Anima Anandkumar Google Scholar: h-index, Total Citations, and Citation Map
Anima Anandkumar's h-index is 106 (349 i10-index, 78,229+ total citations across 598+ publications) according to Google Scholar as of October 2026. Anima Anandkumar is affiliated with California Institute of Technology and NVIDIA.
Anima Anandkumar is a researcher affiliated with California Institute of Technology and NVIDIA, specializing in Machine Learning and Artificial Intelligence. Their work has been cited 78,229 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Anima Anandkumar's Citation Metrics
Bibliometric impact based on 598 indexed publications.
- H-Index
- 106
- i10-Index
- 349
- Total Citations
- 78,229
- Citing Countries
- 80
As of October 2026.
Anima Anandkumar has an h-index of 106 and 78,229 total citations across 598 publications, with research cited by institutions in 80 countries.
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SegFormer: Simple and efficient design for semantic segmentation with transformers
202111,523
Top Citing Countries
Top Citing Institutions
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Significant Contributions
Auto-detected research lines — a seminal paper and the follow-up work building on it. Review and edit before using in a petition. Each Free PDF opens in a new tab — EB-1A organises this into the structure USCIS applies to Criterion 5 of 8 CFR § 204.5(h)(3)(v); EB-1B re-frames it under § 204.5(i)(3) (outstanding researcher); NIW presents it under prong 2 of Matter of Dhanasar.
8 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher pioneered neural operator frameworks for solving partial differential equations, establishing a foundational approach that has been widely adopted for accelerating scientific simulations and design.
The researcher developed multipole and Fourier neural operators to solve parametric PDEs on general geometries, establishing a foundational framework for operator learning in scientific computing.
The researcher developed SegFormer, a simple and efficient transformer-based architecture for semantic segmentation that has become a widely adopted standard in computer vision.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Anima Anandkumar's research
Anima Anandkumar is a researcher in Machine Learning and Artificial Intelligence at California Institute of Technology and NVIDIA. Their work has been cited 78,229 times across 598 publications (h-index 106), according to Google Scholar.
Their most-cited work, “SegFormer: Simple and efficient design for semantic segmentation with transformers” (2021), has accumulated 11,523 citations. Other influential work includes “Fourier Neural Operator for Parametric Partial Differential Equations” (2021) with 6,628 citations.
Citations of Anima Anandkumar's research come primarily from China, United States and United Kingdom, reflecting international research impact across 5+ countries. The interactive citation map above shows the full geographic distribution of the institutions citing this work.
