佐治亞理工學院數(shù)據(jù)科學基金會主辦第一所暑期學校
2023-09-28 13:50:03 來源：中國教育在線
近年來，越來越多的中國學子選擇留學，那其中佐治亞理工學院數(shù)據(jù)科學基金會主辦第一所暑期學校？本文則針對這個問題，為大家整理了資料，接下來咱們就一起往下了解吧。
The Foundation of Data Science Hosts First Summer School
數(shù)據(jù)科學基金會主辦第一所暑期學校
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.
來自全國各地的四十名高級研究生和博士后研究人員于8月5日在H.密爾頓斯圖爾特工業(yè)與系統(tǒng)工程學院（ISYE）集合，參加佐治亞理工學院主持的數(shù)據(jù)科學暑期學校的第一個基礎(chǔ)。
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.
這項為期四天的計劃由羅素·錢德勒三世教授和佐治亞理工大學推進數(shù)據(jù)科學跨學科研究所（三合會）、小明霍和Harold R.、Mary Anne Nash早期職業(yè)教授和Yao Xie教授助理組成。參與者被介紹到一個數(shù)據(jù)科學的理論基礎(chǔ)和一系列應用主題。重點是統(tǒng)計、優(yōu)化和信號處理的基本概念，以及這些技術(shù)在跨學科研究中的應用。
“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.”
“參與研究的學生接觸了一套數(shù)學工具，這些工具有可能被用來推導數(shù)據(jù)科學中廣泛采用的各種技術(shù)性能的基本界限，”霍教授解釋說。雖然全國各地有許多在線和物理活動（如自助夏令營和暑期學校）教數(shù)據(jù)科學工具，但是一個強調(diào)數(shù)學工具和數(shù)據(jù)科學技術(shù)基礎(chǔ)的暑期學校很少。因此，這所暑期學校是獨一無二的?！?/p>
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.
該計劃是由三合一和國家科學基金會贊助的，并由包括喬治亞理工學院在內(nèi)的各種各樣的教師進行專題講座，其中包括Polo Chu，計算科學與工程學院的副教授，Mark Davenport，電氣與計算機工程學院副教授，Vladimir Koltchinskii，數(shù)學學院教授，阿卡迪·尼米洛夫斯基，約翰·亨特教授，伊斯耶教授，還有霍和謝。富國銀行（Wells Fargo）數(shù)據(jù)科學家黃巖（音譯）博士（Ph.D.14）為本課程帶來了更多的行業(yè)視角。
“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.”
“根據(jù)參與者的反饋，他們中的大多數(shù)人意識到這個暑期學校強調(diào)數(shù)據(jù)科學的理論方面，”霍說。“他們喜歡開放和互動的氛圍。一些人認為，他們很可能會利用他們在暑期學校在未來的工作中學習或開發(fā)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.
主辦單位很可能在2020年繼續(xù)舉辦這類暑期學校。他們計劃納入更多的內(nèi)容，這些內(nèi)容是今年參與者推薦的。
About TRIAD
關(guān)于三合會
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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