DIAL (Data, Inference Analysis, and Learning) - Nitesh Chawla's Research Group

About

We apologize for not all information of all our projects/publications available on the website. We will be updating it shortly. In the meantime, please email us at dial@nd.edu with any questions regarding our projects/papers.

Welcome to DIAL (Data, Inference Analysis, and Learning) -- Professor Nitesh Chawla's research group.

"Print, film, magnetic, and optical storage media produced about 5 exabytes of new information in 2002. Ninety-two percent of the new information was stored on magnetic media, mostly in hard disks. " ~Berkeley 2003

This data pervades every sector of human interest, medicine, biology, commerce, WWW, security, fraud, space research, and others, and within it are (potentially) useful information, patterns, associations, and even anomalies. Our main research focus is on the process of automatic discovery and synthesizing useful knowledge from large sets of data. This work taps into many frameworks from related fields such as data mining, machine learning, pattern recognition, databases, probability, statistics, information theory and visualization. Such a broad framework allows the application into a variety of real-world applications.

Our work ranges a diverse set of problems including class imbalance, data segmentation, bias detection, parallel data mining, graph mining and clustering, collaborative filtering, and biometrics.


	News September 2008: "Start Globally, Optimize Locally, Predict Globally: Improving Performance on Unbalanced Data" was accepted to the 8th IEEE International Conference on Data Mining. September 2008: "Scaling Classifiers to Cloud Computers" was accepted to the 8th IEEE International Conference on Data Mining. September 2008: "Data Mining for Climate Change and Impacts" was accepted to the ICDM Workshop on Spatial / Spatio-Temporal Data Mining. July 2008: Karsten Steinhaeuser takes a summer internship at Oak Ridge National Laboratory July 2008: "CARE for your future: Collaboartive Assessment and Recommendation Engine for prospective healthcare" accepted at ACM SIGKDD Workshop on Mining Medical Data. More News About We apologize for not all information of all our projects/publications available on the website. We will be updating it shortly. In the meantime, please email us at dial@nd.edu with any questions regarding our projects/papers. Welcome to DIAL (Data, Inference Analysis, and Learning) -- Professor Nitesh Chawla's research group. "Print, film, magnetic, and optical storage media produced about 5 exabytes of new information in 2002. Ninety-two percent of the new information was stored on magnetic media, mostly in hard disks. " ~Berkeley 2003 This data pervades every sector of human interest, medicine, biology, commerce, WWW, security, fraud, space research, and others, and within it are (potentially) useful information, patterns, associations, and even anomalies. Our main research focus is on the process of automatic discovery and synthesizing useful knowledge from large sets of data. This work taps into many frameworks from related fields such as data mining, machine learning, pattern recognition, databases, probability, statistics, information theory and visualization. Such a broad framework allows the application into a variety of real-world applications. Our work ranges a diverse set of problems including class imbalance, data segmentation, bias detection, parallel data mining, graph mining and clustering, collaborative filtering, and biometrics.

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