2007 NSF Next Generation Data Mining Symposium
Economics of privacy-preserving data mining (ICDE'07 panel)
Data Mining in Vehicular Sensor Networks: Technical and Marketing Challenges (KDD'07 talk)
Thoughts on Human Emotions, Communication Breakthroughs, and the Next Generation of Data Mining (NGDM'07 talk)

Data Mining: Next Generation Challenges and Future Directions
H. Kargupta, A. Joshi, K. Sivakumar, and Y. Yesha
MIT/AAAI Press (to be released in early 2004)

Adv ances in Distributed and Parallel Knowledge Discovery
Edited by Hillol Kargupta and Philip Chan

DIADIC Research Laboratory:

Our research is primarily focused in the area of distributed computation for data analysis and modeling. We explore algorithms, systems, and applications for environments where data, computing resources, and users are distributed.

Algorithm Development:

- Distributed Data Mining
- Peer-to-peer data mining
- Distributed Data Stream Mining
- Privacy sensitive multi-party data mining
- Mobile data mining

Systems Research and HCI
- Developing lightweight distributed data mining systems
- Energy consumption issues in data mining algorithms for lightweight applications
-Visualization issues in data mining for mobile applications

- Security and surveillance applications
- Physiological data stream mining
- Mobile portfolio manager
- VEhicle DAa Stream (VEDAS) mining and management
- Sensor network mining
- Distributed astronomy data mining grid
- Mining distributed NASA Earth Observing Satellite data streams
- Distributed web mining

Ongoing Projects


Selected Publications

Sponsoring Organizations

Website Designed by: James G. Cornell