I am in the process of updating the website with research projects
and publications. Currently, it is just a container of recent news
highlights. Feel free to drop me a line, if you have any queries.
I readily provide data sets (particularly highly unbalanced data sets) and software that I or my group have
developed. So, please email me if you are looking for that.
Recent News/Highlights
March 2008
"Modeling Product Space as Network for Causality and Proftability",
Accepted in Fourth Symposium on Statistical Challenges in Electronic
Commerce Research ,
Troy Raeder and Nitesh Chawla
February 2008
"Automatically countering imbalance and its empirical relationship to
cost", Published in
Data Mining and Knowledge Discovery Journal ,
Nitesh Chawla, David Cieslak, Larry Hall, Ajay Joshi
January 2008
"A Framework for Monitoring Classifiers' Performance: When and Why
Failure Occurs?", Accepted in
Knowledge and Information Systems Journal ,
David Cieslak and Nitesh Chawla
January 2008
"Detecting Fractures in Classifier Performance", selected
in Best of IEEE ICDM'07,
December 2007
"Analyzing PETs performance on imbalanced datasets when training
and testing distributions differ", Accepted in
PAKDD Conference,
Nitesh Chawla and David Cieslak
November 2007
"Community detection in large social networks", Accepted in
Social Computing, Behavioral Modeling, and Prediciton Workshop,
Karsten Steinhaeuser and Nitesh Chawla.
July 2007
"CSR-AES: Troubleshooting Large Scale Computing Grids with Machine
Learning Techniques", Nitesh Chawla (PI), Xiaohui Song, Shaowen Wang, and
Douglas Thain, National Science Foundation, August 2007-2008.
"Detecting Fracture Points in Classifier Performance", Accepted as a regular paper in
IEEE ICDM , David Cieslak and Nitesh Chawla
"Learning to Predict Gender from IRISES", Accepted in
IEEE BTAS, Vince Thomas, Nitesh Chawla, Kevin Bowyer, Pat Flynn.
May 2007
"Enhanced Situational Awareness: Application of DDDAS Concepts to Emergency and Disaster Management ",
Gregory R. Madey, Albert-László Barabási, Nitesh V. Chawla, et al.
in International Conference on Computational Science, serial Lecture Notes in Computer Science, V. N. Alexandrov, G. D. van Albada, P. M. A. Sloot, and J. Dongarra, Eds., May 2007.
"Authentication Anomaly detection: A case study on a VPN", Mike Chapple,
Nitesh V. Chawla and Aaron Striegel. To appear in
ACM MineNet 2007
"Anomaly detection in mobile communication networks." Alec Pawling,
Nitesh V. Chawla, Greg Madey. To appear in the Computational and
Mathematical Organization Theory (CMOT) Journal .
April 2007
"Actively Exploring Creation of Face Spaces for Improved Face
Recognition", Nitesh V. Chawla and Kevin Bowyer. To appear in
AAAI 2007
February 2007
"Exploiting Diversity in Ensembles: Improving Performance on
Unbalanced Datasets", Nitesh V. Chawla and Jared Sylvester. To appear in
MCS 2007
October 2006
Research Grant "Face Recognition From Video", from DOJ, jointly with Professors Bowyer (PI) and Flynn.
"A Black-Box Approach to Query Cardinality Estimation", Tanu Malik, Randal Burns, and Nitesh V. Chawla To appear in CIDR, 2007.
September 2006
"Resource Access Pattern Mining for Dynamic Energy Management", Dinesh Rajan, Christian Poellabauer, and Nitesh V. Chawla, Proceedings of the Workshop on Autonomic Computing: A New Challenge for Machine Learning, ECML/PKDD, Berlin, Germany, September 2006.
"Exploiting Thread-level Parallelism to Build Decision Trees", Karsten Steinhaueser, Nitesh V. Chawla, Peter Kogge. Proceedings of the Workshop on Parallel and Distributed Data Mining, ECML/PKDD, Berlin, Germany, 2006.
July 2006
"Pricing Scheme for Benefit Scoring," Nitesh V. Chawla, Xiangning Li. Accepted in the 2nd Workshop on Utility Based Data Mining, KDD 2006.
"Estimating Query Result Sizes for Proxy Caching in Scientific Database Federations," Tanu Malik, Randal Burns, Nitesh V. Chawla, Alex Szalay. Accepted in Supercomputing2006.
June 2006
"Evaluation of Summarization Schemes for Learning in Streams," Alec Pawling, Nitesh V. Chawla, Amitabh Chaudhary. Accepted in 10th European Conference on Principles and Practice of Knowledge Discovery in
Databases (PKDD).
May 2006
"Anomaly Detection in a Mobile Communication Network", Alec Pawling, Nitesh V. Chawla, Greg Madey. Accepted in Annual Conference of the North American Association for Computational Social and Organizational Science (NAACSOS) --- Best Student Paper Award.
April 2006
"Evaluating Calibration of Probability Estimation Trees", Nitesh V. Chawla, David Cieslak. Accepted in Proceedings of the AAAI Workshop on the Evaluation Methods in Machine Learning, Boston, July 2006.
"Towards Learning-based Sensor Management," Karsten Steinhaeuser, Nitesh V. Chawla, Christian Poellabauer, Accepted in Proceedings of the First Workshop on Tackling Computer Systems Problems with Machine Learning Techniques (SYSML), SIGMETRICS, France, June 2006.
March 2006
Department of Defense University Research Instrumentation Program (DURIP) award (jointly with Prof. Poellabauer (PI) and Prof. Thain), April 2006-2007.
"Troubleshooting Distributed Systems via Data Mining," David Cieslak, Douglas Thain, Nitesh V. Chawla. Accepted in Hot Topics Sessions: 15th IEEE International Symposium on High Performance Distributed Computing (HPDC-15).
"Evolutionary Ensemble Creation and Thinning", Jared Sylvester, Nitesh V. Chawla. Accepted in IEEE International Joint Conference on Neural Networks (IJCNN).
January 2006
Paper, "Combating Imbalance in Network Intrusion Data", David Cieslak, Nitesh V. Chawla and Aaron Striegel, accepted in the IEEE International Conference on Granular Computing as a full paper.