Pacific Asia Knowledge Discovery and Data Mining

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See Archive for past awards.

Each year the Steering Committee presents two special awards - The Most Influential Paper award (published 10 years ago) and the Most Distinguished Contribution award. The conference Program Committee also presents the best paper awards and the best student paper awards.

PAKDD Distinguished Contribution Award 2016 21 April 2016

The Distinguished Contributions Award is awarded to a member of our community to recognise and honour an individual who has made significant and continued contributions in research and services to the advancement of the PAKDD conferences. The selection committee for 2016 was chaired by Professor David Cheung of the University of Hong Kong and assisted by Professors Kyu-Young Whang of the Korean Advanced Institute of Science & Technology and Chengqi Zhang of the University of Technology Sydney.

The 2016 PAKDD Distinguished Contribution is awarded to Zhi-Hua Zhou.

Distinguished Contributions: Professor Zhou's distinctive research contributions in Machine Learning and Data Mining areas can be witnessed, e.g., by his many papers published in premium journals/conferences such as the AIJ (8), IEEE PAMI (6), IEEE TKDE (9), AAAI (30), IJCAI (18), ICML (9), NIPS (4), COLT (2) and KDD (6). According to GoogleScholar, his publications have received 20,000+ citations, with H-index 71, and 19 papers are with 200+ citations.

His research has been highly motivated by the core challenge of predictive modeling, i.e., generalization. Aiming to improve generalization ability of learning systems, Zhi-Hua spans his research in two wings: On one wing, he tries to construct stronger models, and thus he emphasizes studies on ensemble methods; on the other wing, he tries to study data encountered in real situations, and thus he focuses on learning from multi-labeled and partially-labeled data. First, Zhi-Hua is one of the leaders in the research of “ensemble learning” in the world. Because ensemble methods are usually with superior learning performance, they have been widely adopted by almost all winners of various data analysis competitions such as Kaggle competitions and KDDCups. Zhi-Hua’s work helped refine the scope of this area. For example, his AIJ 2002 paper received 1,280+ citations, this impressive citation number clearly shows the high impact of this work. His book “Ensemble Methods: Foundations and Algorithms” has been well-recognized as “bible in ensemble methods”. Second, Zhi-Hua is a leading expert in the research of learning from multi-labeled and partially-labeled data; involving multi-label learning, multi-instance learning, semi-supervised learning. For example, his MLkNN algorithm has become a common standard and one of the most often used multi-label learning algorithm; it has been implemented in the online MULAN toolbox by an European group, and applied by many researchers to various tasks such as image annotation, text categorization, gene function selection, etc. The corresponding paper received 900+ citations. In addition to theoretical and algorithmic contributions, he has also made significant contributions to practical applications. He held 14 patents, and developed many application systems.

Service Contributions: Zhi-Hua has distinctive contributions to the community by his outstanding services. He served on editorial boards for more than twenty journals, and served as chairs or program committee members for all major conferences in his research fields. He has served as General Chair of IEEE ICDM 2016, Program Chair of IEEE ICDM 2015, SIAM Data Mining Conference 2013, IJCAI’ 2015 Machine Learning Track, among many other conferences. He is also the founder of the ACML conference series.

PAKDD Contributions: Zhi-Hua has made great contributions to PAKDD. He served as Steering Committee member from 2007, and life member from 2015. He served as General Chair for PAKDD 2014, Program Chair for PAKDD 2007 and 2015, Area Chair/SPC, PC member for many times. He has served as Keynote speaker for PAKDD 2011. His paper won the PAKDD 2008 Best Paper Award, and he was the team leader for PAKDD 2006 Data Mining Competition (Open Category) Grand Champion, and PAKDD 2012 Data Mining Competition (Open Category) Grand Prize Winner. Education contributions: Zhi-Hua is also a talented educator. He has supervised eleven PhD students in completion, among which eight students have won the “CCF Distinguished PhD Thesis Award”, which is a prestigious award presented by the China Computer Federation, each year only 10 PhD theses in computer science in the whole country will be selected. That means, his students achieved 10% of all awards for the whole country! Many of his students have become active data mining researchers in both academia and industry.

Zhi-Hua is an AAAI Fellow, IEEE Fellow, IAPR Fellow, IET/IEE Fellow, CCF Fellow and ACM Distinguished Scientist.

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Celebrating 20 years of Data Mining and Knowledge Discovery in the Asia Pacific Region