I completed my PhD since 2019. I also spent great time at Siemens Research and Facebook AI Research (FAIR). My PhD research focus was computer vision and deep learning, especially their applicaitons in medical imaging and healthcare.

I am working on machine learning and computer vision research at Google.

I am actively looking for self-motivated interns to explore research topics (e.g. data efficient learning). Contact me if you are interested.

Selected Publications

[ICCV'21] Learning Fast Sample Re-weighting Without Reward Data, Zizhao Zhang, Tomas Pfister (code)

[ICLR'21] PseudoSeg: Designing Pseudo Labels for Semantic Segmentation, Yuliang Zou, Zizhao Zhang, Han Zhang, Chun-Liang Li, Xiao Bian, Jia-Bin Huang, Tomas Pfister (code)

[AAAI'21] Improved Consistency Regularization for GANs, Zhengli Zhao, Sameer Singh, Honglak Lee, Zizhao Zhang, Augustus Odena, Han Zhang

[NeurIPS'20] FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence, Kihyuk Sohn*, David Berthelot*, Chun-Liang Li, Zizhao Zhang, Nicholas Carlini, Ekin D. Cubuk, Alex Kurakin, Han Zhang, Colin Raffel (code)

[ECCV'20] Consistency-Based Semi-Supervised Active Learning: Towards Minimizing Labeling Cost, Mingfei Gao, Zizhao Zhang, Guo Yu, Sercan O Arik, Larry S Davis, Tomas Pfister

[CVPR'20] Distilling Effective Supervision from Severe Label Noise, Zizhao Zhang, Han Zhang, Sercan O Arik, Honglak Lee, Tomas Pfister (code)

[ICLR'20] Consistency Regularization for Generative Adversarial Networks, Han Zhang, Zizhao Zhang, Augustus Odena, Honglak Lee

[ICLR'20] Distance-Based Learning from Errors for Confidence Calibration, Chen Xing, Sercan Arik, Zizhao Zhang, Tomas Pfister (code)

Before 2020

Pathologist-level interpretable whole-slide cancer diagnosis with deep learning

Z. Zhang, P. Chen, M. McGough, F. Xing, C. Wang, M. Bui, Y. Xie, M. Sapkota, L. Cui, J. Dhillon, N. Ahmad, F. K. Khalil, S. I. Dickinson, X. Shi, F. Liu, H. Su, J. Cai, and L. Yang

Nature Machine Intelligence, 2019

[pdf] [data] [code] [public news] [institution news]

Text-guided Neural Network Training for Image Recognition in Natural Scenes and Medicine

Z. Zhang, P. Chen, X. Shi, L. Yang

Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2019

[pdf] [code & data]

Reducing Uncertainty in Undersampled MRI Reconstruction with Active Acquisition

Z. Zhang, A. Romero, M. J. Muckley, P. Vincent, L. Yang, M. Drozdzal, International Conference on Computer Vision and Pattern Recognition (CVPR), 2019

[pdf] [blog]

fastMRI: A Publicly Available Raw k-Space and DICOM Dataset of Knee Images for Accelerated MR Image Reconstruction Using Machine Learning

J. Zbontar, F. Knoll, A. Sriram, M. J. Muckley, M. Bruno, A. Defazio, M. Parente, K. J. Geras, J. Katsnelson, H. Chandarana, Z. Zhang, M. Drozdzal, A. Romero, M. Rabbat, P. Vincent, J. Pinkerton, D. Wang, N. Yakubova, E. Owens, C. L. Zitnick, M. P. Recht, D. K. Sodickson, Y. W. Lui, Radiology: Artificial Intelligence, 2019

[pdf] [code] [project]

Photographic Text-to-Image Synthesis with a Hierarchically-nested Adversarial Network

Z. Zhang, Y. Xie, L. Yang, International Conference on Computer Vision and Pattern Recognition (CVPR), 2018, Spotlight

[pdf] [code]

Translating and Segmenting Multimodal Medical Volumes with Cycle- and Shape-Consistency Generative Adversarial Network

Z. Zhang, L. Yang, Y. Zheng, International Conference on Computer Vision and Pattern Recognition (CVPR), 2018

[pdf] [MIA version] [handbook of MICCAI]

TandemNet: Distilling Knowledge from Medical Images Using Diagnostic Reports as Optional Semantic References

Z. Zhang, P. Chen, M. Sapkota, L. Yang, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2017, Oral

[pdf] [code] [data] [handbook of MICCAI]

MDNet: A Semantically and Visually Interpretable Medical Image Diagnosis Network

Z. Zhang, Y. Xie, F. Xing, M. McGough, L. Yang, International Conference on Computer Vision and Pattern Recognition (CVPR), 2017, Oral

[pdf] [talk] [code]

Revisiting Graph Construction for Fast Image Segmentation

Z. Zhang, F. Xing, H. Wang, Y. Yan, Y. Huang, X. Shi, L. Yang, Pattern Recognition (PR), 2018

[pdf] [arXiv] [code]

Recent Advances in the Applications of Convolutional Neural Networks to Medical Image Contour Detection

Z. Zhang, F. Xing, H. Su, X. Shi, L. Yang, arXiv:1708.07281, 2017


SemiContour: A Semi-supervised Learning Approach for Contour Detection

Z. Zhang, F. Xing, X. Shi, L. Yang, International Conference on Computer Vision and Pattern Recognition (CVPR), 2016

[arXiv] [pdf] [results]

Kernel-Based Supervised Discrete Hashing for Image Retrieval

X. Shi , F. Xing, J. Cai, Z. Zhang, Y. Xie, L. Yang, European Conference on Computer Vision (ECCV), 2016