Anil Jain's research over the past thirty five years has been directed at understanding the structure of multidimensional data, which is one of the key challenges that have spurred the increased interest in data mining. His research has had profound influence on a wide variety of areas in data mining, statistical learning, and pattern recognition including unsupervised learning, error estimation, feature selection and extraction, model selection, and information fusion. In fact many of his early contributions on curse of dimensionality (IEEE Trans. Computers, 1974; IEEE Trans. SMC, 1975), data clustering (Pattern Recognition, 1976), and dimensionality reduction (Proc. ICPR, 1976; IEEE Trans. PAMI, 1979) were published before the field of data mining was formally established as a separate discipline.
In addition to theoretical contributions, his research has also advanced a number of applications including content-based image retrieval, texture modeling and segmentation, document image understanding, remote sensing, medical image analysis, fingerprint matching, face recognition, and biometric fusion.
His contributions to the area of data clustering have significantly influenced the data mining community. Jain's book, Algorithms for Clustering Data, is ranked among top 100 in the Most Cited Articles in Computer Science (over all times) and his paper "Data Clustering: A Review" (ACM Computing Surveys, 1999) is consistently ranked in the Top 10 Most Popular Magazine and Computing Survey Articles Downloaded.
He has received a number of awards, including Guggenheim fellowship, Humboldt Research award, Fulbright fellowship, IEEE Computer Society Technical Achievement award (2003), W. Wallace McDowell award (2007), and IAPR King-Sun Fu Prize (2008) for contributions to pattern recognition and biometrics. He also received the best paper awards from the IEEE Trans. Neural Networks (1996) and the Pattern Recognition journal (1987, 1991, 2005).
2008 IEEE ICDM Nomination and Evaluation Committees