Murat Kantarcioglu
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Murat Kantarcioglu | |
|---|---|
| Nationality | Turkish, American |
| Alma mater | Middle East Technical University, Purdue University |
| Known for | Research in data security, privacy, machine learning |
| Awards | NSF CAREER award, AMIA Homer R Warner Award, IEEE ISI Technical Achievement Award |
| Scientific career | |
| Fields | Computer Science, Data Security, Privacy |
| Institutions | University of Texas at Dallas |
| Thesis | Privacy-preserving distributed data mining and processing on horizontally partitioned data (2005) |
| Doctoral advisor | Chris Clifton |
| Notable students | Mehmet Kuzu, Ali Inan |
Murat Kantarcioglu is a Turkish-American computer scientist and the Ashbel Smith Professor of Computer Science at the University of Texas at Dallas (UTD).[1] His research interests lie in the areas of data security, privacy, and machine learning.[2]
Early life and education
Dr. Kantarcioglu received his Bachelor of Science degree in Computer Engineering from Middle East Technical University, Turkey, in 2000. He went on to complete his Master of Science degree in Computer Science at Purdue University in 2002. In 2005, he obtained his Ph.D. in Computer Science from Purdue University, under the supervision of Dr. Chris Clifton.[3]
Research and career
After completing his doctoral studies, Dr. Kantarcioglu joined the faculty of the University of Texas at Dallas in 2005, where he currently serves as the Ashbel Smith Professor of Computer Science. He has made significant contributions to the field through his research in data security and privacy, with a particular focus on issues raised by data mining, machine learning, social networks, databases, healthcare, and cryptography. His work has garnered recognition, including the NSF CAREER award, the AMIA Homer R Warner Award, and the IEEE ISI Technical Achievement Award.[4]
Dr. Kantarcioglu's research aims to develop efficient technologies that extract valuable information from data while preserving privacy and ensuring security. He has contributed to various areas, such as fraud detection, botnet detection, risk assessment, and the use of blockchain technology for secure data sharing.
References
External links
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