Vladimir Vapnik

Vladimir Vapnik is a Professor of Computer Science at Royal Holloway, University of London, affiliated with the Computer Learning Research Centre. He previously held roles at AT&T Bell Laboratories and the Institute of Control Sciences in Moscow. His work spans over 30 years in computer science, theoretical and applied statistics.

• Education: Master's in Mathematics from Uzbek State University (1958)

Research focuses on foundational statistical learning theory, including the development of Support Vector Machines (SVM) and minimizing expected risk through empirical data. His contributions address pattern recognition, regression, dependency estimation, and intelligent machine construction. Key publications include Statistical Learning Theory (1998) and The Nature of Statistical Learning Theory (2000).

No specific scientific awards are listed in the provided text. His research has influenced dependency estimation, forecasting, and machine intelligence. He remains affiliated with the Foundations of Data Science initiative.