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Best Universities for Computer Vision in the World

Updated: February 29, 2024

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Below is a list of best universities in the World ranked based on their research performance in Computer Vision. A graph of 108M citations received by 5.28M academic papers made by 4,264 universities in the World was used to calculate publications' ratings, which then were adjusted for release dates and added to final scores.

We don't distinguish between undergraduate and graduate programs nor do we adjust for current majors offered. You can find information about granted degrees on a university page but always double-check with the university website.

1. University of California - Berkeley

For Computer Vision

2. Stanford University

3. Massachusetts Institute of Technology

4. University of Illinois at Urbana - Champaign

5. Carnegie Mellon University

6. California Institute of Technology

7. University of Oxford

8. Tsinghua University

9. University of Cambridge

10. University of Michigan - Ann Arbor

11. University of Tokyo

12. University of Washington - Seattle

13. Harvard University

14. University of Toronto

15. University of Texas at Austin

16. Princeton University

17. University of California - Los Angeles

18. University College London

19. University of Arizona

20. Johns Hopkins University

21. University of Maryland - College Park

22. University of California-San Diego

23. Federal Institute of Technology Lausanne

24. University of Wisconsin - Madison

25. Georgia Institute of Technology

26. Cornell University

27. Swiss Federal Institute of Technology Zurich

28. Shanghai Jiao Tong University

29. Nanyang Technological University

30. University of British Columbia

31. Harbin Institute of Technology

32. Pennsylvania State University

33. University of Southern California

34. Imperial College London

35. Ohio State University

36. Columbia University

37. Catholic University of Leuven

38. National University of Singapore

39. Zhejiang University

40. University of Minnesota - Twin Cities

41. Yale University

42. New York University

43. University of Hong Kong

44. University of Pennsylvania

45. Beihang University

46. Technical University of Munich

47. Delft University of Technology

48. Peking University

49. Technion - Israel Institute of Technology

50. University of California - Santa Barbara

51. University of Chicago

52. Huazhong University of Science and Technology

53. Wuhan University

54. Xidian University

55. University of Science and Technology of China

56. McGill University

57. Purdue University

58. Xi'an Jiaotong University

59. University of Electronic Science and Technology of China

61. University of Sydney

62. Seoul National University

63. University of California - Santa Cruz

64. Michigan State University

65. University of Florida

66. RWTH Aachen University

67. Australian National University

68. Hong Kong Polytechnic University

69. University of Waterloo

70. Tel Aviv University

71. Kyoto University

72. Northwestern Polytechnical University

73. University of Manchester

74. Osaka University

75. Chinese University of Hong Kong

76. Texas A&M University - College Station

77. Pierre and Marie Curie University

78. University of North Carolina at Chapel Hill

79. Northwestern University

80. National University of Defense Technology

81. Beijing Institute of Technology

82. Arizona State University - Tempe

83. University of California - Irvine

84. Rutgers University - New Brunswick

85. Heidelberg University - Germany

86. University of California - Davis

87. University of New South Wales

88. National Taiwan University

89. University of Rochester

90. University of Amsterdam

91. University of Virginia

92. Hong Kong University of Science and Technology

93. University of Colorado Boulder

94. University of Edinburgh

95. National Chiao Tung University

96. University of Alberta

97. Duke University

98. Karlsruhe Institute of Technology

99. Boston University

100. Western University

Computer Science subfields in the World

CSRankings: Computer Science Rankings

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This ranking is designed to identify institutions and faculty actively engaged in research across a number of areas of computer science, based on the number of publications by faculty that have appeared at the most selective conferences in each area of computer science (see the FAQ for more details).

We gratefully acknowledge the generous support of our sponsors, including Stony Brook University . Sponsor CSrankings

Prominent mentions of CSrankings: CMU ( 1 , 2 ) | Edinburgh | Michigan | Rutgers | Technion | Yann LeCun | John Regehr | Charles Sutton

CSRankings by Emery Berger is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License . Based on a work at https://github.com/emeryberger/CSrankings . Follow @csrankings for updates. Copyright 2017-2023 © Emery Berger

computer science open rankings

Rankings are an ideology . Each is biased in its own way. So choose and combine existing rankings to generate your preferred meta ranking for computer science programs in the United States and Canada. Ranking sources represent: reputation ( U.S. News * U.S. News provides data for universities in the United States and Maclean's provides data for universities in Canada ), faculty publications ( csrankings.org * The rankings shown under the csrankings.org column may differ from their website because of different subfields and implementation of geometric mean count. ), academic placement ( placement rank ), and recognition ( best paper awards ). Use this to find the best computer science program for you in artificial intelligence, systems, or theory.

by Alice Marbach, Jeff Huang, Long Do, Shaun Wallace, and others who contributed the original ranking sources.

ranking source

A ranking based on reputation of graduate programs, compiled from the survey responses of academics to produce a peer assessment score per university. Click here and here for more information.

This ranking measures research publications by professors across the field of computer science. Publications occurring in selected conferences in the year 2010 or later are counted based on the proportion of authors that are professors at that institution. The numbers we report under the csrankings column might differ from csrankings.org because while we use the same formula (geometric mean count) we have a different implementation and different subfields. Click here for more information.

Ranking based on placement of students from an institution into faculty positions. The data comes from a publicly-editable dataset of professor profiles . The university where a professor got their bachelors or doctorate is treated as the source node in the Pagerank algorithm, where the score is generated from. See the original scores for the PageRank calculations.

This ranking measures papers from 30 top computer science conferences recognized as "best papers". Points are assigned to schools based on author affiliation and their position in the author list based on a decreasing exponential scale. See the best papers page for the full listing.

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"This Top Ten ranking in Computer Vision is a tribute to the AI Institute's successful hiring through the SUNY Empire Innovation Program,” said Steven Skiena, Director of the AI Institute. “We took a good program to one of the best in the country--and now we are in position to make it even better!"

The Department of Computer Science’s Computer Vision Lab was founded in 2001 by Professor Dimitris Samaras . The group’s faculty includes: Samaras (Director), Minh Hoai Nguyen , Allen Tannenbaum , Romeil Sandhu , David Xianfeng Gu , Haibin Ling , Michael Ryoo and Zhaozheng Yin . Ling, Ryoo and Yin recently joined the department as SUNY Empire Innovation Program professors. Prior to the opening of the Computer Vision Lab, Distinguished Professor Emeritus Theo Pavlidis led research on pattern recognition.

As Director, Samaras chooses projects deeply rooted in practical problems, to inform his group's theoretical advances. “As Computer Vision matures into a major component of the Artificial Intelligence technological revolution, the ability to understand and model problems from diverse domains will be paramount,” he said. Quite often his theoretical and technological advances have come from multi-disciplinary endeavors. For example, an important application area has been Medical Image Analysis where novel Machine Learning methods for the analysis of functional  brain images and Digital Histopathology have been developed.

Samaras - Explaining visual data for Computer Vision, Computer Graphics and Medical Image Analysis, through the appropriate physical and statistical models. Application areas have been Face and Gesture Analysis, Human Activity Understanding, Shadow and Texture Classification.

Ling - Video Object Tracking, Image and Object Recognition, Visual Matching, Object Segmentation and Detection, Computer Graphics, Image Processing, Robotics, Human Computer Interaction and Augmented Reality. Federal- and industry-funded research includes Smart and Connected Health, Security and Privacy, Biodiversity Study and Surveillance.

Nguyen - Developing algorithms for Human Behavior Analysis (the actions or activities of a person or a group of people recorded on video), the interaction between hands and other objects, facial or head movements (to quantify a person’s emotional state) discovering the parts of an image or a video that attract visual attention, as well as predicting and manipulating visual attention. His analysis works on both recognition and prediction tasks.

Ryoo - Intelligent Robotics focusing on robot perception and robot action learning, enabling robots to recognize their surrounding environment as well as events/activities of interacting humans, and imitation of human actions by learning them from visual examples. He develops machine learning approaches for robots that bridge robots' visual input data to motor control (i.e., visuo-motor control policy learning). In collaboration with researchers at Google Brain, he has been working on representation learning for video data, discovering neural architectures with optimal connectivities for video understanding.

Yin - Working on Computer Vision and Machine Learning with a wide range of applications in Biomedical Image Analysis, Cyber Physical Systems, Human Robot Collaboration, Social Media Analysis, Security, and Surveillance.

For more information about the Computer Vision Lab at Stony Brook University, please visit their Website .

Institute for AI-Driven Discovery and Innovation, 251 New Computer Science Building, Stony Brook, NY 11794-2424 631-632-9026 

Best Global Universities for Artificial Intelligence

Artificial intelligence is a subcategory of computer science focusing on research to create machines that attempt to problem-solve and analyze contradictory or ambiguous information. Topics covered in this category include artificial intelligence technologies such as expert systems, fuzzy systems, natural language processing, speech recognition, pattern recognition, computer vision, decision-support systems, knowledge bases and neural networks. These are the world's top universities for artificial intelligence. Read the methodology »

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Here are the best global universities for artificial intelligence

Tsinghua university, nanyang technological university, chinese university of hong kong, university of technology sydney, national university of singapore, harbin institute of technology, university of adelaide, university of electronic science & technology of china, peking university, university of chinese academy of sciences, cas.

See the full rankings

• Clear Filters
• # 1 in Best Universities for Artificial Intelligence
• # 23 in Best Global Universities

Tsinghua University, located in northwest Beijing, China, is a public institution that traces its roots back to 1911... Read More

• # 2 in Best Universities for Artificial Intelligence
• # 30 in Best Global Universities
• # 3 in Best Universities for Artificial Intelligence  (tie)
• # 53 in Best Global Universities
• # 112 in Best Global Universities  (tie)
• # 5 in Best Universities for Artificial Intelligence
• # 26 in Best Global Universities
• # 6 in Best Universities for Artificial Intelligence
• # 196 in Best Global Universities  (tie)
• # 7 in Best Universities for Artificial Intelligence
• # 74 in Best Global Universities  (tie)
• # 8 in Best Universities for Artificial Intelligence
• # 231 in Best Global Universities  (tie)
• # 9 in Best Universities for Artificial Intelligence
• # 39 in Best Global Universities  (tie)

Peking University is a public institution that was founded in 1898, though it wasn't known by its current name until... Read More

• # 10 in Best Universities for Artificial Intelligence