Dr. Rastogi is the Director of Machine Learning at Amazon and a Fellow of ACM. He has made seminal contributions to data mining, and has been recognized globally as a technical leader and innovator. He has published over 200 papers which have been cited over 19,000 times and has an H-index of 59. Dr. Rastogi developed a series of clustering and outlier detection methods in the early days of data mining. His paper “CURE: an efficient clustering algorithm for large databases” (1998, cited 2877 times) and “ROCK: a robust clustering algorithm for categorical attributes” (1999, cited 1846 times) developed several fundamental methodologies in scalable clustering methods, which have been used extensively even now. His paper “Efficient algorithms for mining outliers from large data sets” (2000, cited 1395 times) introduced the notion of distance-based outliers that has been widely adopted in research and practice. As another example, his work “SPIRIT: sequential pattern mining with regular expression constraints” started a new research direction on constraint-based pattern mining, which was followed by many researchers.
Dr. Rastogi has been an excellent model of applying data mining research to industry practice. In 1998 Dr. Rastogi became a Distinguished Member of Technical Staff at Bell Labs, and in 1999 became a Director of the Internet Management Research Department. He became a Bell Labs Fellow in 2003. He was the Vice President of Yahoo! Labs in Bangalore and is currently serving as the Director of Machine Learning at Amazon. In these positions, Dr. Rastogi has led a series of large-scale applied data mining and data science projects.
2016 IEEE ICDM Nomination and Evaluation Committees