WORKSHOP: Doctoral Consortium at HCOMP 2017

研讨会:HCOMP 2017 博士联盟

基本信息

  • 批准号:
    1748375
  • 负责人:
  • 金额:
    $ 2.19万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2017
  • 资助国家:
    美国
  • 起止时间:
    2017-08-01 至 2018-07-31
  • 项目状态:
    已结题

项目摘要

This is funding to support participation of at least 8 promising doctoral students from U.S. educational institutions at a Doctoral Consortium (workshop)along with distinguished research faculty, to be held in conjunction with the 5th AAAI Conference on Human Computation & Crowdsourcing (HCOMP 2017), which will take place October 24-26 in Quebec City, Canada, and which is sponsored by the Association for the Advancement of Artificial Intelligence. HCOMP is the premier venue for disseminating the latest research findings on crowdsourcing and human computation. While artificial intelligence (AI) and human-computer interaction (HCI) represent traditional mainstays of this cross-disciplinary conference, HCOMP believes strongly in inviting, fostering, and promoting broad, interdisciplinary research. The diverse disciplines the field draws upon, and contributes to, range from human-centered qualitative studies and HCI design, to computer science and artificial intelligence, economics and the social sciences, all the way to digital humanities, policy, and ethics. More information about the conference is available online at http://www.humancomputation.com/2017/. The Doctoral Consortium will be a research-focused full day meeting that immediately precedes the conference, on October 23. It will enhance the scientific workforce in this emerging research area by nurturing a group of promising young investigators interested in human computation and crowdsourcing. The award will also allow these young researchers to attend the HCOMP 2017 conference, thereby allowing them: to interact with other researchers and conference events; to learn of potential career paths within academia and industry; to access an international network of researchers who can support their professional development; and to observe the interdisciplinary nature, diversity and interrelationships of research in human computation. The Doctoral Consortium Chairs will select up to 6 additional distinguished researchers to serve as faculty mentors; this group also will serve as the review committee for student applications. Students will be accepted based on a paper giving an overview of the student's dissertation research, an explanation of why the student wants to participate in the Doctoral Consortium, a CV, and a letter of support from the student's advisor. The organizers will give preference to students who are most in need of mentoring and joining a peer group. Moreover, the organizers will promote diversity among the selected students by selecting no more than one or two students from any one school, and by prioritizing the selection of women and underrepresented minorities. In accordance with CISE policy, NSF funds will only be used to support students from U.S.-based educational institutions.The full-day Doctoral Consortium will include activities to guide the research of these promising young researchers. The Consortium will allow participants to interact with established researchers and with other students, through presentations, question-answer sessions, panel discussions, and invited presentations. Each participant will give a short presentation on their research and will receive feedback from at least one faculty mentor and from fellow students. The feedback will be geared toward helping the student participants understand and articulate how their research is positioned relative to other work on human computation and crowdsourcing. The feedback will also address whether the students' topics are adequately focused for thesis research projects, whether their methods are correctly chosen and applied, and whether their results are being appropriately analyzed and presented. Activities led by the faculty will include a panel discussion to give students more information about the process and lessons of research and life in academia and industry. To further integrate the Doctoral Consortium participants into the conference itself, students will have a chance to present their work as posters in an interactive poster session and their papers will be posted online on the workshop webpage. These activities will benefit the participants by offering each fresh perspectives and comments on their work from researchers outside their own institution, both from faculty and other students; providing a supportive setting for mutual feedback on participants' current research and guidance on future research directions; and enabling participants to form a cohort of new researchers.
这笔资金将支持来自美国教育机构的至少8名有前途的博士生与杰出的研究人员一起参加博士联盟(研讨会),该研讨会将与第五届AAAI人类计算和众包会议(HCOMP 2017)一起举行,该会议将于10月24日至26日在加拿大魁北克市举行,由人工智能促进协会赞助。HCOMP是传播关于众包和人类计算的最新研究成果的主要场所。虽然人工智能(AI)和人机交互(HCI)是这一跨学科会议的传统支柱,但HCOMP坚信邀请、培养和促进广泛的跨学科研究。从以人为中心的定性研究和人机交互设计,到计算机科学和人工智能、经济学和社会科学,一直到数字人文、政策和伦理,该领域所借鉴和贡献的学科多种多样。有关会议的更多信息,请访问http://www.humancomputation.com/2017/。在10月23日的会议之前,博士联盟将举行一个以研究为重点的全天会议。它将通过培养一批对人类计算和众包感兴趣的有前途的年轻研究人员,加强这一新兴研究领域的科学劳动力。该奖项还将允许这些年轻的研究人员参加HCOMP 2017会议,从而使他们能够:与其他研究人员和会议活动互动;了解学术界和工业界潜在的职业发展道路;访问国际研究人员网络,支持他们的专业发展;并观察人类计算研究的跨学科性质、多样性和相互关系。博士联盟主席将选择最多6名杰出的研究人员作为教师导师;该小组还将担任学生申请的审查委员会。学生将根据一篇论文被接受,该论文概述了学生的论文研究,解释了学生为什么要参加博士联盟,简历和学生导师的支持信。组织者将优先考虑最需要指导和加入同伴小组的学生。此外,组织者还将促进入选学生的多样性,从每一所学校选拔不超过一到两名学生,并优先选拔女性和代表性不足的少数族裔。根据CISE政策,NSF基金将只用于支持来自美国教育机构的学生。全天的博士联盟将包括指导这些有前途的年轻研究人员的研究活动。该联盟将允许参与者通过演讲、问答环节、小组讨论和邀请演讲,与已有的研究人员和其他学生进行互动。每位参与者将对他们的研究做一个简短的介绍,并将从至少一位教师导师和同学那里获得反馈。反馈将有助于学生参与者理解和表达他们的研究相对于其他人类计算和众包工作的定位。反馈还将涉及学生的主题是否充分关注论文研究项目,他们的方法是否正确选择和应用,以及他们的结果是否得到适当的分析和呈现。由教师领导的活动将包括小组讨论,让学生更多地了解学术界和工业界的研究过程和经验教训。为了进一步将博士联盟的参与者融入会议本身,学生将有机会在互动海报环节以海报的形式展示他们的作品,他们的论文将在研讨会网页上在线发布。这些活动将使参与者受益,为他们自己机构以外的研究人员,包括教师和其他学生,提供对他们工作的新鲜观点和评论;为参与者提供一个相互反馈当前研究和指导未来研究方向的支持性环境;并使参与者形成一个新的研究团队。

项目成果

期刊论文数量(0)
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科研奖励数量(0)
会议论文数量(0)
专利数量(0)

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Brent Hecht其他文献

Early LLM-based Tools for Enterprise Information Workers Likely Provide Meaningful Boosts to Productivity
早期为企业信息工作者提供的基于法学硕士的工具可能会显着提高生产力
  • DOI:
  • 发表时间:
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Alexia Cambon;Brent Hecht;Donald Ngwe;Sonia Jaffe;Amy Heger;Mihaela Vorvoreanu;Sida Peng;Jake Hofman;Alex Farach;Margarita Bermejo;Eric Knudsen;James Bono;Hardik Sanghavi;S. Spatharioti;David M. Rothschild;Daniel G. Goldstein;Eirini Kalliamvakou;Peter Cihon;Mert Demirer;Michael Schwarz;J. Teevan
  • 通讯作者:
    J. Teevan
LLM-based and Retrieval-Augmented Control Code Generation
基于 LLM 和检索增强的控制代码生成
  • DOI:
  • 发表时间:
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Alexia Cambon;Brent Hecht;Donald Ngwe;Sonia Jaffe;Amy Heger;Mihaela Vorvoreanu;Sida Peng;Jake Hofman;Alex Farach;Margarita Bermejo;Eric Knudsen;James Bono;Hardik Sanghavi;S. Spatharioti;David M. Rothschild;Daniel G. Goldstein;Eirini Kalliamvakou;Peter Cihon;Mert Demirer;Michael Schwarz;J. Teevan
  • 通讯作者:
    J. Teevan

Brent Hecht的其他文献

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{{ truncateString('Brent Hecht', 18)}}的其他基金

Workshop: Confronting and Mitigating the Negative Broader Impacts of Computing
研讨会:面对和减轻计算的更广泛的负面影响
  • 批准号:
    1841993
  • 财政年份:
    2018
  • 资助金额:
    $ 2.19万
  • 项目类别:
    Standard Grant
CAREER: Understanding and Addressing Geographic Inequalities in Location-Aware Technologies
职业:理解和解决位置感知技术中的地理不平等
  • 批准号:
    1707296
  • 财政年份:
    2016
  • 资助金额:
    $ 2.19万
  • 项目类别:
    Continuing Grant
CAREER: Understanding and Addressing Geographic Inequalities in Location-Aware Technologies
职业:理解和解决位置感知技术中的地理不平等
  • 批准号:
    1552955
  • 财政年份:
    2016
  • 资助金额:
    $ 2.19万
  • 项目类别:
    Continuing Grant
CHS: Small: Collaborative Research: Human-Centered Semantic Relatedness
CHS:小型:协作研究:以人为中心的语义相关性
  • 批准号:
    1707319
  • 财政年份:
    2016
  • 资助金额:
    $ 2.19万
  • 项目类别:
    Standard Grant
III: Small: Collaborative Research: Automatically Generating Contextually-Relevant Visualizations
III:小:协作研究:自动生成上下文相关的可视化
  • 批准号:
    1702440
  • 财政年份:
    2016
  • 资助金额:
    $ 2.19万
  • 项目类别:
    Standard Grant
CHS: Small: Collaborative Research: Human-Centered Semantic Relatedness
CHS:小型:协作研究:以人为中心的语义相关性
  • 批准号:
    1526988
  • 财政年份:
    2015
  • 资助金额:
    $ 2.19万
  • 项目类别:
    Standard Grant
III: Small: Collaborative Research: Automatically Generating Contextually-Relevant Visualizations
III:小:协作研究:自动生成上下文相关的可视化
  • 批准号:
    1421655
  • 财政年份:
    2014
  • 资助金额:
    $ 2.19万
  • 项目类别:
    Standard Grant

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