佐治亚理工学院数据科学基金会主办第一所暑期学校
2023-09-28 13:50:03 来源:中国教育在线
近年来,越来越多的中国学子选择留学,那其中佐治亚理工学院数据科学基金会主办第一所暑期学校?本文则针对这个问题,为大家整理了资料,接下来咱们就一起往下了解吧。
The Foundation of Data Science Hosts First Summer School
数据科学基金会主办第一所暑期学校
Sep 12 2019
2019年9月12日
Forty advanced graduate students and post-doctoral researchers from across the country gathered on August 5th at the H. Milton Stewart School of Industrial and Systems Engineering (ISyE) to participate in the first Foundation of Data Science Summer School hosted by Georgia Tech.
来自全国各地的四十名高级研究生和博士后研究人员于8月5日在H.密尔顿斯图尔特工业与系统工程学院(ISYE)集合,参加佐治亚理工学院主持的数据科学暑期学校的第一个基础。
The four-day program was organized by A. Russell Chandler III Professor and Director of Georgia Tech’s Transdisciplinary Research Institute for Advancing Data Science (TRIAD) Xiaoming Huo and Harold R. and Mary Anne Nash Early Career Professor and Assistant Professor Yao Xie. Participants were introduced to a theoretical foundation of data science with a selection of application topics. The emphasis was on the foundational concepts of statistics, optimization, and signal processing, and on the applications of these techniques in developing cross-disciplinary research.
这项为期四天的计划由罗素·钱德勒三世教授和佐治亚理工大学推进数据科学跨学科研究所(三合会)、小明霍和Harold R.、Mary Anne Nash早期职业教授和Yao Xie教授助理组成。参与者被介绍到一个数据科学的理论基础和一系列应用主题。重点是统计、优化和信号处理的基本概念,以及这些技术在跨学科研究中的应用。
“The participating students were exposed to a set of mathematical tools that can potentially be used to derive the fundamental bounds on the performance of various techniques that have been widely adopted in data science,” explained Huo. “While there are many online and physical events (such as bootcamps and summer schools) across the nation that teach data science tools, a summer school that emphasizes the mathematical tools and foundation of data science technique is rare. Therefore, this summer school is unique.”
“参与研究的学生接触了一套数学工具,这些工具有可能被用来推导数据科学中广泛采用的各种技术性能的基本界限,”霍教授解释说。虽然全国各地有许多在线和物理活动(如自助夏令营和暑期学校)教数据科学工具,但是一个强调数学工具和数据科学技术基础的暑期学校很少。因此,这所暑期学校是独一无二的。”
The program was sponsored by TRIAD and the National Science Foundation and featured talks from a wide variety of Georgia Tech faculty including Polo Chau, an associate professor in the School of Computational Science and Engineering, Mark Davenport, an associate professor in the School of Electrical and Computer Engineering, Vladimir Koltchinskii, a professor in the School of Mathematics, and Arkadi Nemirovski, John Hunter Chair and professor in ISyE, in addition to Huo and Xie. Huan Yan (Ph.D. 14), a data scientist at Wells Fargo, brought additional industry perspective to the class.
该计划是由三合一和国家科学基金会赞助的,并由包括乔治亚理工学院在内的各种各样的教师进行专题讲座,其中包括Polo Chu,计算科学与工程学院的副教授,Mark Davenport,电气与计算机工程学院副教授,Vladimir Koltchinskii,数学学院教授,阿卡迪·尼米洛夫斯基,约翰·亨特教授,伊斯耶教授,还有霍和谢。富国银行(Wells Fargo)数据科学家黄岩(音译)博士(Ph.D.14)为本课程带来了更多的行业视角。
“Based on the feedback from the participants, most of them appreciate the fact that this summer school emphasizes the theoretical aspect of the data science,” said Huo. “They enjoyed the open and interactive atmosphere. Some believe that they are likely to use the ideas that they learned or developed during this summer school in their future work.”
“根据参与者的反馈,他们中的大多数人意识到这个暑期学校强调数据科学的理论方面,”霍说。“他们喜欢开放和互动的氛围。一些人认为,他们很可能会利用他们在暑期学校在未来的工作中学习或开发的想法。
The organizers are likely to continue organizing this type of summer school in 2020. They plan to incorporate more contents, which were recommended by this year’s participants.
主办单位很可能在2020年继续举办这类暑期学校。他们计划纳入更多的内容,这些内容是今年参与者推荐的。
About TRIAD
关于三合会
TRIAD is a cross-disciplinary institute that was established in 2017 as part of the National Science Foundation’s TRIPODS (Transdisciplinary Research in Principles of Data Science) program. TRIAD unites statistics, mathematics, and theoretical computer science to further develop the foundations of data science. TRIAD brings together senior, mid-career, and junior faculty members, postdoctoral fellows, graduate and undergraduate students, all from Tech’s colleges of Computing, Engineering, and Sciences, and data science practitioners-at-large using focused working groups, national and international workshops, and organized innovation labs.
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