1st US-Japan Workshop Enabling Global Collaborations in Big Data Research; June, 2017, Atlanta, GA

第一届美日研讨会促进大数据研究的全球合作；

• 批准号: 1741034
• 负责人: Calton Pu
• 金额: $ 2.5万
• 依托单位: Georgia Tech Research Corporation
• 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: 2017-05-15 至 2018-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1741034&HistoricalAwards=false
• 关键词: 1st; US; Japan; Workshop; Enabling

The 1st US-Japan Workshop Enabling Global Collaborations in Big Data Research brings together researchers from the United States (U.S.) and Japan to discuss experiences, challenges, and opportunities in international research collaborations. The workshop provides opportunities for participants from both countries to identify mutual research interests that leverage resources and expertise to accelerate advancements in smart and connected communities, cyber-physical systems, artificial intelligence, and machine learning. The workshop includes two tracks to support a broad range of participation: track 1, for participants with prior collaboration experience and significant potential to advance the field; and track 2, for those without prior collaboration experience who may benefit significantly from the diverse training environments afforded by international collaborations. The outcomes of the workshop will be disseminated through a report describing the main strategic areas, key research opportunities, and collaboration scenarios discussed during the workshop, thereby benefiting a broader research community. The workshop is co-located with the 2017 IEEE International Conference on distributed Computing Systems (ICDCS). This engagement builds upon prior National Science Foundation (NSF)-Japan Science and Technology Agency (JST) collaborations.The areas of smart and connected communities, cyber-physical systems, artificial intelligence, and machine learning present intellectual challenges of their own, as well as challenges and opportunities at their intersections. Specifically, the challenges and opportunities created by growing data, sensors, cloud and edge computing, and networking at a global scale call for international research collaborations. For example, advances in machine learning and artificial intelligence, paired with the development and implementation of large sensor networks (e.g., Array of Things in Chicago and Fujisawa Sustainable Smart Town in Japan) can enable city-scale data to improve efficiency, economic prosperity, and security in our cities and communities. The workshop will focus on research challenges that are beyond the individual reach of each participant, but that become feasible goals with effective collaboration between the two countries. This can be achieved when both sides share similar interests, but with complementary expertise and skills, (e.g., from different but related areas such as the examples mentioned above).

在大数据研究中实现全球合作的第一届美国日本研讨会汇集了美国（美国）和日本的研究人员，讨论国际研究合作的经验，挑战和机遇。该研讨会为两国的参与者提供了机会，以确定利用资源和专业知识的共同研究兴趣，以加快智能和连接社区，网络物理系统，人工智能和机器学习的进步。该研讨会包括两条曲目，以支持广泛的参与：轨道1，适用于具有先前协作经验的参与者，并且有巨大的潜力推进了该领域；对于那些没有事先合作经验的人，他们可能会从国际合作提供的潜水员培训环境中受益匪浅。研讨会的结果将通过一份报告来传播，该报告描述了讲习班期间讨论的主要战略领域，关键研究机会和协作场景，从而使更广泛的研究社区受益。该研讨会与2017年IEEE国际分布式计算系统会议（ICDC）共同分居。这种参与基于现有国家科学基金会（NSF） - 日本科学技术局（JST）合作。智能和互联社区，网络物理系统，人工智能和机器学习的领域面临着自己的智力挑战，以及交叉点的挑战和机遇。具体而言，通过不断增长的数据，传感器，云和边缘计算以及在全球范围内进行网络的挑战和机会，要求国际研究合作。例如，机器学习和人工智能的进步与大型传感器网络的开发和实施（例如，芝加哥和日本的富吉岛可持续智能小镇）的开发和实施可以促进城市规模的数据，以提高我们的城市和社区的效率，经济繁荣和安全性。研讨会将重点关注每个参与每个参与的个人范围之外的研究挑战，但这是两国之间有效合作的可行目标。当双方共享相似的兴趣，但具有完整的专业知识和技能（例如，来自不同但相关的领域，例如上述示例）时，这可以实现。