World's Best Scientists 2026 revealed!
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Computer Science
USA
2026

D-Index & Metrics

Computer Science

D-Index
140
Citations
120482
World Ranking
63
National Ranking
36

Research.com Recognitions

  • 2026 - Research.com Computer Science in United States Leader Award
  • 2025 - Research.com Computer Science in United States Leader Award
  • 2023 - Research.com Computer Science in United States Leader Award
  • 2022 - Edward J. McCluskey Technical Achievement Award, IEEE Computer Society For contributions to Bayesian, learning and optimization-based approaches to computer vision.
  • 2022 - Research.com Computer Science in United States Leader Award

Overview

Alan L. Yuille is affiliated with Johns Hopkins University in the United States. Their research spans significant contributions in the areas of computer science and medicine, with a strong focus on computer vision, artificial intelligence, and medical imaging.

Their publication record includes frequent contributions to prominent venues such as arXiv (Cornell University), where they have published over 200 papers, as well as the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), the Proceedings of the AAAI Conference on Artificial Intelligence, Medical Image Analysis, and bioRxiv (Cold Spring Harbor Laboratory).

Major research topics covered by Alan L. Yuille include:

  • Advanced Neural Network Applications
  • Domain Adaptation and Few-Shot Learning
  • Multimodal Machine Learning Applications
  • Human Pose and Action Recognition
  • Radiomics and Machine Learning in Medical Imaging
  • Advanced Image and Video Retrieval Techniques
  • COVID-19 diagnosis using AI

Their main fields of study are:

  • Computer Science
  • Medicine

Within these fields, their subfields of expertise include:

  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Radiology, Nuclear Medicine and Imaging
  • Oncology
  • Biomedical Engineering

Frequent co-authors in their research work have been:

  • Adam Kortylewski
  • Zongwei Zhou
  • Cihang Xie
  • Yuyin Zhou
  • Angtian Wang

Recent papers by Alan L. Yuille include:

  • TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation, 2021, arXiv (Cornell University)
  • TransUNet: Rethinking the U-Net architecture design for medical image segmentation through the lens of transformers, 2024, Medical Image Analysis
  • Masked Feature Prediction for Self-Supervised Visual Pre-Training, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detection, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • When Radiology Report Generation Meets Knowledge Graph, 2020, Proceedings of the AAAI Conference on Artificial Intelligence

In 2022, Alan L. Yuille received the Edward J. McCluskey Technical Achievement Award from the IEEE Computer Society for contributions to Bayesian, learning, and optimization-based approaches to computer vision.

Best Publications

  • DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs

    Liang-Chieh Chen;George Papandreou;Iasonas Kokkinos;Kevin Murphy

  • Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs

    Liang-Chieh Chen;George Papandreou;Iasonas Kokkinos;Kevin Murphy

  • TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation

    Jieneng Chen;Yongyi Lu;Qihang Yu;Xiangde Luo

  • Region competition: unifying snakes, region growing, and Bayes/MDL for multiband image segmentation

    Song Chun Zhu;A. Yuille

  • Region competition: unifying snakes, region growing, energy/Bayes/MDL for multi-band image segmentation

    S.C. Zhu;T.S. Lee;A.L. Yuille

  • Feature extraction from faces using deformable templates

    Alan L. Yuille;Peter W. Hallinan;David S. Cohen

  • Progressive Neural Architecture Search

    Chenxi Liu;Barret Zoph;Maxim Neumann;Jonathon Shlens

  • Object Perception as Bayesian Inference

    Daniel Kersten;Pascal Mamassian;Alan L Yuille

  • Active vision

    Andrew Blake;Alan Yuille

  • The Role of Context for Object Detection and Semantic Segmentation in the Wild

    Roozbeh Mottaghi;Xianjie Chen;Xiaobai Liu;Nam-Gyu Cho

  • Attention to Scale: Scale-Aware Semantic Image Segmentation

    Liang-Chieh Chen;Yi Yang;Jiang Wang;Wei Xu

  • The Secrets of Salient Object Segmentation

    Yin Li;Xiaodi Hou;Christof Koch;James M. Rehg

  • The concave-convex procedure

    A. L. Yuille;Anand Rangarajan

  • Weakly-and Semi-Supervised Learning of a Deep Convolutional Network for Semantic Image Segmentation

    George Papandreou;Liang-Chieh Chen;Kevin P. Murphy;Alan L. Yuille

  • Deep Captioning with Multimodal Recurrent Neural Networks (m-RNN)

    Junhua Mao;Junhua Mao;Wei Xu;Yi Yang;Jiang Wang

  • Generation and Comprehension of Unambiguous Object Descriptions

    Junhua Mao;Jonathan Huang;Alexander Toshev;Oana Camburu

  • Improving Transferability of Adversarial Examples With Input Diversity

    Cihang Xie;Zhishuai Zhang;Yuyin Zhou;Song Bai

  • Feature extraction from faces using deformable templates

    A.L. Yuille;D.S. Cohen;P.W. Hallinan

  • Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image Segmentation

    Chenxi Liu;Liang-Chieh Chen;Florian Schroff;Hartwig Adam

  • Vision as Bayesian inference: analysis by synthesis?

    Alan L Yuille;Daniel Kersten

Frequent Co-Authors

Lingxi Xie
Lingxi Xie Huawei Technologies (China)
Wei Shen
Wei Shen Johns Hopkins University
Zhuowen Tu
Zhuowen Tu University of California, San Diego
Song-Chun Zhu
Song-Chun Zhu Peking University
Iasonas Kokkinos
Iasonas Kokkinos University College London
Peng Wang
Peng Wang Baidu (China)
Jason J. Corso
Jason J. Corso University of Michigan–Ann Arbor
Gregory D. Hager
Gregory D. Hager Johns Hopkins University
Song Bai
Song Bai ByteDance

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