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).

首届美日大数据研究全球合作研讨会汇集了来自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。研讨会为两国的参与者提供了机会，以确定共同的研究兴趣，利用资源和专业知识加速智能和互联社区、网络物理系统、人工智能和机器学习的进步。研讨会包括两个轨道，以支持广泛的参与：轨道1，为具有先前合作经验和推动该领域发展的巨大潜力的参与者；轨道2，对于那些没有先前合作经验的人，他们可能会从国际合作提供的多样化培训环境中受益匪浅。研讨会的成果将通过一份报告传播，该报告描述了研讨会期间讨论的主要战略领域、关键研究机会和合作方案，从而使更广泛的研究界受益。本次研讨会与2017年IEEE分布式计算系统国际会议（ICDCS）同时举行。这项合作建立在美国国家科学基金会（NSF）与日本科学技术振兴机构（JST）之前的合作基础上。智能和互联社区、网络物理系统、人工智能和机器学习等领域既存在自身的智力挑战，也存在相互交叉的挑战和机遇。具体来说，全球范围内不断增长的数据、传感器、云和边缘计算以及网络带来的挑战和机遇需要国际研究合作。例如，机器学习和人工智能的进步，加上大型传感器网络（如芝加哥的Array of Things和日本的Fujisawa Sustainable Smart Town）的开发和实施，可以使城市规模的数据提高城市和社区的效率、经济繁荣和安全。该研讨会将侧重于超出每个参与者个人能力范围的研究挑战，但通过两国之间的有效合作，这些挑战将成为可行的目标。当双方有相似的兴趣，但具有互补的专业知识和技能时（例如，来自不同但相关的领域，如上述例子），这可以实现。