Professor Vapnik gained a Master's Degree in Mathematics in 1958 from Uzbek State University in Samarkand, USSR. From 1961 to 1990, he worked at the Institute of Control Sciences in Moscow, ultimately becoming the Head of the Computer Science Research Department. He joined AT&T Bell Laboratories in Holmdel, NJ, and was appointed Professor of Computer Science and Statistics at Royal Holloway in 1995. With over 30 years of teaching and research experience in computer science and theoretical and applied statistics, Professor Vapnik has published six monographs and over a hundred research papers. A major achievement is the development of a general theory for minimizing expected risk using empirical data, leading to the invention of a new type of learning machine called the Support Vector Machine, which exhibits a high level of generalization ability. His techniques have been applied to solve problems in pattern recognition, regression estimation, and dependency forecasting. His current research is presented in significant works such as "Statistical Learning Theory" (Wiley, 1998) and "The Nature of Statistical Learning Theory" (Springer, 2000). He was elected as a new member of the National Academy of Engineering in the USA on February 10, 2006, recognizing his insights into the complexities of learning and the invention of practical machine learning algorithms. In December 2011, the Max Planck Institute for Intelligent Systems in Tuebingen, Germany, organized an "Empirical Inference Symposium" in honor of his 75th birthday anniversary.