This is in response to the call for workshop proposals to SIAM DM 2004.
We are requesting for a full-day workshop.

                        8th International Workshop on
                       High Performance Data Mining:
                                (HPDM'05)

             Workshop History: This is the 8th workshop on this
             theme held annually. The first four held in conjunction
             with IPDPS were held at Orlando ( HPDM'98), San
             Juan ( HPDM'99), Cancun (HPDM'00). and San
             Francisco (HPDM'01). Over the last three years the workshop has
	     invited papers in the areas of  
             mobile and location-aware data mining issues,
             (HPDM:RLM'02), pervasive and stream datamining (HPDM:PDS'03),
	     and grid data mining (HPDM:GRID'04).
             Traditionally, the workshop has been held
             along-side the SIAM conference.  

            Over
            the years the definition of high performance computing
            has taken on various forms as a function of the types of
            technical and creative uses and the underlying
            semantics of the applications driving them. Traditional
            definitions often refer to the problem of using high end
            parallel computers to meet the need of scientific
            applications. However, high performance computing
            can also include the need for fast sequential algorithms
            that target memory and I/O performance. The last
            decade has seen the growth and importance of grid
            computing where resources and data are physically
            distributed. This has led to the development of high
            performance distributed algorithms over the
            computational grid. This year the workshop welcomes papers
	    on all aspects of high performance data mining.
	    Topics of interest include but are not limited to:

                Grid-based data mining algorithms and systems

                Distributed techniques for incremental,
                exploratory and interactive mining. 

                Distributed techniques for security, privacy preserving
                data mining.

                Peer-to-Peer Data Mining

                High performance data stream mining and management. 

                Resource and location-aware mining algorithms. 

                Data mining in mobile environments. 

                Theoretical foundations for resource-aware mining
                in a mobile, streaming and/or distributed environment.

                Systems support for resource and location aware
                data mining. 

                Efficient, scalable, disk-based, parallel and
                distributed algorithms for large-scale data mining
                and pre-procesing and post-processing tasks. 

                Parallel or distributed frameworks for stream management,
                KDD systems, and parallel or distributed mining. 

                Applications of parallel and distributed data
                mining (PDDM) in business, science, engineering,
                medicine, and other disciplines. 

          The organizers plan to have invited talk(s) and 
          a panel on this year's focus area. 
          In addition it is
          anticipated that there will be several contributed sessions
          and one invited session on various topics of interest to
          the workshop. 


PC Co-Chairs

Salvatore Orlando, University of Venice, Italy 
Krishnamoorthy Sivakumar, Washington State University, USA

Steering Committee

Hillol Kargupta, UMBC
Vipin Kumar, UMN
Srinivasan Parthasarathy, Ohio State
David Skillicorn, Queens University
Mohammed Zaki, RPI

A list of 30+ researchers with interest in attending, and
submitting to the workshop. 
# G. Agrawal , Ohio State University  
# E. Bertino, DSI, University of Milan, Italy 
# D. Cheung, University of Hong Kong, Hong Kong 
# A. Choudhary, Northwestern University, USA 
# J. Gehrke, Cornell University, USA 
# R. Grossman, University of Illinois-Chicago, USA  
# Ron Musick, iKuni Inc., USA  
# G. Ostrouchov, Oak Ridge National Labs, USA  
# S. Orlando, University of Venice, Italy  
# B. H. Park , Oak Ridge National Labs, USA  
# Y. Pan, Georgia State University, USA  
# R. Rastogi , Lucent Technologies, USA  
# P. Scheuermann, Northwestern University  
# K. Sivakumar, Washington State University, USA  
# D. Talia, DEIS, University of Calabria, Italy  
# G. Williams, CSIRO, Aust. Nat. Univ., Australia
# V. Kumar, UMN, USA
# H. Kargupta, UMBC, USA
# S. Parthasarathy, Ohio State, USA
# D. Skillikorn, Queens U., Canada
# M. Zaki, RPI, USA
# C. Caruthers, RPI, USA
# J. Saltz, OSU, USA
# S. Mcclean, Ireland
# N. Samatova, ORNL, USA
# A. Grama, Purdue, USA
# C. Clifton, Purdue, USA
# Yike Guo, Imperial College, UK
# Marios Dikaiakos, Univ. of Cyprus, Cyprus
# José Gutiérrez, Universidad de Cantabria, Spain
# Ning Zhong, Maebashi Institute of Technology, Japan


Biography of PC Co-Chairs


Biography of Steering Committee Submitter:

Srinivasan Parthasarathy is an assistant professor of computer science
at Ohio State University. His interests are in parallel and distributed
systems and data mining. He has published over 60 articles in peer
reviewed journals and conferences related to these topics including two
best paper awards at IEEE ICDM 2002 and SIAM Data Mining 2003. 
His work in these areas are funded through grants from
the National Science Foundation (including an NSF CAREER grant), 
the Department of Energy (including a DOE
Early Career Principal Investigator Grant), 
Pfizer Inc. and SBC (formerly Ameritech) Inc.
He served as the lead co-chair for the HPDM workshop in 2002 and 2003.