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.

从2019年3月10日至12日，旧金山大学（USF）的数据研究所将在旧金山USF市区校园举办数据学院会议。 在过去的十年中，可用数据的爆炸率从根本上改变了跨学科的研究人员处理问题的方式。行业正遇到类似的破坏，因为数据驱动的决策正在推动经常创造的“数据科学”的新技能和角色的创新。尽管传统上，学术研究人员一直是创新和研究的中心，但行业仍在为许多相同问题开发解决方案。对于一个专门在这种传统鸿沟中交换思想的会议，这种孤立和平行的方法是找到解决方案的方法。这次会议旨在吸引行业和学术界数据科学领导者，以探讨数据科学中最新的理论进步和技术应用，以促进下一代跨学科研究。这次会议将对更大的科学界产生同样重要的影响，重点是招募和增加数据科学的多样性，而这些参与者传统上在STEM领域中并不代表。该建议致力于支持学生，博士后学者和早期研究人员，尤其是来自代表性不足的研究人员。数据科学是一个迅速发展的领域，具有流体边界，但在很大程度上包含统计，数学和计算科学中的研究领域。这次会议将汇集来自行业和学术界的初级和高级研究人员，以交流有关这些领域数据科学最新进展的想法。轨道包括网络分析，实验设计，高维信号处理和机器学习，以及专门针对这些统计主题到深度学习，社会善良和营销的最新应用的轨道。显然需要这种新颖的数据科学会议方法。这个领域的大多数会议都有成千上万的参与者编号，并且要么非常广泛，要么有数十个并行会议，要么集中在数据科学领域的单个主题上。这将是中等大小（〜350）的，在任何给定时间，都有三个或更少的平行课程，并有许多重叠的研究线程，以最大程度地利用学者与行业从业者之间的合作和建立新的研究机会。要了解有关数据学院会议的更多信息，请访问网站：https：//www.sfdatainstitute.org/.This奖奖反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛影响的审查标准通过评估来获得支持的。