SIGKDD Awards

SIGKDD Innovation Award

The award recognizes individuals for their outstanding technical contributions to the field of knowledge discovery in data and data mining that have had lasting impact in furthering the theory and/or development of commercial systems.

Recipients

2017 SIGKDD Innovation Award: Dr. Jian Pei

ACM SIGKDD is pleased to announce that Dr. Jian Pei is the winner of its 2017 Innovation Award.  He is recognized for his seminal contributions to the foundation of data mining and applications, particularly in pattern mining and spatial data mining.  He is a major inventor of several pattern-growth methods, including FP-growth and PrefixSpan, which have been extensively used by industry and adopted by data mining textbooks and open source software toolkits. As one of the most cited authors in data mining, his prolific publications have been cited tens of thousands of times.

The ACM SIGKDD Innovation Award is the highest award for technical excellence in the field of Knowledge Discovery and Data Mining (KDD). It is conferred on one individual or one group of collaborators whose outstanding technical innovations in the KDD field have had a lasting impact in advancing the theory and practice of the field. The contributions must have significantly influenced the direction of research and development of the field or transferred to practice in significant and innovative ways and/or enabled the development of commercial systems.

Continue Reading

2016 SIGKDD Innovation Award: Philip S. Yu

ACM SIGKDD is pleased to announce that Philip S. Yu is the winner of its 2016 Innovation Award.  He is recognized for his influential research and scientific contributions on mining, fusion and anonymization of big data.

The ACM SIGKDD Innovation Award is the highest award for technical excellence in the field of Knowledge Discovery and Data Mining (KDD). It is conferred on one individual or one group of collaborators whose outstanding technical innovations in the KDD field have had a lasting impact in advancing the theory and practice of the field. The contributions must have significantly influenced the direction of research and development of the field or transferred to practice in significant and innovative ways and/or enabled the development of commercial systems.

Continue Reading

2015 SIGKDD Innovation Award: Hans-Peter Kriegel

Hans-Peter Kriegel is the winner of its 2015 Innovation Award.  He is recognized for his influential research and scientific contributions to data mining in clustering, outlier detection and high-dimensional data analysis, including density-based approaches. He has been a Professor of Informatics at Ludwig-Maximilians-Universitaet Muenchen, Germany since 1991. He has published over a wide range of data mining topics including clustering, outlier detection and high-dimensional data analysis. In 2009 the Association for Computing Machinery (ACM) elected Professor Kriegel an ACM Fellow for his contributions to knowledge discovery and data mining, similarity search, spatial data management, and access-methods for high-dimensional data.

Continue Reading

2014 SIGKDD Innovation Award: Pedro Domingos

Prof. Domingos carried out some of the earliest research on mining data streams. His VFDT algorithm was the first to be capable of learning decision trees from streams while guaranteeing that the result is very close to that of batch learning, and remains the fastest decision tree learner available. He went on to generalize the ideas in VFDT to clustering, the EM algorithm, Bayesian network structure learning, and other problems. The resulting VFML toolkit is one of the best open-source resources for stream mining.

Continue Reading

2013 SIGKDD Innovation Award: Prof. Jon Kleinberg

ACM SIGKDD is pleased to announce that Prof. Jon Kleinberg is the winner of the 2013 Innovation Award. He is recognized for his seminal contributions to the analysis of social and information networks, mining the web graph, study of cascading behaviors in networks, and the development of algorithmic models of human behavior.

Continue Reading

2012 SIGKDD Innovation Award: Prof. Vipin Kumar

Prof. Vipin Kumar is recognized for his technical contributions to foundational research in data mining as well as its applications to mining scientific data. Prof. Kumar has made numerous significant and impactful contributions to a wide range of core data mining areas including graph partitioning, clustering, association analysis, high performance and parallel data mining, anomaly/change detection and data driven discovery methods for analyzing global climate and ecosystem data. Many of his papers on these topics are amongst the most highly cited papers in data mining.

Continue Reading

2011 SIGKDD Innovation Award: Dr. J. Ross Quinlan

Dr. Ross Quinlan is recognized for his seminal contributions to rule induction and decision tree algorithms and for participating in laying the foundation of data mining, particularly with the invention of ID3 and C4.5, algorithms pivotal in myriad applications. Dr. Ross Quinlan is best known for the development of programs for machine learning and data mining. 

Continue Reading

2010 SIGKDD Innovation Award: Dr. Christos Faloutsos

Prof. Christos Faloutsos is recognized for his fundamental contributions to graph and multimedia mining, fractals, self-similarity and power laws; indexing for multimedia and bioinformatics data, and data base performance evaluation. His seminal cross-disciplinary works on power-law graphs, fractal-based analysis, time series, multimedia and spatial indexing are a rare combination of both impressive breadth as well as fundamental depth that set new research directions and inspired subsequent research impacting the KDD field.

Continue Reading

2009 SIGKDD Innovation Award: Dr. Padhraic Smyth

Padhraic Smyth is recognized for his contributions to both the theory and application of probabilistic and statistical approaches to data mining. Smyth’s research is in the area of statistical data mining and machine learning. His research focuses on both the basic principles of inference from data (theory and algorithms), combined with applications to a variety of data-driven problems in the sciences, medicine, and engineering. 

Continue Reading

2008 SIGKDD Innovation Award: Raghu Ramakrishnan

Ramakrishnan's contributions span foundational technical innovation on algorithmic and systems aspects of data mining. His work on scalable data mining algorithms started with BIRCH, the first truly scalable clustering algorithm. BIRCH introduced the groundbreaking idea of a cluster feature, a concise summary of a cluster, which was then used in many subsequent clustering algorithms as an integral component.

Continue Reading

2007 SIGKDD Innovation Award: Dr. Usama M. Fayyad

Fayyad is recognized for his seminal work on the development data mining, machine learning algorithms and their scalability to massive database systems, and fundamental applications of data mining in scientific discovery and commercial database systems. His contributions span fundamental technical innovation and significant large-scale applications of the technology in science data analysis, commercial practice, and commercial database systems.

Continue Reading

2006 SIGKDD Innovation Award: Dr. Ramakrishnan Srikant

Srikant identified novel pruning techniques and data structures that made the discovery of association rules feasible. He also generalized association rules along three orthogonal dimensions: discovering associations across different levels of a hierarchy over the items; discovering temporal associations ("sequential patterns"); and discovering associations over quantitative attributes. In each case, Srikant invented pruning techniques and data structures that kept the execution times practical.

Continue Reading

2005 SIGKDD Innovation Award: Dr. Leo Breiman

Dr. Leo Breiman is widely considered one of the founding fathers of modern machine learning and data mining. He has been actively contributing to these fields, as well as to statistics, for more than 30 years. His best known contribution is his landmark work on decision trees.

Continue Reading

2004 SIGKDD Innovation Award: Dr. Jiawei Han

Dr. Han is widely and well regarded as a pioneer researcher in data mining and knowledge discovery, who has made many fundamental research contributions. He has published more than 100 research papers on data mining in leading database and data mining conferences and journals. His contribution can be seen in almost every area of the field. Dr. Han is a very highly cited author, with over 3,000 citations, indicating the quality of his work, his influence in the field, and his contributions to many topics of data mining.

Continue Reading

2003 SIGKDD Innovation Award: Dr. Heikki Mannila

Professor Mannila has the rare virtue of being able to identify new problems, viewpoints, and concepts, and thereby taking the field forward. He introduced the concept of "inductive databases" that integrate data mining and databases. Equally impressive are Professor Mannila's contributions in providing a substantial and much needed theoretical foundation in a very young field. He has given strong theoretical results for many data mining problems, including association rules and frequent time sequences. The breadth of Prof Mannila's work is quite spectacular. He has over 130 articles in journals and refereed conferences covering such diverse topics as association rules, probabilistic modeling, inductive databases, similar time series, and bio-informatics.

Continue Reading

2002 SIGKDD Innovation Award: Dr. Jerome H. Friedman

Jerry Friedman has contributed a remarkable array of topics and methodologies to data mining and machine learning during the last 25 years. Taken together, Dr. Friedman's list of contributions to new methodology, including CART, MARS, PRIM, PPR, and Gradient Boosting, constitutes one of the broadest ranges of any one person in the field.

Continue Reading

2000 SIGKDD Innovation Award: Dr. Rakesh Agrawal

Rakesh Agrawal from IBM has received the first ACM SIGKDD Award for Innovation for his many research contributions, including his pioneering work on association rules, mining sequences and much more.

 

Continue Reading

Frequency of the Awards

Once a year.

Administration of the Awards Program

The SIGKDD Awards Committee, consisting of 3-5 prominent senior scientists in the field, will solicit nominations for recipient candidates, evaluate the nominations, and select winners.

The SIGKDD Chair will form the Awards Committee by inviting candidates. The SIGKDD Chair will appoint the Chair of the Awards Committee.

The terms of the Awards Committee will be the same as the term of the SIGKDD Chair.

Once formed, the Awards Committee will select winners of the Awards completely independently of SIGKDD Chair or SIGKDD Executive Committee.

The Award winner will be decided by a two-thirds majority vote of the Awards Committee.

There will be at most one individual or one group to receive either Award in any given year. (It is possible that in a given year, there may be no winner of either Award.)
 
The Awards Committee will solicit nominations for Award recipients 5 months before the SIGKDD Annual International Conference via the SIGKDD website, SIGKDD Annual Conference website, and the KDNuggets electronic newsletter.

Nominations, once made, may be re-considered for the subsequent two years; if the nominee does not win after the first three years, the nomination is discarded.

The deadline for the nominations will be 3 months before the SIGKDD Annual International Conference. (The Awards Committee will take 6 weeks to make its decisions.)

The winners will receive the Awards at the SIGKDD Annual International Conference. The winners will be announced in the SIGKDD Conference website and the SIGKDD website.

The Awards

Each Award carries a $2,500 monetary award and a plaque.

If the winner is a group of individuals, the group will receive $2,500 (not each individual). However, each individual will receive a plaque.

Exclusions

SIGKDD Chair and members of the SIGKDD Awards Committee are not eligible to be nominated for either Award.

 

Awards Committee

2015 ACM SIGKDD Awards Committee (in alphabetical order)

  • Pedro Domingos (University of Washington)
  • Jiawei Han (University of Illinois)
  • Vipin Kumar (University of Minnesota)
  • Ying Li (EV Analysis Corp.)
  • Gabor Melli (VIgiLink)
  • Bharat Rao (KPMG)
  • Ted Senator — Chair (Leidos)
  • Padhraic Smyth (University of California at Irvine)
  • Ramasamy Uthurusamy (General Motors Corporation, retired)
  • Osmar Zaiane (University of Alberta)

2014 ACM SIGKDD Awards Committee

  • Gabor Melli (VigLink) – Chair of Awards Committee
  • Rakesh Agrawal (Microsoft)
  • Jon Kleinberg (Cornell University)
  • Sunita Sarawagi (Indian Institute of Technology)
  • Bharat Rao (Deloitte)
  • Christos Faloutsos (Carnegie Mellon University)
  • Vipin Kumar (University of Minnesota)
  • Ying Li (EV Analysis Corporation)
  • Osmar Zaiane (University of Alberta)
  • Usama Fayyad (Barclays)

2013 ACM SIGKDD Awards Committee

  • Bharat Rao (Deloitte)
  • Christos Faloutsos (Carnegie Mellon University)
  • Osmar Zaiane (University of Alberta)
  • Padhraic Smyth (University of California, Irvine)
  • Ross Quinlan (Rulequest Research)
  • Ramasamy Uthurusamy (General Motors Corporation)
  • Sunita Sarawagi (Indian institute of technology)
  • Usama Fayyad (ChoozOn Corporation)
  • Vipin Kumar (University of Minnesota)
  • Ying Li (Concurix Corporation) – Chair of Awards Committee

2012 ACM SIGKDD Awards Committee

  • Ramasamy Uthurusamy, Chair Chid Apte, IBM Research
  • Christos Faloutsos, Carnegie Mellon University
  • Bing Liu, University of Illinois at Chicago
  • Gregory Piatetsky-Shapiro, KD Nuggets
  • Daryl Pregibon, Google
  • J. Ross Quinlan, Rulequest
  • Ted Senator, SAIC
  • Padhraic Smyth, University of California at Irvine
  • Qiang Yang, Hong Kong University of Science and Technology
  • Osmar R. Zaiane, University of Alberta C Past Chair

2011 ACM SIGKDD Awards Committee

  • Osmar R. Zaïane, Chair
  • Ramasamy Uthurusamy, Past Chair
  • Christos Faloutsos (Carnegie Mellon University)
  • Peter Flach (University of Bristol)
  • Robert Grossman (University of Illinois at Chicago)
  • Ying Li (Microsoft)
  • Bing Liu (University of Illinois at Chicago)
  • Sunita Sarawagi (Indian Institute of Technology, Bombay)
  • Padhraic Smyth (University of California at Irvine)
  • Qiang Yang (Hong Kong UST)

 

Related Posts:

Copyrights © 2016 All Rights Reserved - SIGKDD
ACM Code of Conduct