1. Data Quality, Data Cleaning and Treatment of Noisy Data DIMACS Workshop November 3-4, 2003 Organizer: Tamraparni Dasu, AT&T Labs - Research

7. Workshop Talks cover different aspects of the complex DQ issue Outstanding set of speakers from academia, industrial labs and industry Cover theoretical, methodological, applied aspects – case studies! From a wide range of disciplines and areas

8. Welcome!

9. Rene Miller University of Toronto Renee is an Associate Professor of Computer Science at the University of Toronto. S.B., Mathematics, MIT. S.B., Cognitive Science, MIT. Ph.D., Computer Science, U. Wisconsin-Madison. Heterogeneous databases, data mining, and data warehousing. “Managing Inconsistency in Data Exchange and Integration”

10. Grace Zhang Morgan Stanley Institutional Equity Division IT. Master of Philosophy in Computer Science from Columbia University, and a Master and B.S. in Computer Science from Zhongshan University,China. Develop tools to check data quality issues in equity trading data, design and build the standard destination referential data repository. “Data Quality in Trading Surveillance”

11. Ted Johnson AT&T Labs – Research Database Research department. B.S. in Mathematics, Johns Hopkins University, Ph.D. in Computer Science, New York University, 1990. Data warehousing and data mining “Bellman - A Data Quality Browser “

12. Ron Pearson Daniel Baugh Institute for Functional Genomics and Computational Biology, Thomas Jefferson University. B.S. in physics from the University of Arkansas at Monticello and M.S.E.E. and PhD in electrical engineering from M.I.T. in 1982. Design and analysis of nonlinear digital filters, exploratory data analysis and the validation of analytical results. “The Data Cleaning Problem -- Some Key Issues and Practical Approaches”

13. Dhammika Amaratunga, Javier Cabrera, Nandini Raghavan Johnson & Johnson, Rutgers University, Johnson & Johnson “Pre-processing of Microarray Data”

14. S. Muthukrishnan Rutgers University, AT&T Labs – Research Associate Professor of Computer Science Design and analysis of algorithms “Checks and Balances: Monitoring Data Quality Problems in Network Traffic Databases”

15. T. Bonates, P. Hammer, A. Kogan, and I. Lozina RutCOR, Rutgers University Operations Research Maximum Patterns and Outliers in the Logical Analysis of Data (LAD)

16. Jiawei Han Professor, Simon Fraser University. Currently at University of Illinois, UC. Ph. D. from University of Wisconsin, Madison in 1985. Data mining (knowledge discovery in databases), data warehousing, spatial databases, multimedia databases, deductive and object-oriented databases, and logic programming “Data Mining: A Powerful Tool for Data Cleaning”

17. Jon Hill British Telecommunications Jon leads a team of information experts to deliver solutions within asset management, process control and billing assurance. Jon uses a wide range of information quality tools within projects and has extensive experience in investigation and solving IQ problems. “A $220 Million Success Story”

18. G. Vesonder, J. Wright & T. Dasu AT&T Labs - Research Head of Adaptive Systems research AI, Knowledge Engineering, Expert Systems “Life Cycle Datamining”

19. Andrew Hume AT&T Labs – Research Very large data systems, string searching, performance measurement Tamed many legacy systems “Managing Data Streams”

20. Bing Liu Associate Professor at National Singapore University, on leave at University of Illinois at Chicago Data mining and knowledge discovery; web, text and image mining; Bioinformatics Web page cleaning for web data mining

21. R.K. Pearson and M. Gabbouj Collaboration with Moncef Gabbouj from the Tampere University of Technology in Finland. “Relational Nonlinear FIR Filters”

22. Thank you!