NSF Student Travel Grant for the 2019 ACM Conference on Embedded Networked Sensor Systems (ACM SenSys 2019)

2019 年 ACM 嵌入式网络传感器系统会议 (ACM SenSys 2019) 的 NSF 学生旅费补助金

• 批准号: 1945574
• 负责人: Lu Su
• 金额: $ 1.84万
• 依托单位: SUNY at Buffalo
• 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: 2019-10-01 至 2020-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1945574&HistoricalAwards=false
• 关键词: NSF; Student; Travel; Grant; 2019

The 17th Association for Computing Machinery (ACM) Conference on Embedded Networked Sensor Systems (ACM SenSys 2019) is a premier symposium with a highly selective single-track technical program dedicated to systems issues of networked sensing and actuation, broadly defined. Systems of smart sensors and actuators have a wide array of application areas such as cyber-physical systems, vehicular networks, and smart grid. This award supports graduate and undergraduate students who will substantially benefit from attending this conference but have limited foreign travel funds. Priority will be given to students from under-represented groups (women, minorities, and those with disabilities), authors without other funding, and first-time attendees. The students will be exposed to the state-of-the-art developments in the field and will have the opportunity to interact with peers from institutions worldwide, participate in a mentoring event, meet with leading researchers, and participate in discussions that are likely to shape their future and that of the field.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.

嵌入式网络传感器系统（ACM Sensys 2019）的第17届计算机机械协会（ACM）会议是一场首要的研讨会，具有高度选择性的单轨技术计划，该计划专门针对网络感应和动力的系统问题，广泛定义。 智能传感器和执行器的系统具有广泛的应用领域，例如网络物理系统，车辆网络和智能电网。该奖项为研究生和本科生提供支持，他们将在参加这次会议但外国旅行资金有限的情况下受益匪浅。将优先考虑来自代表性不足的团体（妇女，少数民族和残疾人），没有其他资金的作者以及首次与会者的学生。 学生将接触到该领域的最先进的发展，并有机会与来自世界各地机构的同伴互动，参加指导活动，与领先的研究人员会面，并参与讨论的讨论，这些讨论可能会影响其未来和领域的未来。该奖项通过评估NSF的法定任务和众所周知的范围来反映出该奖项的知识群体的范围，该奖项被视为众所周知的范围。