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2018第一届中澳天文联合研究中心天文信息学暑期学校 第一轮通知 (2018年7月12日更新)

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参与人名单

第一届中澳天文联合研究中心(ACAMAR)-天文信息论坛暑期学校将于2018年8月5日至7日在上海天文台举行。本次暑期学校面向全国各高校优秀本科生、研究生和青年学者招收约30名学员。此次暑期学校得到了中澳天文联合研究中心、国家科技部、中国SKA办公室和中国科学院的支持。

即将启动建设的平方公里阵列射电望远镜(SKA)是天文学家迄今建造的最大科学实验装置,有望为人类探索和认识宇宙带来革命性的发现。SKA将产生前所未有的射电天文大数据,SKA天文数据处理平台将承担深度数据分析和科学数据的长期存储,直接面对科学用户,其数据处理能力和科研团队的分析研究水平是SKA能否取得预期科研突破的关键。为了更好应对SKA大数据的挑战,中澳天文联合研究中心联合上海天文台举办第一届“天文信息学暑期学校”,集中讨论天文大数据相关的内容,并为学员提供:

1. 天文信息学方面的相关培训,以便更好的应对大数据下的数据分析方法,以及不同天文领域中日益增加的计算建模的需求。

2. 利用SKA早期科学数据,进行数据分析与计算建模的实战练习机会。

暑期学校将会以授课与上手实践混合(围绕具体课题开展实践为主)的方式开展活动,上海天文台将提供必要的计算资源和测试数据。

授课内容包括机器学习和GPU的使用、Python与数据可视化与HPC环境下的编程。具体授课内容安排如下:

SessionTimeDescription
1August 5 morningIntroduction of three subjects: objectives and deliverable
  • Machine Learning and GPU Programming with Python
  • Data Visualization with Python
  • Introduction to HPC and Distributed Processing
2August 5th afternoon, August 6th whole day, August 7th morning Break-out sessions: hands-on training
3August 7th, 13.30 - 15:00Prepare for the team presentations
4August 7th, 15.00 - 16:30Team presentations , each 30 min

具体实践安排详见暑期学校网址的课程安排。

暑期学校网址:http://astroinformatics-2018.csp.escience.cn/

研究生或本科生需要在注册时按要求(详见申请资格)提供总共不超过两页的简历及自述,以便组委会根据情况择优录取。

暑期学校具体安排如下:

时间:2018年8月5日-7日

地点:中国科学院上海天文台

安排:暑期学校

授课语言:英语

申请资格:

  1. 天文、物理、计算机、通信、图像处理、统计以及密切相关专业。
  2. 因全程英语授课和实战练习,对英语水平要求较高:要求英语六级,或托福90分及以上、或雅思6分及以上。
  3. 有发表论文/专利或相关科研经历者优先考虑。
  4. 需具备以下至少一个条件:有Python编程经验,了解GPU编程语言,有HPC实践相关经验。【以上信息可体现在申请材料中】
  5. 招生规模:不超过30名高年级本科生、研究生及青年学者

费用情况:免注册费。本科生及研究生择优资助食宿与交通费,青年学者食宿需自理。

报名截止日期:请有意申请的学员在6月30日前完成网上注册:http://astroinformatics-2018.csp.escience.cn/

更多信息及后继信息更新请关注以及上海天文台SKA团组主页:http://202.127.29.4/CRATIV/zh-cn/home.html

重要时间节点:

7月10日:通过邮件通知入选学员【未入选者不再通知】

7月15日:讲课老师布置参考资料和课题描述,搭建基本软件环境,提供测试数据、程序和代码

7月16-30日:预习,建群提前与老师以及其他学员沟通交流

主讲教师:

Chenzhou Cui (崔辰州),国家天文台,主讲虚拟天文台与国际虚拟天文台联盟

Shiyuan He (贺诗源), 中国人民大学统计与大数据研究院,主讲机器学习与GPU编程相关课程。

Brian Skjerven, Pawsey Supercomputing Centre,主讲HPC编程与实践相关课程。

Elaina Hyde,Western Sydney University, 主讲Python与数据可视化

SOC:

会议联系人:

Robert Shen(澳大利亚天文学有限公司AAL): robert.shen@astronomyaustralia.org.au

安涛(上海天文台):antao@shao.ac.cn

伍筱聪(上海天文台): wuxc@shao.ac.cn

郭铨(上海天文台):guoquan@shao.ac.cn

主办方: 中澳天文联合研究中心 (ACAMAR)

承办方: 中国科学院上海天文台

2018 年 6 月 10 日

主讲教师简介

Chenzhou Cui(崔辰州)

Abstract: A brief introduction about Virtual Observatory, including its history, sciences, and challenges. The current status of International Virtual Observatory Alliance (IVOA), architecture and key specifications of the IVOA will be introduced. Resources and services of the Chinese Virtual Observatory (China-VO) and their applications in astronomy research will be described.

Dr. Cui got his Ph.D. degree in 2003 from National Astronomical Observatories, Chinese Academy of Sciences (NAOC). He is the first person to get a Ph.D. degree in the research field of Virtual Observatory in the world. In 2006, Dr. Cui became the Chief Information Officer for NAOC, and led the NAOC Center of Information and Computing. As the Principle Investigator (PI) of Chinese Virtual Observatory (China-VO), Dr. Cui built up the China-VO service platform during the last decade, which is a cyberinfrastructure for astronomical research, providing observation, data archiving and access, data analyzing, data mining, cloud-computing, and other services. In June 2018, Dr. Cui was nominated as the deputy chair of the IVOA.

Shiyuan He (贺诗源)

Shiyuan got his Ph.D in statistics from Texas A&M University. His research interests include statistical computing, functional data analysis, manifold optimization in statistics and astrostatistics. He is specialized in large scale computing, distributed and randomized algorithm to reduce the computation cost.

Brian Skjerven

Supercomputing Application Specialist

Pawsey Supercomputing Centre, Australia

Elaina Hyde

Astronomer by training, data scientist by trade. Google Cloud Engineering Instructor. Currently an Adjunct Fellow at Western Sydney University and a consultant at Servian in downtown Sydney. Trained in Astrophysics, I combine machine learning and data science with consulting and astrophysics. As a fellow and part time lecturer at the University of Western Sydney in Australia as well as the previous Information Support Officer for ITSO at the Australian Astronomical Observatory gives me a high degree of technical expertise. I completed a PhD degree at Macquarie University in Australia and a bachelor’s in Astronomy and Physics (with minors in Optical Engineering and Planetary Sciences) from the University of Arizona in Tucson, Arizona, a masters research program at the Max-Plank Institute, as well as a masters program in Astrophysics from the University of Amsterdam. These studies allowed me to participate in research in engineering and astrophysics. My current favourite programming languages are Python, C, R and SQL.

I am interested in data science applications as well as the theory behind the algorithms, in particular for machine learning, data analysis, classification algorithms and AI. My research interests include in coding machine learning algorithms in Python to search astrophysical databases and combining that approach with a public facing projects. My current main focus area is cloud computing and providing solutions utilizing the Google Cloud Platform. I am a certified Google Cloud Engineering Instructor and provide consulting to data science based projects both in and above the cloud.

初步日程

8月5日

SessionTimeDescriptionNotes
1.08.30 - 9.00Registration3rd floor of SHAO, Nandan Road, No 80
1.19.00 - 9.30Welcome from host institute (Zhiqiang Shen)
Opening remark from ACAMAR (Lister Staveley-Smith)
Introduction and Housekeeping rules (Tao An & Robert Shen)
1.29.30-10.00Virtual Observatory and IVOA (Chenzhou Cui)
10:00-10:30Take a group photo and coffee break
1.310:30 – 11:00Introduction to Machine Learning and GPU Programming with Python (Lecturer: Shiyuan He)
1.4 11:00 - 11:30 Introduction to Data Visualization with Python (Lecturer: Elaina Hyde)
1.511:30-12:00 Introduction to HPC and Distributed Processing (Lecturer: Brian Skjerven)
1.6 12:00 – 12:30 Hands on assignment: group objectives, task assignment, deliverable; 10min each group
12:30 – 13:30 Lunch (SHAO canteen)
1.4 13.30 - 17.00 Break-out sessions: hands-on training
Group 1: Machine Learning and GPU Programming with Python (Advisor: Shiyuan He)
Group 2: Data Visualization with Python (Advisor: Elana Hyde)
Group 3: HPC and Distributed Processing (Advisor: Brian Skjerven)
1.517.00 - 17.30Group review: what we learned so far; 10min report each group
1.718.30Workshop Banquet
8月6日
SessionTime Description Notes
2.19.00 – 10:30Break-out sessions: hands-on training
Group 1: Machine Learning and GPU Programming with Python (Advisor: Shiyuan He)
Group 2: Data Visualization with Python (Avisor: Elaina Hyde)
Group 3.HPC and Distributed Processing (Advisor: Brian Skjerven)
10:30-11:00 Coffee Break
2.2 11.00-12.30 Break-out sessions: hands-on training
Group 1: Machine Learning and GPU Programming with Python (Advisor: Shiyuan He)
Group 2: Data Visualization with Python (Advisor: Elaina Hyde)
Group 3: HPC and Distributed Processing (Advisor: Brian Skjerven)
12.30 - 13.30Lunch (SHAO canteen)
2.3 13.30 - 15.00Break-out sessions: hands-on training
Group 1: Machine Learning and GPU Programming with Python (Advisor: Shiyuan He)
Group 2: Data Visualization with Python (Advisor: Elaina Hyde)
Group 3: HPC and Distributed Processing (Advisor: Brian Skjerven)
15.00 - 15.30Coffee Break
2.4 15:30 – 17:00Break-out sessions: hands-on training
Group 1: Machine Learning and GPU Programming with Python (Advisor: Shiyuan He)
Group 2: Data Visualization with Python (Advisor: Elaina Hyde)
Group 3: HPC and Distributed Processing (Advisor: Brian Skjerven)
2.5 17:00 – 17:30Group review: what we learned so far; 10min report each group
18:30 Dinner
8月7日
Session Time Description Notes
3.1 9:00 – 10:30 Break-out sessions: hands-on training
Group 1: Machine Learning and GPU Programming with Python (Advisor: Shiyuan He)
Group 2: Data Visualization with Python (Advisor: Elaina Hyde)
Group 3: HPC and Distributed Processing (Advisor: Brian Skjerven)
10:30-11:00 Coffee Break
3.2 11:00-12.30 Break-out sessions: hands-on training
Group 1: Machine Learning and GPU Programming with Python (Shiyuan He)
Group 2: Data Visualization with Python (Advisor: Elaina Hyde)
Group 3: HPC and Distributed Processing (Advisor: Brian Skjerven)
12.30 - 13.30 Lunch (SHAO canteen)
3.313.30 - 15:00 Team to prepare for the presentations
3.4 15.00 - 16:30 Team presentations , each 30 min
3.5 16:30 - 17:00 Closing remarks

参与人名单

姓名单位邮箱
陈骁上海天文台xchen@shao.ac.cn
杜翔宇美国卡耐基梅隆大学(CMU)-
冯毅国家天文台yifeng@nao.cas.cn
郭铨上海天文台guoquan@shao.ac.cn
郭绍光上海天文台sgguo@shao.ac.cn
劳保强上海天文台lbq@shao.ac.cn
刘伟北京师范大学weiliu@mail.bnu.edu.cn
刘奕含华中科技大学u201410253@mail.hust.edu.cn
刘映峰国家天文台liuyingfeng17@mails.ucas.edu.cn
刘雨辰伦敦大学学院liuyuchenlyc2016@163.com
邵琅紫金山天文台lang@pmo.ac.cn
施嫄国家天文台shiyuan17@mails.ucas.edu.cn
王玲玲上海天文台llwang@shao.ac.cn
吳浩然香港中文大学-
熊浪浪南昌大学langlangx@email.ncu.edu.cn
杨舒程上海天文台ysc@shao.ac.cn
于昂桂林电子科技大学-
Tin-yau YuUniversity of British Columbia-
张燕坤云南天文台yankun_zh@163.com
张迎康上海天文台ykzhang@shao.ac.cn
张宗煜清华大学zongyu-z15@mails.tsinghua.edu.cn
赵佳华南方科技大学11612801@mail.sustc.edu.cn
赵振上海天文台zhaozhen@shao.ac.cn
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