From: Ramasamy Uthurusamy   
   Date: 22 July 2007   
   Subject: ACM SIGKDD 2007 Innovation Award to Usama M. Fayyad   
      
   ACM SIGKDD is pleased to announce that Usama M. Fayyad is the winner   
   of its 2007 Innovation Award.  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.   
      
   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, and   
   Ramakrishnan Srikant.   
      
   The award includes a plaque and a check for $2,500, to be presented at   
   KDD-2007 (The 13th ACM SIGKDD International Conference on Knowledge   
   Discovery and Data Mining) Opening Plenary Session on August 12, 2007   
   in San Jose, CA.  Fayyad will present the Innovation Award Lecture   
   immediately after the award presentations.   
      
   Fayyad's contributions span fundamental technical innovation and   
   significant large-scale applications of the technology in science data   
   analysis, commercial practice, and commercial database systems. His   
   early contributions include the theoretical analysis of decision tree   
   learning algorithms and the invention of some of the fundamental   
   algorithms in decision tree induction from large scale data. His   
   algorithm for discretization of numerical attributes has been and   
   remains the state-of-the-art method in the machine learning and data   
   mining communities for the past decade. His work on applications of   
   data mining and statistical pattern recognition to massive scientific   
   data sets in Astronomy, Planetary Geology, and remote sensing at   
   NASA's Jet Propulsion Lab (JPL), California Institute of Technology   
   have led to solving significant scientific advances and new   
   discoveries in those fields. He received a U.S. Government Medal from   
   NASA for this work as well as the JPL Lew Allen Award for Research   
   Excellence from Caltech -- the highest honor granted to JPL   
   scientists.   
      
   Fayyad's contributions to database systems involved inventing scalable   
   data mining algorithms for massive databases, co-authoring new SQL   
   Extensions and leading development work for embedding data mining   
   algorithms inside the database engine of Microsoft's SQL Server 2000   
   system. The latest version of SQL Server 2006 still includes Fayyad's   
   algorithms as well as derivatives and descendants of the core   
   methodology he introduced.   
      
   Fayyad has played a leading innovative role in the development of the   
   data mining industry by launching a startup company, Revenue Science   
   Inc. (digiMine, Inc.) that developed an innovative business model   
   around hosted on-demand applications of data mining, business   
   intelligence, and targeting algorithms. His second start-up, DMX Group   
   was acquired by Yahoo! Inc. in 2004 where, as a member of the senior   
   executive team as the industry's first Chief Data Officer, he presides   
   over the world's largest data streams (processing over 25 terabytes of   
   data per day), and launching and overseeing Yahoo! Research which has   
   the mission of inventing the new sciences underlying the data-rich   
   areas of Internet, Microeconomics of the Web, and Search and   
   Information Navigation over the world's largest collection of   
   knowledge: the world-wide web.   
      
   Fayyad is co-editor of two influential books in data mining and   
   knowledge discovery and has published over 100 technical articles in   
   machine learning, Artificial intelligence, data mining and databases.   
   He is a prolific inventor with over 30 patents issued and over 50   
   filed patents in the areas of data mining, on-line marketing and the   
   Internet.   
      
   Fayyad has actively participated in the KDD community.  He served as   
   Program Co-Chair of the First International Conference on Knowledge   
   Discovery and Data Mining (KDD 1995), and served as general chair of   
   KDD-96 and as first general chair when the conference moved to ACM   
   SIGKDD in 1999. He is the founding Editor-in-Chief of the primary   
   technical journal in the field: Data Mining and Knowledge Discovery   
   and remained as editor-in-chief for its first decade. He is founding   
   Editor-in-Chief of ACM's SIGKDD Explorations, the official newsletter   
   of the SIGKDD. He is a Fellow of the AAAI (Association for Advancement   
   of Artificial Intelligence) and a Fellow of the ACM and is the   
   recipient of many industry awards.   
      
   ACM SIGKDD is pleased to present Usama M. Fayyad its 2007 Innovation   
   Award for his seminal contributions to machine learning and data   
   mining algorithms that scale to large commercial database systems and   
   for his fundamental applications in mining massive science data sets   
   leading to significant new scientific discoveries.   
      
   2007 ACM SIGKDD Awards Committee   
      
   Ramasamy Uthurusamy (General Motors, USA), Chair   
   Jerome Friedman (Stanford University, 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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