NSF Student Travel Grant for 2020 IEEE North American School for Information Theory(NASIT)
NSF Student Travel Grant for 2020 IEEE North American School for Information Theory(NASIT)
批准号:
2024158
负责人:
Yu Xiang
金额:
$1.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-03-15 至 2023-02-28
中文摘要
2020年IEEE北美信息理论学院(NASIT '20)将于2020年7月8日至7月10日在加拿大温哥华的不列颠哥伦比亚省大学举行。该奖项支持美国研究生就读该校的旅费。这些参与者通过向资深同事学习,在海报会议上展示自己的研究成果,扩大与社区的联系,以及磨练专业发展技能而受益。IEEE北美信息理论学院是IEEE信息理论学会的年度活动,今年将是该学院运营的第七个年头。学校提供了一个支持性的环境,为学习和长期的未来科学合作奠定了基础。该学院为研究生提供现代信息理论所支持的数学,工程和计算机科学方面的互动教育,并为学生提供与来自学术界和工业界的高级研究人员会面和学习的机会。学生参与者在海报会议上展示自己的研究成果。IEEE信息理论学会的“Padovani讲座”在学校举行。该奖项反映了NSF的法定使命,并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,被认为值得支持。
英文摘要
The 2020 IEEE North American School for Information Theory (NASIT ’20) will be held at the University of British Columbia in Vancouver, Canada, from July 8th to July 10th, 2020. This award supports travel expenses for US graduate students attending the school. These participants benefit by learning from senior colleagues, presenting their own research in poster sessions, and expanding their network with their community, as well as honing professional development skills.The IEEE North American School for Information Theory is an annual event of the IEEE Information Theory Society; this will be the school's seventh year of operation. The School provide a supportive environment where foundations for learning and long-term future scientific collaborations are established. The School delivers interactive education for graduate students in the mathematical, engineering, and computer science aspects espoused by modern information theory, and offers students the opportunity to meet with and learn from senior researchers from academia and industry who present long-format tutorials. Student participants present their own research results in poster sessions. The IEEE Information Theory Society “Padovani Lecture” is delivered at the school.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.
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