祝贺杨强教授获得2017年SIGKDD杰出服务奖

祝贺杨强教授获得2017年SIGKDD杰出服务奖

2017 SIGKDD SERVICE AWARD AWARD WINNER

祝贺杨强教授获得2017年SIGKDD杰出服务奖

杨强教授

2017年SIGKDD杰出服务奖得主

中国人工智能学会副理事长、AAAI Fellow、香港科技大学计算机科学与工程学系主任

杨强博士长期服务于促进数据挖掘和人工智能领域的发展,并为此作出了杰出的贡献。他曾担任ACM KDD 2010 会议的程序委员会联合主席,并于2012年在北京举办的ACM KDD 担任会议主席的职位。 他还在2015年由阿根廷举办的2015 IJCAI中担任程序委员会主席职务。同时他还担任过多个会议的主席或联合主席,比如:ACM IUI 2009、ACM RecSys 2013和 IEEE Big Data 2013等。同时,他还主持了多个数据挖掘和人工智能方面的评奖委员会主席,包括2017年的ACM SIGKDD长期贡献奖、2017年的IJCAI人工智能奖,以及2017年的IEEE AI ten-to-watch奖。他是ACM智能系统和技术期刊的创刊主编,该本期刊已经成为ACM最近历史上被引用最多的期刊之一。他还在IEEE 创建了大数据期刊,并担任该期刊的主编。与此同时,他还在AAAI的执行委员会任职,也是IJCAI董事会的成员。

杨强博士是中国数据挖掘、机器学习和SIGKDD事业的支持者和组织者。在他的领导下,SIGKDD在2016年初开启了中国的分会。仅在2016年,中国KDD就已经组织了十项活动,大力促进了SIGKDD在中国的发展,为中国工业和学术界之间的架起了桥梁。这些活动吸引了500多名国内会员,其中包括大批的学生和工业研究人员。多年来,杨强博士也在中国国内举办了多次讲座,被邀请参加迁移学习、机器学习和推荐系统相关的演讲和教程。

多年来,杨强博士花费大量的精力来教育学生“如何做研究” 。他参与合著的“学术研究:你的成功之道”一书,是Morgan Claypool出版社网站上下载量最多的书之一,这本书的中文版(清华大学出版社)在中国也非常受读者欢迎。

除了投身于SIGKDD的社会服务外,杨强博士还因其对数据挖掘和机器学习的技术贡献而闻名,特别是在研究迁移学习方面。 他所带领的研究团队赢得了2004年和2005年ACM KDDCUP杯的比赛。同时杨强博士还是多个团体的Fellow,包括IEEE,AAAI,AAAS和IAPR。

与此同时,杨强博士还活跃于数据挖掘和机器学习的工业应用领域。2012年他与其他同事创立了华为的“诺亚方舟实验室”,旨在解决大数据、数据挖掘和机器学习等重大问题。该实验室在电信行业的数据挖掘研究和应用方面做了多项创新。

杨强博士于1982年获得北京大学的天体物理学学士学位,1985年获得美国马里兰大学的天体物理学硕士学位。1989年,他获得了马里兰大学 College Park分校的计算机博士学位。后来,他成为滑铁卢大学的助理教授,并在加拿大西蒙弗雷泽大学担任副教授/全职教授。他现在是香港科技大学的新明工程学讲座教授,同时也是计算机科学与工程学系的主任, 香港科技大学“大数据研究所”的创始主任。

以往获得往届SIGKDD服务奖的15位得主分别是:Gregory Piatetsky-Shapiro、Sunita Sarawagi、Sunita Sarawagi、Won Kim、Ramasamy Uthurusamy、Ramasamy Uthurusamy、Ramasamy Uthurusamy、Ramasamy Uthurusamy、Ramasamy Uthurusamy、Ramasamy Uthurusamy、Ramasamy Uthurusamy、Ramasamy Uthurusamy、Xindong Wu、Ramasamy Uthurusamy、Wei Wang。

该奖项将于2017年8月13日在加拿大哈利克斯举行的第22届ACM SIGKDD国际会议(kdd-2017)会议开幕式上进行颁奖,奖项内容包含奖牌以及2500美元的奖金。

原文链接:http://www.kdd.org/awards/view/2017-sigkdd-service-award-dr.-qiang-yang?from=timeline&isappinstalled=0

原文内容:

Dr. Qiang Yang has a outstanding history of serving and promoting the fields of data mining and the artificial intelligence. He has served as the PC Co-chair for ACM KDD 2010, General Chair for ACM KDD 2012 in Beijing and PC Chair for IJCAI 2015. He was the General Co-Chair for conferences such as ACM IUI 2009, ACM RecSys 2013, and IEEE Big Data 2013. He has chaired many committees in data mining and AI, including the 2017 ACM SIGKDD Test-of-Time Paper Award Committee, 2017 IJCAI Award Committee, and 2017 IEEE AI Ten-to-Watch Committee. He is the founding editor in chief of ACM Transactions on Intelligent Systems and Technology (ACM TIST), which has become one of the most cited journals under ACM in recent history. He has also founded the journal IEEE Transactions on Big Data, for which he is the Editor in Chief. He serves on the AAAI Executive Council and is a member of the Board of Trustees for IJCAI.

Dr. Yang is a strong proponent for data mining, machine learning and SIGKDD in China. Under his leadership, SIGKDD opened a new chapter in China in early 2016. In 2016 alone, KDD China has organized 10 events under the SIGKDD China Chapter, significantly promoting SIGKDD in China and bridging the gap between industries and academia in China. It has attracted more than 500 members including large numbers of students and industrial researchers. Over the years, Dr. Yang has given many tutorials and lectures in KDD on China. Many of the invited talks and tutorials are related to transfer machine learning and recommendation systems.

Over the years, Dr. Yang spent a great effort in educating students and young researchers on the topic of “research methodology.” His co-authored book "Crafting Your Research Future: A Guide to Successful Master's and Ph.D. Degrees in Science & Engineering" is among the the most downloaded books on Morgan & Claypool Publishers' website. A companion Chinese book is also very popular in China.

Besides his service for SIGKDD, Dr. Yang is also well known for his technical contributions to data mining and machine learning, particularly in the research area of transfer learning. He is a world leading researcher in both the theoretical formalization and practical applications of transfer learning. His team won the 2004 and 2005 ACM KDDCUP competitions. Dr. yang is an IEEE Fellow, AAAI Fellow, AAAS Fellow and IAPR Fellow.

Dr. Yang is also active in industrial applications of data mining and machine learning. Under his leadership, a new research lab named the Noah’s Ark Lab was set up to tackle important problems in big data, data mining and machine learning. The lab took many new initiatives in research and applications of data mining in the telecommunications industry.

Dr. Qiang Yang received a B.S degree from Peking University in China and a M.S. degree from the University of Maryland, both in Astrophysics. He obtained his Ph.D. degree from the University of Maryland, College Park in 1989. Subsequently, he became an assistant/associate professor at the University of Waterloo and Associate/Full Professor at the Simon Fraser University in Canada. He is now the New Bright Professor of Engineering at Hong Kong University of Science and Technology (HKUST). He is also a Chair Professor and head of Department of Computer Science and Engineering at HKUST. He is also the founding director of the Big Data Institute at HKUST.

The fifteen previous SIGKDD Service Award winners have been: Gregory Piatetsky-Shapiro, Ramasamy Uthurusamy, Usama Fayyad, Xindong Wu, The Weka team, Won Kim, Robert Grossman, Sunita Sarawagi, Osmar R. Zaïane, Bharat Rao, Ying Li, Gabor Melli, Ted Senator, Jian Pei, and Wei Wang.

The award includes a plaque and a check for $2,500 and will be presented during the Opening Plenary Session of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2017), on Sunday August 13 in Halifax, Canada.

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