From: 	 Ramasamy Uthurusamy   
   Date: 	 Jun 21, 2010   
   Subject:   ACM SIGKDD 2010 Innovation Award to Prof. Christos   
   Faloutsos   
      
      
   ACM SIGKDD is pleased to announce that Prof. Christos   
   Faloutsos is the winner of 2010 SIGKDD Innovation   
   Award. He 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.   
      
   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.   
      
   Professor Faloutsos 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.   
      
   His fundamental contributions to spatial and multimedia   
   mining and indexing were well recognized. In 1997, VLDB   
   recognized his R+tree method with its 'ten year paper'   
   award. His work on Hilbert curves and fractals allowed for   
   better access methods, as well as for modeling and   
   selectivity estimations of real clouds of points. His work on   
   QBIC (Query By Image Content) has been cited more than   
   1,000 times and inspired similar features that are in   
   commercial products such as DB2 Image Extender, and the   
   proposed GeMINI approach (GEneralized Multimedia   
   INdexIng) became the norm in the field.   
      
   His expertise in the field of time series analysis and mining   
   is widely recognized. His FODO 1993 paper introduced   
   methods for efficient similarity search in sequence   
   databases, and it has been cited over 1200 times. His   
   SIGMOD 2004 paper on fast subsequence matching in   
   time-series databases was recognized with the best paper   
   award and has been cited over 1100 times. These seminal   
   papers laid the foundations that inspired a new research   
   area on time series databases.   
      
   His SIGCOMM 1999 paper discovered the fundamental   
   power-laws in the Internet topology. This work pioneered   
   the field, and has inspired many follow-up studies. As an   
   indicator of the huge impact, the paper is the 5th most   
   cited paper in 1999, it has been cited over 3000 times   
   since, and will be presented with the "Test of Time" award   
   at SIGCOMM 2010.   
      
   His KDD 2004 paper was a pioneering contribution to   
   large-scale graph mining. It introduced fast methods to   
   discover connectivity subgraphs, leveraging the duality   
   between random-walk and electricity-based similarity to   
   achieve efficient methods that can be applied at web scale.   
   Going beyond static network models, his seminal paper on   
   modeling network evolution received the best paper award   
   in KDD 2005. This paper reveals surprising phenomena in   
   time-evolving networks such as shrinking diameter and   
   provides a mathematical model, the densification law, to   
   accurately explain those phenomena. His work has also   
   introduced fast methods for estimation of key graph   
   metrics, winning two consecutive SDM best paper awards   
   in 2007 and 2008 Two of his students won dissertation   
   award and runner-up on topics related to graph mining in   
   KDD 2008 and 2007, respectively.   
      
   His sustained contributions to KDD, with more than 200   
   highly cited publications, have been well recognized by a   
   series of prestigious awards, including the ICDM Research   
   Contributions Award in 2006 and 15 Best Paper awards   
   from various highly competitive academic forums including   
   KDD, ICDM, SDM, PKDD, PAKDD, SIGMOD, and VLDB.   
      
   His work has led not only to important publications, but   
   also to several projects with great broader societal impact.   
   For example, his NetProbe project, which developed tools   
   combating Internet auction fraud, was widely reported by   
   many major news media.   
      
   He served on the Board of Directors of the first ACM   
   SIGKDD Executive Committee. He was Program Chair of   
   KDD 2003 and SIGMOD 1999. He was an associate Editor-   
   in-Chief of IEEE Transactions on Knowledge and Data   
   Engineering (TKDE), and is an associate editor of ACM   
   Transactions on Knowledge Discovery from Data (TKDD).   
   He has made significant contribution to the KDD   
   community by continuously training many prominent   
   students and young researchers.   
      
   He received his PhD in 1987 from the University of   
   Toronto, Canada. Since 2000, he has been a full professor   
   at the School of Computer Science at Carnegie Mellon   
   University . He has been issued 5 patents with 4 more   
   pending. He has delivered more than 100 Distinguished,   
   Keynote, and Invited lectures.   
      
   The previous SIGKDD Innovation Award winners were   
   Rakesh Agrawal, Jerome Friedman, Heikki Mannila, Jiawei   
   Han, Leo Breiman, Ramakrishnan Srikant, Usama M.   
   Fayyad, Raghu Ramakrishnan, and Padhraic Smyth.   
      
   The award includes a plaque and a check for $2,500 and   
   will be presented at the Opening Plenary Session of the   
   16th ACM SIGKDD International Conference on Knowledge   
   Discovery and Data Mining, on July 25, 2010 in Washington, DC.   
      
   Prof. Faloutsos will present the Innovation Award   
   Lecture   
   immediately after the awards presentations.   
   ACM SIGKDD is pleased to present Prof. Christos Faloutsos   
   its 2010 Innovation Award for his foundational technical   
   contributions to the KDD field.   
      
   2010 ACM SIGKDD Awards Committee   
    * Ramasamy Uthurusamy, Chair   
    * Robert Grossman (University of Illinois at Chicago)   
    * Jiawei Han (University of Illinois at Urbana-Champaign)   
    * Tom Mitchell (Carnegie Mellon University)   
    * Gregory Piatetsky-Shapiro (KDnuggets)   
    * Raghu Ramakrishnan (Yahoo! Research)   
    * Sunita Sarawagi (Indian Institute of Technology, Bombay)   
    * Padhraic Smyth ( University of California at Irvine)   
    * Ramakrishnan Srikant (Google Research)   
    * Xindong Wu (University of Vermont)   
    * Mohammed J. Zaki (Rensselaer Polytechnic Institute)   
      
   About ACM SIGKDD Innovation Award   
   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.   
   The award includes a plaque and a check for $2,500 and   
   will be presented at the Opening Ceremony of the annual   
      
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