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LATIFUR KHAN

Dr. Khan is currently a full Professor (tenured) in the Computer Science department at the University of Texas at Dallas where he has been teaching and conducting research since September 2000. He received his Ph.D. and M.S. degrees in Computer Science from the University of Southern California in August of 2000, and December of 1996 respectively. He has received prestigious awards including the IEEE Technical Achievement Award for Intelligence and Security Informatics. He has given several keynote addresses including at the IEEE International Conference on Tools with Artificial Intelligence ICTAI 2010 in Arras, France; Third IEEE ICDM International Workshop on Semantic Aspects in Data Mining SADM 2010 , Sydney, Australia; IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing 2010, Newport Beach, California; and Pacific Asia Knowledge Discovery in Databases 2012 in Kuala Lumpur Malaysia.

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RECENT WORK

With regard to data mining, Dr. Khan considered clustering and classification problems. He has proposed and developed various data mining techniques for the analysis of stream data (e.g., text stream, malware stream, etc.). Dr. Khan is researching supervised learning algorithms to classify evolving data streams. Data streams are continuous flows of data. Examples of data streams include network traffic, sensor data, call center records and so on. Their sheer volume and speed pose a great challenge for the data mining community to mine them. Dr Khan's research group, along with the UIUC group, has presented a novel class detection technique that automatically detects novel classes in data streams by analyzing and quantifying the clustering properties. Dr. Khan's group has applied this algorithm in various domains such as intrusion detection, text mining and geospatial information management.

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