MIT Computer Science and Artificial Intelligence Laboratory

100.6k citations
1.9k papers ·

Impact in

Papers in

MIT Computer Science and Artificial Intelligence Laboratory

1.8k papers receiving 97.5k citations

Peers

MIT Computer Science and Artificial Intelligence Laboratory
Comparison fields: 5 of 233
  • Computer Vision and Pattern Recognition 29.4k
  • Computer Graphics and Computer-Aided Design 4.9k
  • Computer Networks and Communications 25.9k
  • Hardware and Architecture 6.8k
  • Artificial Intelligence 31.8k
Replace Institute of Electrical and Electronics Engineers with:
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MIT Computer Science and Artificial Intelligence Laboratory relative to Institute of Electrical and Electronics Engineers United States Institute of Electrical and Electronics Engineers's profile →
Citations per field
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Citations per year

Countries citing scholars working at MIT Computer Science and Artificial Intelligence Laboratory

Since Specialization
Citations

This map shows the geographic impact of research produced by authors working at MIT Computer Science and Artificial Intelligence Laboratory. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by papers produced at MIT Computer Science and Artificial Intelligence Laboratory with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites MIT Computer Science and Artificial Intelligence Laboratory more than expected).

Fields of papers published by authors at MIT Computer Science and Artificial Intelligence Laboratory

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers affiliated with MIT Computer Science and Artificial Intelligence Laboratory at the time of their publication. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers affiliated with MIT Computer Science and Artificial Intelligence Laboratory at the time of their publication.

About MIT Computer Science and Artificial Intelligence Laboratory

In recent decades, authors affiliated with MIT Computer Science and Artificial Intelligence Laboratory have published 1.9k papers, which have received a total of 100.6k indexed citations . Scholars at this organization have produced 158 papers in Computer Graphics and Computer-Aided Design, 182 papers in Hardware and Architecture, 512 papers in Computer Vision and Pattern Recognition, 521 papers in Computer Networks and Communications and 743 papers in Artificial Intelligence on the topics of Parallel Computing and Optimization Techniques (149 papers), Advanced Vision and Imaging (145 papers), Computer Graphics and Visualization Techniques (142 papers), Distributed systems and fault tolerance (139 papers), Advanced Data Storage Technologies (126 papers), Natural Language Processing Techniques (110 papers), Topic Modeling (110 papers) and Cryptography and Data Security (89 papers). Their work is cited by papers focused on Computer Vision and Pattern Recognition (29.4k citations), Computer Graphics and Computer-Aided Design (4.9k citations), Computer Networks and Communications (25.9k citations), Hardware and Architecture (6.8k citations) and Artificial Intelligence (31.8k citations). Authors at MIT Computer Science and Artificial Intelligence Laboratory collaborate with scholars in United States, United Kingdom and Israel and have published in prestigious journals including ACM Transactions on Graphics, Proceedings of the VLDB Endowment, Computer Graphics Forum, ACM SIGPLAN Notices and Lecture notes in computer science. Some of MIT Computer Science and Artificial Intelligence Laboratory's most productive authors include Frédo Durand, William T. Freeman, Hari Balakrishnan, Nickolai Zeldovich, Samuel R. Madden, Dina Katabi, Vinod Vaikuntanathan, James Glass, Wojciech Matusik and M. Frans Kaashoek.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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