World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
43
Citations
13398
World Ranking
7776
National Ranking
3360

Overview

Ehsan Adeli is affiliated with Stanford University in the United States. Their research focuses primarily on the fields of Computer Science and Medicine, with significant contributions within the subfields of Computer Vision and Pattern Recognition, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Cognitive Neuroscience, and Neurology.

Adeli has published extensively, with topics covering Functional Brain Connectivity Studies, Machine Learning in Healthcare, Human Pose and Action Recognition, Anomaly Detection Techniques and Applications, Advanced Neuroimaging Techniques and Applications, Generative Adversarial Networks and Image Synthesis, and Domain Adaptation and Few-Shot Learning.

Frequent coauthors include Kilian M. Pohl, Qingyu Zhao, Li Fei-Fei, Juan Carlos Niebles, and Edith V. Sullivan.

Adeli's publication record spans various venues, with notable frequency in:

  • arXiv (Cornell University)
  • Lecture Notes in Computer Science
  • UNC Libraries
  • Medical Image Analysis
  • IEEE Robotics and Automation Letters

The scientist has contributed to recent papers such as:

  • "TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation," 2021, arXiv (Cornell University)
  • "On the Opportunities and Risks of Foundation Models," 2021, arXiv (Cornell University)
  • "TransUNet: Rethinking the U-Net architecture design for medical image segmentation through the lens of transformers," 2024, Medical Image Analysis
  • "Medical Image Segmentation Review: The Success of U-Net," 2024, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "Spatiotemporal Relationship Reasoning for Pedestrian Intent Prediction," 2020, IEEE Robotics and Automation Letters

Adeli has also authored books with Springer Science+Business Media, titled "Predictive Intelligence in Medicine," published in 2020, 2021, and 2022 with citations for each edition.

Best Publications

  • TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation

    Jieneng Chen;Yongyi Lu;Qihang Yu;Xiangde Luo

  • On the Opportunities and Risks of Foundation Models.

    Rishi Bommasani;Drew A. Hudson;Ehsan Adeli;Russ Altman

  • Adversarially Learned One-Class Classifier for Novelty Detection

    Mohammad Sabokrou;Mohammad Khalooei;Mahmood Fathy;Ehsan Adeli

  • TransUNet: Rethinking the U-Net architecture design for medical image segmentation through the lens of transformers

    Unknown

  • Landmark-based deep multi-instance learning for brain disease diagnosis

    Mingxia Liu;Jun Zhang;Ehsan Adeli;Dinggang Shen;Dinggang Shen

  • 3D Deep Learning for Multi-modal Imaging-Guided Survival Time Prediction of Brain Tumor Patients.

    Dong Nie;Han Zhang;Ehsan Adeli;Luyan Liu

  • It Is Not the Journey But the Destination: Endpoint Conditioned Trajectory Prediction

    Karttikeya Mangalam;Harshayu Girase;Shreyas Agarwal;Kuan-Hui Lee

  • Joint Classification and Regression via Deep Multi-Task Multi-Channel Learning for Alzheimer's Disease Diagnosis

    Mingxia Liu;Jun Zhang;Ehsan Adeli;Dinggang Shen

  • Spatio-Temporal Graph for Video Captioning With Knowledge Distillation

    Boxiao Pan;Haoye Cai;De-An Huang;Kuan-Hui Lee

  • Rethinking Architecture Design for Tackling Data Heterogeneity in Federated Learning

    Unknown

  • High-Resolution Encoder–Decoder Networks for Low-Contrast Medical Image Segmentation

    Sihang Zhou;Dong Nie;Ehsan Adeli;Jianping Yin

  • Multi-Channel 3D Deep Feature Learning for Survival Time Prediction of Brain Tumor Patients Using Multi-Modal Neuroimages

    Dong Nie;Junfeng Lu;Han Zhang;Ehsan Adeli

  • 3-D Fully Convolutional Networks for Multimodal Isointense Infant Brain Image Segmentation

    Dong Nie;Li Wang;Ehsan Adeli;Cuijin Lao

  • Spatiotemporal Relationship Reasoning for Pedestrian Intent Prediction

    Bingbin Liu;Ehsan Adeli;Zhangjie Cao;Kuan-Hui Lee

  • Inherent Structure-Based Multiview Learning With Multitemplate Feature Representation for Alzheimer's Disease Diagnosis

    Mingxia Liu;Daoqiang Zhang;Ehsan Adeli;Dinggang Shen

  • Spatio-Temporal Graph Convolution for Resting-State fMRI Analysis.

    Soham Gadgil;Qingyu Zhao;Adolf Pfefferbaum;Edith V. Sullivan

  • Training confounder-free deep learning models for medical applications.

    Qingyu Zhao;Ehsan Adeli;Kilian M Pohl;Kilian M Pohl

  • TransDeepLab: Convolution-Free Transformer-Based DeepLab v3+ for Medical Image Segmentation

    Unknown

  • Ethical issues in using ambient intelligence in health-care settings

    Nicole Martinez-Martin;Zelun Luo;Amit Kaushal;Ehsan Adeli

  • Action-Agnostic Human Pose Forecasting

    Hsu-Kuang Chiu;Ehsan Adeli;Borui Wang;De-An Huang

  • Joint feature-sample selection and robust diagnosis of Parkinson's disease from MRI data

    Ehsan Adeli;Feng Shi;Le An;Chong Yaw Wee

  • Imitation Learning for Human Pose Prediction

    Borui Wang;Ehsan Adeli;Hsu-Kuang Chiu;De-An Huang

  • AVID: Adversarial Visual Irregularity Detection

    Mohammad Sabokrou;Masoud Pourreza;Mohsen Fayyaz;Rahim Entezari

  • Image to Images Translation for Multi-Task Organ Segmentation and Bone Suppression in Chest X-Ray Radiography

    Mohammad Eslami;Solale Tabarestani;Shadi Albarqouni;Ehsan Adeli

  • Deep Relative Attributes

    Yaser Souri;Erfan Noury;Ehsan Adeli

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