
翻译
这个综合研究生教育和研究培训(IGERT)为博士生提供独特的跨学科培训,从大量收集的数据中提取有用的信息。消费者的意见,疾病及其症状的信息,以及社交网站上的突发信息,使我们能够以以前未知的规模收集信息。然而,只有当我们能够从中提取信息时,这样的大数据才有用。哥伦比亚大学和纽约市立大学与阿根廷和巴西的国际合作伙伴合作,提议对学生进行跨学科培训,以理解大数据。来自计算机科学、电子工程、心理学和统计学的研究人员将与生物医学信息学、商业和新闻学合作,教育下一代信息科学家解决现实世界的问题。我们将训练学生从多种数据类型中提取信息。文字、视频、音频?并让他们熟悉各种各样的技术,以便从一个Youtube、维基百科、Facebook和Twitter正在取代报纸、百科全书、电视和消费者调查作为日常信息来源的世界中理解信息。更广泛的影响:基于工作室学习概念的课程将整合商业,新闻和生物医学信息学的技术。在来自大公司、主要研究实验室和小型初创公司的顾问的帮助下,该计划将鼓励IGERT学员申请专利,并将他们的研究应用于社会。第二个目标是通过强调现实世界的应用、支持性的环境和多样化的教师榜样,吸引更多不同类型的学生学习信息科学。拟议的指导和职业发展活动将有助于留住这些多样化的人口,并为他们未来的职业生涯做好准备。IGERT是一项nsf范围内的计划,旨在满足教育美国博士科学家和工程师的挑战,他们具有跨学科背景,所选学科的深厚知识,以及未来职业需求所需的技术,专业和个人技能。该项目旨在建立研究生教育和培训的新模式,在一个超越传统学科界限的合作研究的肥沃环境中,让学生了解研究转化为社会效益创新的过程。
英文摘要
This Integrative Graduate Education and Research Traineeship (IGERT) provides Ph.D. students with the unique interdisciplinary training necessary to extract useful information from vast amounts of collected data. Consumer opinions, information on disease and its symptoms, and breaking information on social websites allow us to gather information on a scale previously unknown. However, such big data is useful only if we can extract information from it. Columbia and CUNY, in collaboration with international partners in Argentina and Brazil, propose the interdisciplinary training of students in making sense of big data. Researchers from Computer Science, Electrical Engineering, Psychology, and Statistics will partner with Biomedical Informatics, Business and Journalism, to educate the next generation of information scientists in solving real world problems. We will train students to extract information from multiple data types ? text, video, audio ? and familiarize them with a wide range of techniques for making sense of information from a world in which Youtube, Wikipedia, Facebook, and Twitter are supplanting newspapers, encyclopedias, television, and consumer surveys as everyday sources of information. Broader Impacts: A curriculum based upon the concept of studio learning will integrate techniques from Business, Journalism, and Biomedical Informatics. Aided by advisors from large corporations, major research labs, and small start-up companies, the program will encourage IGERT trainees to pursue patents, and to apply their research in society. A second goal will be attracting more diverse students to information sciences by emphasizing real world applications, a supportive environment, and diverse faculty role models. The mentoring and career development activities proposed will help to retain this diverse population and prepare them for their future careers. IGERT is an NSF-wide program intended to meet the challenges of educating U.S. Ph.D. scientists and engineers with the interdisciplinary background, deep knowledge in a chosen discipline, and the technical, professional, and personal skills needed for the career demands of the future. The program is intended to establish new models for graduate education and training in a fertile environment for collaborative research that transcends traditional disciplinary boundaries, and to engage students in understanding the processes by which research is translated to innovations for societal benefit.
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EAGER: Identifying and Producing Code-Switching in Languages from Spoken, Lexical and Socio-linguistic Features
  • 批准号:
    2327564
  • 项目类别:
    Standard Grant
  • 资助金额:
    $10.89万
  • 财政年份:
    2023
  • 负责人:
    Julia Hirschberg
  • 依托单位:
RI: Small: Creating Text-to-Speech Synthesis for Low Resource Languages
  • 批准号:
    1717680
  • 项目类别:
    Standard Grant
  • 资助金额:
    $50.0万
  • 财政年份:
    2017
  • 负责人:
    Julia Hirschberg
  • 依托单位:
EAGER: Creating Speech Synthesizers for Low Resource Languages
  • 批准号:
    1548092
  • 项目类别:
    Standard Grant
  • 资助金额:
    $15.0万
  • 财政年份:
    2015
  • 负责人:
    Julia Hirschberg
  • 依托单位:
Collaborative Research: CI-P: Reciprosody - A Repository for Prosodically Annotated Material
  • 批准号:
    1205450
  • 项目类别:
    Standard Grant
  • 资助金额:
    $2.5万
  • 财政年份:
    2012
  • 负责人:
    Julia Hirschberg
  • 依托单位:
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
Data-driven Recommendation System Construction of an Online Medical Platform Based on the Fusion of Information
Development of a Linear Stochastic Model for Wind Field Reconstruction from Limited Measurement Data
  • 批准号:
    --
  • 项目类别:
    --
  • 资助金额:
    40万元
  • 批准年份:
    2020
  • 负责人:
    Vikrant Gupta
  • 依托单位:
基于Linked Open Data的Web服务语义互操作关键技术
  • 批准号:
    61373035
  • 项目类别:
    面上项目
  • 资助金额:
    77.0万元
  • 批准年份:
    2013
  • 负责人:
    冯志勇
  • 依托单位: