Wei Fan, Ph.D.

  IBM T.J.Watson Research  
  19 Skyline Drive
  Hawthorne, NY 10532
  Tel: 1-914-784-7027
  Fax: 1-917-464-6646
  Email:  wei.fan@gmail.com
              weifan@us.ibm.com

 


 

Education

  Ph.D., Computer Science, Columbia University, New York City, NY, 2001.
  M.E.,  Computer Science, Tsinghua University, Beijing , China , 1995
  B.E.,  Computer Science (minor Precision Instruments and Mechanology), Tsinghua University, Beijing , China , 1993


 


Short Biography

Dr. Wei Fan received his PhD in Computer Science from Columbia University in 2001 and has been working in IBM T.J.Watson Research since 2000. He published more than 60 papers in top data mining, machine learning and database conferences, such as KDD, SDM, ICDM, ECML/PKDD, SIGMOD, VLDB, ICDE, AAAI, ICML etc. Dr. Fan has served as Area Chair, Senior PC of SIGKDD'06, SDM'08 and ICDM'08/09, sponsorship co-chair of SDM'09, award commitee member of ICDM'09, as well as PC of several prestigious conferences in the area including KDD'09/8/07/05, ICDM'07/06/05/04/03, SDM'09/07/06/05/04, CIKM'09/08/07/06, ECML/PKDD'07'06, ICDE'04, AAAI'07, PAKDD'09/08/07, EDBT'04, WWW'09/08/07, etc. He is on the advisory board of KD2U. Dr. Fan was invited to speak at ICMLA'06. He served as US NSF panelist in 2007/08. His main research interests and experiences are in various areas of data mining and database systems, such as, risk analysis, high performance computing, extremely skewed distribution, cost-sensitive learning, data streams, ensemble methods, easy-to-use nonparametric methods, graph mining, predictive feature discovery, feature selection, sample selection bias, transfer learning, novel applications and commercial data mining systems. He is particularly interested in simple, unconventional, but effective methods to solve difficult problems. His thesis work on intrusion detection has been licensed by a start-up company since 2001. His co-teamed submission that uses Random Decision Tree (RDT) has won the ICDM'08 Contest Crown Awards. His co-authored paper in ICDM'06 that uses "Randomized Decision Tree" to predict skewed ozone days won the best application paper award. The open source code of Random Decision Tree (RDT) in JAVA is available from The DICE Library. His co-authored paper in KDD'97 on distributed learning system "JAM" won the runner-up best application paper award.