Ehsan Adeli

14.5k total citations · 2 hit papers
139 papers, 4.6k citations indexed

About

Ehsan Adeli is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Ehsan Adeli has authored 139 papers receiving a total of 4.6k indexed citations (citations by other indexed papers that have themselves been cited), including 58 papers in Computer Vision and Pattern Recognition, 53 papers in Artificial Intelligence and 32 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Ehsan Adeli's work include Functional Brain Connectivity Studies (20 papers), Domain Adaptation and Few-Shot Learning (15 papers) and Machine Learning in Healthcare (14 papers). Ehsan Adeli is often cited by papers focused on Functional Brain Connectivity Studies (20 papers), Domain Adaptation and Few-Shot Learning (15 papers) and Machine Learning in Healthcare (14 papers). Ehsan Adeli collaborates with scholars based in United States, South Korea and China. Ehsan Adeli's co-authors include Dinggang Shen, Jun Zhang, Kilian M. Pohl, Dong Nie, Mingxia Liu, Qingyu Zhao, J. Mahjoobi, Juan Carlos Niebles, Mingxia Liu and Han Zhang and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and IEEE Transactions on Pattern Analysis and Machine Intelligence.

In The Last Decade

Ehsan Adeli

131 papers receiving 4.5k citations

Hit Papers

TransUNet: Rethinking the... 2024 2026 2024 2024 50 100 150 200 250

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Ehsan Adeli 1.6k 1.6k 1.2k 800 533 139 4.6k
Weidong Cai 2.4k 1.5× 3.0k 1.9× 2.1k 1.7× 792 1.0× 432 0.8× 303 7.0k
Yuanjie Zheng 1.6k 1.0× 2.4k 1.5× 3.6k 3.1× 834 1.0× 1.5k 2.8× 244 8.9k
Baiying Lei 3.1k 2.0× 2.6k 1.7× 2.4k 2.0× 1.0k 1.3× 844 1.6× 296 8.1k
Guorong Wu 1.7k 1.1× 2.5k 1.6× 2.9k 2.4× 871 1.1× 1.1k 2.1× 204 7.0k
Marc Niethammer 1.3k 0.8× 2.2k 1.4× 1.7k 1.4× 337 0.4× 319 0.6× 179 5.1k
Hamid Soltanian‐Zadeh 1.3k 0.8× 2.4k 1.5× 2.3k 1.9× 818 1.0× 1.4k 2.6× 456 7.3k
Carole H. Sudre 604 0.4× 878 0.6× 1.2k 1.0× 643 0.8× 308 0.6× 108 4.5k
Manuel Graña 1.6k 1.0× 971 0.6× 629 0.5× 286 0.4× 780 1.5× 304 4.7k
Mads Nielsen 2.2k 1.4× 4.2k 2.7× 1.5k 1.2× 357 0.4× 306 0.6× 186 8.2k

Countries citing papers authored by Ehsan Adeli

Since Specialization
Citations

This map shows the geographic impact of Ehsan Adeli's research. 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 Ehsan Adeli with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ehsan Adeli more than expected).

Fields of papers citing papers by Ehsan Adeli

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ehsan Adeli. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ehsan Adeli. The network helps show where Ehsan Adeli may publish in the future.

Co-authorship network of co-authors of Ehsan Adeli

This figure shows the co-authorship network connecting the top 25 collaborators of Ehsan Adeli. A scholar is included among the top collaborators of Ehsan Adeli based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ehsan Adeli. Ehsan Adeli is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Dai, Wei, Ehsan Adeli, Dev Dash, et al.. (2025). Developing ICU Clinical Behavioral Atlas Using Ambient Intelligence and Computer Vision. NEJM AI. 2(2). 2 indexed citations
2.
Kim, Soopil, Hee Jung Park, Philip Chikontwe, et al.. (2025). Communication Efficient Federated Learning for Multi-Organ Segmentation via Knowledge Distillation With Image Synthesis. IEEE Transactions on Medical Imaging. 44(5). 2079–2092.
3.
Peng, Wei, Jiahong Ouyang, Robert Paul, et al.. (2024). Metadata-conditioned generative models to synthesize anatomically-plausible 3D brain MRIs. Medical Image Analysis. 98. 103325–103325. 5 indexed citations
4.
Kim, Soopil, Hee Jung Park, Kyong Hwan Jin, et al.. (2024). Federated learning with knowledge distillation for multi-organ segmentation with partially labeled datasets. Medical Image Analysis. 95. 103156–103156. 15 indexed citations
5.
Turnbull, Adam, Michelle C. Odden, Christine E. Gould, et al.. (2024). A health-equity framework for tailoring digital non-pharmacological interventions in aging. Nature Mental Health. 2(11). 1277–1284. 3 indexed citations
6.
Chen, Jieneng, Jieru Mei, Xianhang Li, et al.. (2024). TransUNet: Rethinking the U-Net architecture design for medical image segmentation through the lens of transformers. Medical Image Analysis. 97. 103280–103280. 287 indexed citations breakdown →
7.
Zhao, Qingyu, Kate B. Nooner, Susan F. Tapert, et al.. (2024). The Transition From Homogeneous to Heterogeneous Machine Learning in Neuropsychiatric Research. SHILAP Revista de lepidopterología. 5(1). 100397–100397. 2 indexed citations
8.
Wang, Yanchen, Adam Turnbull, Yunlong Xu, et al.. (2024). Vision-based estimation of fatigue and engagement in cognitive training sessions. Artificial Intelligence in Medicine. 154. 102923–102923. 2 indexed citations
9.
Zhao, Qingyu, Edith V. Sullivan, Li Fei-Fei, et al.. (2024). Data-driven discovery of movement-linked heterogeneity in neurodegenerative diseases. Nature Machine Intelligence. 6(9). 1034–1045. 3 indexed citations
10.
Kim, Soopil, et al.. (2023). FedNN: Federated learning on concept drift data using weight and adaptive group normalizations. Pattern Recognition. 149. 110230–110230. 15 indexed citations
12.
Chikontwe, Philip, Soopil Kim, Kyong Hwan Jin, et al.. (2023). One-Shot Federated Learning on Medical Data Using Knowledge Distillation with Image Synthesis and Client Model Adaptation. Lecture notes in computer science. 14221. 521–531. 5 indexed citations
13.
Luo, Zelun, et al.. (2021). MOMA: Multi-Object Multi-Actor Activity Parsing. Neural Information Processing Systems. 34. 7 indexed citations
14.
Zhu, Hancan, et al.. (2020). FCN Based Label Correction for Multi-Atlas Guided Organ Segmentation. Neuroinformatics. 18(2). 319–331. 12 indexed citations
15.
Liu, Bingbin, Ehsan Adeli, Zhangjie Cao, et al.. (2020). Spatiotemporal Relationship Reasoning for Pedestrian Intent Prediction. IEEE Robotics and Automation Letters. 5(2). 3485–3492. 125 indexed citations
16.
Sabokrou, Mohammad, Mahmood Fathy, Guoying Zhao, & Ehsan Adeli. (2020). Deep End-to-End One-Class Classifier. IEEE Transactions on Neural Networks and Learning Systems. 32(2). 675–684. 78 indexed citations
17.
Xue, Jie, Kelei He, Dong Nie, et al.. (2019). Cascaded MultiTask 3-D Fully Convolutional Networks for Pancreas Segmentation. IEEE Transactions on Cybernetics. 51(4). 2153–2165. 55 indexed citations
18.
Zhao, Qingyu, Nicolas Honnorat, Ehsan Adeli, & Kilian M. Pohl. (2019). Variational Autoencoder with Truncated Mixture of Gaussians for Functional Connectivity Analysis. arXiv (Cornell University). 1 indexed citations
19.
Adeli, Ehsan, Kim‐Han Thung, Le An, Feng Shi, & Dinggang Shen. (2015). Robust feature-sample linear discriminant analysis for brain disorders diagnosis. Neural Information Processing Systems. 28. 658–666. 20 indexed citations
20.
Adeli, Ehsan, et al.. (2009). Clustering Based Non-parametric Model for Shadow Detection in Video Sequences.. IPCV. 440–445. 2 indexed citations

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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