Next Generation Data Mining

The world is facing a number of critical challenges. Finding the next generation of solutions for energy supply, reducing greenhouse emissions, and transportation problems is critical to sustain the world and our civilization. Energy crisis is a major challenge that needs to be addressed for sustaining and further developing the world. Greenhouse emissions is widely believed to be connected with energy consumption. Transportation system has significant effect on the energy consumption and on greenhouse emissions. Many problems related to greenhouse emissions and transportation industry are critically connected to the consumption and supply of energy. Information processing and advanced data analysis techniques are likely to play important roles in solving these problems for the next generation.

Efficient production, distribution, and consumption of existing and alternate energy would require supporting information processing networks in order to adaptively control and protect the underlying physical systems. Understanding the effects of greenhouse emissions requires advanced data analysis techniques for understanding remotely sensed data. Reducing the carbon footprints of buildings, vehicles, and airplanes would require continuous monitoring of sensors and detecting deviation from desired behavior. Designing the next generation of transportation network becomes particularly challenging in the context of increasing demand for energy supplies and reducing greenhouse emissions. Sensor networks for highways and vehicles equipped with diagnostic data bus along with the availability of machine-to-machine wireless communication networks are going to make the role of advanced data mining techniques very important in the transportation industry. Computing in itself is under scrutiny from the perspective of its effect on greenhouse emissions and pollution. We need to pay close attention to the environmental impacts of computing and the supporting infrastructure. Overall, we need to explore technology for sustainable computing and computing technology for a sustainable world.

The “Next Generation Data Mining (NGDM’09) Summit: Dealing with Energy Crisis, Greenhouse Emissions, and Transportation Challenges” will bring together data mining researchers, scientists and engineers from a diverse background along with domain experts.

NGDM’09 will focus on the following areas:

1)      Energy crisis, information processing and data mining
2)      Greenhouse emissions, climate changes, and data mining
3)      Transportation, emissions, and data mining

The summit will generate a report based on the presentations and discussions of the participants.


Chandra Bhat, University of Texas at Austin
Kirk Borne, George Mason University
Alok Choudhary, Northwestern University
Umesh Dayal, HP Labs
Wei Fan, IBM T. J. Watson Research Laboratory
Douglas Fisher, National Science Foundation
Auroop Ganguly, Oak ridge National Laboratory
Johannes Gehrke, Cornell University

Carla Gomes, Cornell University
Vipin Kumar, University of Minnesota
Rich Lechner, IBM
Edward Maibach, George Mason University
Mark McGranaghan, Electric Power Research Inst.
Paul Melby, MITRE Corporation
Robert Neff, UMBC
Dino Pedreschi, Univ. of Pisa & Northeastern Univ,
Krishna Rajan, Iowa State University
Shashi Shekhar, University of Minnesota
Ashok Srivastava, NASA Ames Research Center
Eugene Tierney, US Env. Protection Agency
Ramasamy Uthurusamy, General Motors (Ret.)
Brian Worley, Oak Ridge National Laboratory
Philip Yu, University of Illinois at Chicago
Vince Mow, Mactec Federal Programs
Chris Stock, Verizon