From:      Ramasamy Uthurusamy   
   Date:       August 3, 2008   
   Subject:  ACM SIGKDD 2008 Innovation Award to Raghu Ramakrishnan   
      
      
   ACM SIGKDD is pleased to announce that Raghu Ramakrishnan is the   
   winner of its 2008 Innovation Award.  Ramakrishnan is recognized for   
   his seminal research on techniques for scaling data mining algorithms   
   to large datasets, and on mining ordered and streaming data.   
      
   The ACM SIGKDD Innovation Award is the highest technical award in the   
   field of data mining and knowledge discovery. It is given to one   
   individual or one group of collaborators who has made significant   
   technical innovations in the field of Data Mining and Knowledge   
   Discovery that have been transferred to practice in significant ways,   
   or that have significantly influenced direction of research and   
   development in the field.   
      
   The previous SIGKDD Innovation Award winners were Rakesh Agrawal,   
   Jerome Friedman, Heikki Mannila, Jiawei Han, Leo Breiman, Ramakrishnan   
   Srikant, and Usama Fayyad.   
      
   The award includes a plaque and a check for $2,500, to be presented at   
   KDD-2008 (The 14th ACM SIGKDD International Conference on Knowledge   
   Discovery and Data Mining) Opening Plenary Session on August 24, 2008   
   in Las Vegas, NV. Ramakrishnan will present the Innovation Award   
   Lecture immediately after the award presentations.   
      
   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.   
   Because of its novelty and importance, this is one of the highest   
   cited data mining papers in the last decade. Ramakrishnan later   
   extended this work into a clustering framework for arbitrary metric   
   spaces.  He also worked on scalable algorithms for decision tree   
   construction that are still considered state-of-the-art today.   
      
   BIRCH is also the first true data stream mining algorithm: it   
   constructs a clustering model in a single scan over the data with   
   limited memory. Such algorithms for mining data streams have become a   
   very important area of research in the data mining community over the   
   last decade.   
      
   Further, Ramakrishnan developed a general framework for incrementally   
   mining evolving data and created a framework for measuring change in   
   data streams, again, visionary research topics that have generated   
   much follow-up work since then.  His work also introduced a new   
   construct for analysis of ordered data, reflected in the inclusion of   
   WINDOW functions in the SQL language.   
      
   Ramakrishnan's work includes important contributions to data   
   anonymization, and applying the multi-dimensional model from OLAP to   
   develop a framework for exploratory data mining.   
      
   In addition to his academic research at the University of Wisconsin-   
   Madison, Ramakrishnan has been active in applying data mining in   
   industry. From 2000 to 2003, he was CTO and chairman of QUIQ, a   
   company that developed technology for mass collaboration, a visionary   
   concept that now with the arrival of Web 2.0 has gained widespread   
   acceptance; the QUIQ-powered Ask Jeeves AnswerPoint question-answering   
   portal was the forerunner of similar portals from Amazon, Linked-In   
   and Yahoo!.   
      
   As Chief Scientist for Audience at Yahoo! he has led the research on   
   content optimization, i.e., the task of algorithmically selecting the   
   right content to display on a page when a user visits a web portal.   
   This technology is already having a significant impact in practice. At   
   Yahoo!, Ramakrishnan is also leading the research in cloud computing   
   to develop a family of data hosting and analysis services, which,   
   among other applications, will make it much easier to do data mining   
   on the massive datasets seen at web-scale.   
      
   Ramakrishnan was Program Co-Chair of the Sixth International   
   Conference on Knowledge Discovery and Data Mining (KDD 2000), and   
   served as an Editor-in-Chief of the primary technical journal in the   
   field, Data Mining and Knowledge Discovery.   
      
   He is Chair of ACM SIGMOD, on the Board of Directors of ACM SIGKDD,   
   and on the Board of Trustees of the VLDB Endowment.   
      
   He is a Fellow of the Association for Computing Machinery (ACM) and   
   the Institute of Electrical and Electronics Engineers (IEEE). He has   
   received several awards, including the ACM SIGMOD Contributions Award,   
   a Distinguished Alumnus Award from IIT Madras, a Packard Foundation   
   Fellowship in Science and Engineering, and an NSF Presidential Young   
   Investigator Award.   
      
   ACM SIGKDD is pleased to present Raghu Ramakrishnan its 2008   
   Innovation Award for his foundational contributions to the field.   
      
      
   2008 ACM SIGKDD Awards Committee   
      
   Ramasamy Uthurusamy (General Motors, USA), Chair   
   Usama M. Fayyad (Yahoo!, USA)   
   Robert Grossman (University of Illinois at Chicago, USA)   
   Jiawei Han (University of Illinois Urbana-Champaign, USA)   
   Vipin Kumar (University of Minnesota, USA)   
   Heikki Mannila (University of Helsinki, Finland)   
   Rajeev Motwani (Stanford University, USA)   
   Ramakrishnan Srikant (Google, USA)   
   Ian H. Witten and Eibe Frank (University of Waikato, New Zealand)   
   Xindong Wu (University of Vermont, USA)   
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