The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Vladimir Vapnik sits on this spectrum.
This scientist: 128 publications — 18th percentile
18% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 991 publications or more.
The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Vladimir Vapnik sits on this spectrum.
This scientist: 70 D-Index — 87th percentile
87% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 131 D-Index or more.
Vladimir Vapnik is affiliated with Princeton University in the United States and has contributed to the field of Computer Science, particularly through work in Artificial Intelligence and Computer Vision and Pattern Recognition. Their research spans several main topics including Neural Networks and Applications, Face and Expression Recognition, and Machine Learning and Extreme Learning Machines (ELM).
Their recent publication includes a paper titled "Reinforced SVM method and memorization mechanisms" published in 2021 in the journal Pattern Recognition. This work has been cited 61 times. Pattern Recognition is also the primary venue for their publications.
Vladimir Vapnik's career includes recognition through several awards. These include the BBVA Foundation Frontiers of Knowledge Award in 2019 and the IEEE John von Neumann Medal in 2017, awarded for the development of statistical learning theory, theoretical foundations for machine learning, and support vector machines.
Other honors include the Benjamin Franklin Medal from the Franklin Institute and the IEEE Frank Rosenblatt Award, both received in 2012, the Neural Networks Pioneer Award from the IEEE Computational Intelligence Society in 2010, and the ACM Paris Kanellakis Theory and Practice Award in 2008 for the development of Support Vector Machines.
Vapnik was also inducted as a Member of the National Academy of Engineering in 2006 for insights into the fundamental complexities of learning and inventing practical machine-learning algorithms.
Vladimir N. Vapnik
Vladimir Naumovich Vapnik
Corinna Cortes;Vladimir Vapnik
Unknown
Bernhard E. Boser;Isabelle M. Guyon;Vladimir N. Vapnik
Isabelle Guyon;Jason Weston;Stephen Barnhill;Vladimir Vapnik
Vladimir Vapnik;A. Ya. Chervonenkis
Harris Drucker;Christopher J. C. Burges;Linda Kaufman;Alex J. Smola
V.N. Vapnik
Vladimir Naumovich Vapnik
Vladimir Vapnik;Steven E. Golowich;Alex J. Smola
V. N. Vapnik
Olivier Chapelle;Vladimir Vapnik;Olivier Bousquet;Sayan Mukherjee
Vladimir Vapnik;Sayan Mukherjee
O. Chapelle;P. Haffner;V.N. Vapnik
H. Drucker;Donghui Wu;V.N. Vapnik
Asa Ben-Hur;David Horn;Hava T. Siegelmann;Vladimir Vapnik
B. Scholkopf;Kah-Kay Sung;C.J.C. Burges;F. Girosi
V. Vapnik
Jason Weston;Sayan Mukherjee;Olivier Chapelle;Massimiliano Pontil
Klaus-Robert Müller;Alex J. Smola;Gunnar Rätsch;Bernhard Schölkopf
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