Data mining, recommender systems, learning analytics, high-performance computing, and chemical informatics; problems in health informatics, information retrieval, bioinformatics, and scientific computing. Focus in developing novel algorithms to solve existing or emerging problems and practical software tools implementing these algorithms.
George Karypis’s interests span the areas of data mining, bio-informatics, parallel processing, CAD, and scientific computing. His research in data mining is focused on developing innovative new algorithms for a variety of data mining problems including clustering, classification, pattern discovery, and deviation detection, with an emphasis on business applications and information retrieval. George also takes great joy in teaching, advising, and mentoring undergraduate and graduate students. He teaches courses on algorithms and data structures, parallel computing, data mining, and computational techniques used in bioinformatics.