The work of this year's winners of the ACM SIGKDD Innovation and Service Awards, Prof. Kleinberg and Dr. Melli', has opened new exploration paths for data scientists and practitioners." Ying Li, Chair of the KDD Awards Committee
CHICAGO (PRWEB) August 06, 2013
ACM’s Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD) will recognize the winners of awards for seminal research and outstanding service to the community at its KDD conference August 11-14. Prof. Jon Kleinberg of Cornell University is the winner of the 2013 Innovation Award, Dr. Gabor Melli will receive the 2013 Service Award, and Dr. Yizhou Sun of University of Illinois at Urbana-Champaign is the recipient of the Best Doctoral Dissertation Award.
“Prof. Kleinberg’s development of new algorithms and clean formalizations of novel data mining problems and Dr. Melli’s dedication to the science of data mining and to the KDD community have had profound effect on the field,” said Ying Li, Chief scientist and Co-Founder of Concurix Corporation and Chair of the KDD Awards Committee. “Their research and efforts have opened new exploration paths for data scientists and practitioners.”
ACM SIGKDD Innovation Award – Studying social, information and human networks
The ACM SIGKDD Innovation Award is the highest award for technical excellence in Knowledge Discovery and Data Mining (KDD). Prof. Kleinberg 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. His works include the hubs and authorities algorithm for computing importance scores of nodes in a graph (an important part of any search engine’s ranking of search results), methods for predicting the occurrence of new links in networks, and an algorithm for maximizing the spread of influence through a social network. His recent research focuses on methods for studying social phenomena on the Internet, understanding ways, in which humans evaluate and express opinions about each other, the role of structural diversity and social contagion in networks, link formation and network evolution, and analysis of temporal bursts in networks.
A Tisch University Professor of Computer Science at Cornell, Kleinberg was awarded a MacArthur Foundation Fellowship, also known as the “genius grant,” in 2005, and the Nevanlinna Prize in 2006, which is given every four years as the premier distinction in computational mathematics. He also won the 2008 ACM-Infosys Foundation Award for personal contributions by young scientists to a contemporary innovation in computing. He is a member of the National Academy of Engineering, the American Academy of Arts and Sciences, and the National Academy of Sciences. For additional information, visit: http://www.kdd.org/blog/acm-sigkdd-2013-innovation-award-prof-jon-kleinberg.
ACM SIGKDD Service Award – Building the KDD community
The ACM SIGKDD Service Award recognizes individuals or group for outstanding professional services and contributions to the knowledge discovery and data mining community. Dr. Gabor Melli has contributed to the KDD community since 1997 when he released his synthetic dataset generator. In 2005 he co-founded the Data Mining Case Studies workshop series and became the SIGKDD Information Director, helping organize various KDD, ICDM and CIKM international conferences. More recently Melli initiated a project to semi-automatically create an extensive web knowledge base of KDD concepts.
Melli has published over 25 papers in the field and currently is the Chief Scientist at VigLink Inc., a content monetization platform, where he is driving revenue for leading websites through his research into data-driven solutions to semantic information processing. Prior to VigLink, he led projects at Microsoft, AT&T Wireless, Verizon, and WalMart. For more information, visit http://www.kdd.org/blog/acm-sigkdd-2013-service-award-dr-gabor-melli.
ACM SIGKDD Doctoral Dissertation Award – Next generation of data science and research
The ACM SIGKDD Best Doctoral Dissertation award recognizes excellent research by doctoral candidates in the field of data mining and knowledge discovery. “Mining Heterogeneous Information Networks” is the title of this year’s winning entry by Dr. Yizhou Sun, currently an assistant professor of Computer Science at Northeastern University in Boston. Tufts University’s Byron Wallace’s work “Machine Learning in Health Informatics: Making Better use of Domain Experts” is the runner up, and U Kang (Carnegie Mellon University) and Venu Satuluri (Ohio State University) will receive honorable mentions.
Bringing the world’s top data scientists and data mining experts to Chicago
Attracting leading data scientists and practitioners, KDD 2013 is the premier venue to exchange research and industry practice ideas and results and shape the future of predictive analytics and data mining. In addition to the highly selective research and industry and government tracks, the conference features an Industry Practice Expo track, giving a forum to leading experts, who have developed and deployed successful, large-scale predictive analytics and data mining systems in their respective fields.
Keynote speakers include Microsoft CTO Raghu Ramakrishnan on a new generation of data management and analytic systems for today’s data scale and usage. In addition, Stanford University’s Andrew Ng, a founder of Coursera, the massive open online course program started at Stanford University, will offer his thoughts on the revolution to make high-quality online education accessible to everyone. Other keynoters include Stephen Wright of University of Wisconsin-Madison on optimization in learning and data analysis; and Google Chief Economist Hal Varian on predicting the present with search engine data.
Registration for KDD 2013 is open online at http://www.kdd.org/kdd2013/registration.
With over 2000 members from leading research institutions, universities and business organizations in more than 80 countries, the ACM Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD) is the premier forum for advancement and adoption of KDD, data science, and data mining over Big Data. SIGKDD’s mission is to provide the growing community of big data and analytics experts with tools and resources to promote the value of knowledge discovery and data mining in today’s data-centric economy. For additional information, please visit http://www.kdd.org or follow us on Twitter (@kdd_news).
ACM, the Association for Computing Machinery, is the world’s largest educational and scientific computing society, uniting computing educators, researchers and professionals to inspire dialogue, share resources and address the field’s challenges. ACM strengthens the computing profession’s collective voice through strong leadership, promotion of the highest standards, and recognition of technical excellence. ACM supports the professional growth of its members by providing opportunities for life-long learning, career development, and professional networking.
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