The Annual Data Institute Conference

年度数据研究所会议

• 批准号: 1841307
• 负责人: James Wilson
• 金额: $ 1.5万
• 依托单位: University of San Francisco
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-03-15 至 2020-02-29
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1841307&HistoricalAwards=false
• 关键词: Annual; Data; Institute; Conference

From March 10th - 12th, 2019, the Data Institute at the University of San Francisco (USF) will host the Data Institute Conference at the downtown campus of USF in San Francisco. In the past decade the explosion of available data has fundamentally changed the way researchers across disciplines approach problems. Industry is experiencing a similar disruption as data driven decision-making is driving innovation toward new skills and roles that are often coined "data science." While academic researchers have traditionally been the center of innovation and research, industry is pouring significant resources into developing solutions to many of these same problems. This isolated and paralleled approach to finding solutions is ripe for a conference dedicated to exchanging ideas across this traditional divide. This conference aims to draw leaders of data science in industry and academia to explore the latest theoretical advances and technological applications in data science to promote the next generation of cross-disciplinary research. This conference will make an equally important impact to the greater scientific community with a focus on recruiting and increasing diversity in data science with attendees that are not traditionally represented in STEM fields. This proposal is devoted to the support of students, post-doctoral scholars, and early-career researchers, especially those from underrepresented groups. Data Science is a rapidly developing field with fluid boundaries but largely contains research areas in the statistical, mathematical and computational sciences. This conference will bring together both junior and senior researchers from industry and academia to exchange ideas on the recent advances of data science in these areas. Tracks include network analysis, experimental design, high dimensional signal processing and machine learning, as well as tracks dedicated to recent applications of these statistical topics to deep learning, social good, and marketing. There is a clear need for this novel approach to a conference in data science. Most conferences in this space have attendees numbering in the thousands and are either very broad with dozens of parallel sessions or focused on a single topic in data science. This will be of moderate size (~350) with three or fewer parallel sessions at any given time with many overlapping research threads so as to maximize the opportunity to collaborate and establish new research between academics and industry practitioners. To learn more about the Data Institute Conference, please visit the website: https://www.sfdatainstitute.org/.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.

2019年3月10日至12日，旧金山弗朗西斯科大学（USF）数据研究所将在旧金山弗朗西斯科市中心的USF校园举办数据研究所会议。 在过去的十年中，可用数据的爆炸性增长从根本上改变了跨学科研究人员解决问题的方式。行业正在经历类似的颠覆，因为数据驱动的决策正在推动创新，以实现新的技能和角色，这些技能和角色通常被称为“数据科学”。“虽然学术研究人员传统上一直是创新和研究的中心，但工业界正在投入大量资源来开发解决许多相同问题的解决方案。这种孤立和不稳定的方法来寻找解决方案，是一个成熟的会议，致力于交流思想，跨越这一传统的鸿沟。本次会议旨在吸引工业界和学术界的数据科学领导者，探讨数据科学的最新理论进展和技术应用，以促进下一代跨学科研究。此次会议将对更大的科学界产生同样重要的影响，重点是招募传统上不属于STEM领域的与会者并增加数据科学的多样性。该提案致力于支持学生，博士后学者和早期职业研究人员，特别是那些来自代表性不足的群体。数据科学是一个快速发展的领域，具有流体边界，但主要包含统计，数学和计算科学的研究领域。本次会议将汇集来自工业界和学术界的初级和高级研究人员，就这些领域的数据科学最新进展交换意见。轨道包括网络分析，实验设计，高维信号处理和机器学习，以及轨道致力于这些统计主题的深度学习，社会公益和营销的最新应用。显然，数据科学会议需要这种新颖的方法。这个领域的大多数会议都有数千名与会者，要么非常广泛，有几十个平行会议，要么专注于数据科学中的一个主题。这将是中等规模（~350），在任何给定的时间有三个或更少的平行会议，有许多重叠的研究线程，以最大限度地提高合作的机会，并建立学者和行业从业者之间的新研究。要了解有关数据研究所会议的更多信息，请访问网站：https://www.sfdatainstitute.org/.This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。