World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
57
Citations
11016
World Ranking
3889
National Ranking
1840

Overview

Eric Chang is affiliated with Microsoft in the United States. Their research primarily spans the fields of Computer Science and Medicine, with significant contributions in subfields such as Computer Vision and Pattern Recognition, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Surgery, and Biophysics.

Their work addresses several main topics including AI in cancer detection, digital imaging for blood diseases, generative adversarial networks and image synthesis, radiomics and machine learning in medical imaging, medical image segmentation techniques, image retrieval and classification techniques, and cell image analysis techniques.

Chang has collaborated frequently with several researchers throughout their career. Notable frequent coauthors include Yan Xu, Yubo Fan, Maode Lai, Kailu Li, and Bingzheng Wei.

Eric Chang's publications appear in various scientific venues, with a strong presence in both interdisciplinary and technical journals. Frequent publication venues include:

  • arXiv (Cornell University)
  • Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
  • Frontiers of Medicine
  • IEEE Transactions on Medical Imaging
  • Scientific Reports

Key recent papers by Chang include:

  • Deep learning in digital pathology image analysis: a survey (2020, Frontiers of Medicine)
  • ANHIR: Automatic Non-Rigid Histological Image Registration Challenge (2020, IEEE Transactions on Medical Imaging)
  • Large Scale Image Completion via Co-Modulated Generative Adversarial Networks (2021, arXiv [Cornell University])
  • MRI Cross-Modality Image-to-Image Translation (2020, Scientific Reports)
  • Weakly supervised histopathology image segmentation with self-attention (2023, Medical Image Analysis)

Best Publications

  • Forecasting Fine-Grained Air Quality Based on Big Data

    Yu Zheng;Xiuwen Yi;Ming Li;Ruiyuan Li

  • Large scale tissue histopathology image classification, segmentation, and visualization via deep convolutional activation features.

    Yan Xu;Yan Xu;Zhipeng Jia;Zhipeng Jia;Liang-Bo Wang;Liang-Bo Wang;Yuqing Ai;Yuqing Ai

  • Deep learning of feature representation with multiple instance learning for medical image analysis

    Yan Xu;Tao Mo;Qiwei Feng;Peilin Zhong

  • Location mapping for key-point based services

    Eric Chang;Kong-Kat Wong;Difei Tang

  • MaskFlownet: Asymmetric Feature Matching With Learnable Occlusion Mask

    Shengyu Zhao;Yilun Sheng;Yue Dong;Eric I-Chao Chang

  • Predicting breast tumor proliferation from whole-slide images: The TUPAC16 challenge.

    Mitko Veta;Yujing J. Heng;Nikolas Stathonikos;Babak Ehteshami Bejnordi

  • Weakly supervised histopathology cancer image segmentation and classification

    Yan Xu;Yan Xu;Jun-Yan Zhu;Eric I-Chao Chang;Maode Lai

  • Inferring gas consumption and pollution emission of vehicles throughout a city

    Jingbo Shang;Yu Zheng;Wenzhu Tong;Eric Chang

  • Diagnosing New York city's noises with ubiquitous data

    Yu Zheng;Tong Liu;Yilun Wang;Yanmin Zhu

  • Constrained Deep Weak Supervision for Histopathology Image Segmentation

    Zhipeng Jia;Xingyi Huang;Eric I-Chao Chang;Yan Xu

  • Unsupervised 3D End-to-End Medical Image Registration With Volume Tweening Network

    Shengyu Zhao;Tingfung Lau;Ji Luo;Eric I-Chao Chang

  • Personal Media Landscapes in Mixed Reality

    Darren K. Edge;Eric Chang;Kyungmin Min

  • Unsupervised 3D End-to-End Medical Image Registration with Volume Tweening Network.

    Shengyu Zhao;Tingfung Lau;Ji Luo;Eric I-Chao Chang

  • Unsupervised Object Class Discovery via Saliency-Guided Multiple Class Learning

    Jun-Yan Zhu;Jiajun Wu;Yan Xu;Eric Chang

  • Emotion Detection from Speech to Enrich Multimedia Content

    Feng Yu;Eric Chang;Yingqing Xu;Heung-Yeung Shum

  • Natural language speech recognition using slot semantic confidence scores related to their word recognition confidence scores

    Eric I Chao Chang;Eric G. Jackson

  • Deep convolutional activation features for large scale Brain Tumor histopathology image classification and segmentation

    Yan Xu;Zhipeng Jia;Yuqing Ai;Fang Zhang

  • Voice conversion with smoothed GMM and MAP adaptation.

    Yining Chen;Min Chu;Eric Chang;Jia Liu

  • Gland Instance Segmentation Using Deep Multichannel Neural Networks

    Yan Xu;Yang Li;Yipei Wang;Mingyuan Liu

  • Deep learning in digital pathology image analysis: a survey

    Shujian Deng;Xin Zhang;Wen Yan;Eric I-Chao Chang

  • Using Genetic Algorithms to Improve Pattern Classification Performance

    Eric I. Chang;Richard P Lippmann

  • Unsupervised object class discovery via saliency-guided multiple class learning

    Jun-Yan Zhu;Jiajun Wu;Yichen Wei;Eric Chang

Frequent Co-Authors

Zhuowen Tu
Zhuowen Tu University of California, San Diego
Jun'ichi Tsujii
Jun'ichi Tsujii University of Manchester
Yubo Fan
Yubo Fan Beihang University
Jun-Yan Zhu
Jun-Yan Zhu Carnegie Mellon University
Yu Zheng
Yu Zheng Jingdong (China)
Jiajun Wu
Jiajun Wu Stanford University
Frank Seide
Frank Seide Microsoft (United States)
Wei-Ying Ma
Wei-Ying Ma Tsinghua University
Jian-Tao Sun
Jian-Tao Sun Microsoft (United States)

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