Chuang Zhu  祝闯

Associate Professor, Department of Artificial Intelligence, BUPT

Room702, Mingguang Building, Xitucheng Road, BUPT, Beijing, China

Email: czhu@bupt.edu.cn 

[Google Scholar] [Researchgate] [Github]  

Biography & Research Interest

Chuang Zhu is leading the Multimedia Intelligent Computing group at the Center for Data Science, Beijing University of Posts and Telecommunications (BUPT). He received the Ph.D. from Institute of Electronics Science and Engineering, Peking University in 2015. After that, he was a Postdoctoral Fellow in Peking University. He joined the School of Communication Engineering (2017) and the School of Artificial Intelligence (2021), BUPT. His research interests include image processing, deep learning, computer vision, and large-scale image retrieval. He has authored or co-authored over 50 papers in journals and conferences including IEEE Transactions on Medical Imaging (TMI), IEEE Trans. on multimedia (TMM), Neurocomputing, Frontiers in Oncology, ECCV, and ICCV. He serves as a reviewer for IEEE Transactions on Image Processing (TIP), TMM, IEEE Trans. on Circuits and Systems for Video Technology (TCSVT), Computer Vision and Image Understanding (CVIU), Artificial Intelligence In Medicine (AIIM), and PC member for AAAI. 

News

• 🔔 [2022/04] One paper accepted to Gastric Cancer
  

• 🔔 [2021/11] One paper accepted to IEEE Transactions on Medical Imaging
  

• 🔔 [2021/09] One paper accepted to Frontiers in Oncology; two papers accepted to ICCV 2021 workshops 
  

• 🔔 [2021/05] Congrats to Meike for winning the 2021 BUPT "Top Ten Pioneers on Campus" - Academic Research Pioneer
  

• 🔔 [2021/04] One paper accepted to The American Journal of Pathology

• 🔔 [2021/01] One paper accepted to Neurocomputing

• 🔔 [2020] One paper accepted to ECCV 2020 

• 🔔 [2019/10] Champion  (Team: "kuanguang") of MICCAI 2019  DigestPath2019 challenge

• 🔔 [2019] Congrats to Wutong: one of the best oral presentations in ICCPR 2019

• 🔔 [2016] Champion (Team: "PrimaryCvVers") of CCF RACV 2016       

Professional Activities

• Reviewer, Neural Information Processing Systems (NIPS)
  

• PC member, AAAI Conference on Aritficial Intelligence (AAAI)

• Reviewer, International Conference on Machine Learning (ICML)

• Reviewer, IEEE Transactions on Cybernetics 

• Reviewer, IEEE Transactions on Image Processing (TIP)

• Reviewer, IEEE Transactions on Circuits and Systems for Video Technology (TCSVT)

• Reviewer, IEEE Transactions on Instrumentation & Measurement

• Reviewer, IEEE Transactions on multimedia (TMM)

Selected Publications [Detail]

[2021- 📑]  [PDF][CODE] Hard Sample Aware Noise Robust Learning for Histopathology Image Classification, Chuang Zhu, Wenkai Chen, Ting Peng, Ying Wang, Mulan Jin, IEEE Transactions on Medical Imaging, 2021/11.

[2021- 📑]  [PDF][CODE][PROJECT] LLVIP: A Visible-infrared Paired Dataset for Low-light Vision, Xinyu Jia, Chuang Zhu, Minzhen Li, Wenqi Tang, Wenli Zhou, 2021/8, ICCV 2021 workshop.

[2021- 📑]  [PDF][CODE][PROJECT] Meta Self-Learning for Multi-Source Domain Adaptation: A Benchmark, Shuhao Qiu, Chuang Zhu, Wenli Zhou, 2021/8, ICCV 2021 workshop.

[2021- 📑]  [PDF][CODE][DigestPath2019] Multi-level colonoscopy malignant tissue detection with adversarial CAC-UNet, Chuang Zhu, Ke Mei, Ting Peng, Yihao Luo, Jun Liu, Ying Wang, Mulan Jin, 2021/5/28, Neurocomputing, 438, 165-183.

[2021- 📑]  [PDF][CODE] Hybrid model enabling highly efficient follicular segmentation in thyroid cytopathological whole slide image, Chuang Zhu, Siyan Tao, Huang Chen, Minzhen Li, Ying Wang, Jun Liu, Mulan Jin, Intelligent Medicine, 2021.

[2020- 📑]  [PDF][CODE] Instance adaptive self-training for unsupervised domain adaptation, Ke Mei, Chuang Zhu, Jiaqi Zou, Shanghang Zhang, ECCV 2020.

[2020- 📑]  [PDF][CODE] Cross-stained segmentation from renal biopsy images using multi-level adversarial learning，Ke Mei, Chuang Zhu, Lei Jiang, Jun Liu, Yuanyuan Qiao, ICASSP 2020.

[2020- 📑]  [PDF] A novel tool to provide predictable alignment data irrespective of source and image quality acquired on mobile phones: what engineers can offer clinicians, Teng Zhang, Chuang Zhu, Qiaoyun Lu, Jun Liu, Ashish Diwan, Jason Pui Yin Cheung, European Spine Journal, 2020.

[2019- 📑]  [PDF][CODE] Breast cancer histopathology image classification through assembling multiple compact CNNs, Chuang Zhu, Fangzhou Song, Ying Wang, Huihui Dong, Yao Guo, Jun Liu, BMC Medical Informatics and Decision Making, 2019.

[2019- 📑]  [PDF][CODE] Breast cancer image classification on WSI with spatial correlations, Jiandong Ye, Yihao Luo, Chuang Zhu, Fang Liu, Yue Zhang, ICASSP 2019.

[2018- 📑]  [PDF] Breast cancer histology image classification based on deep neural networks, Yao Guo, Huihui Dong, Fangzhou Song, Chuang Zhu, Jun Liu, ICIAR 2018.

[2017- 📑]  [PDF][CODE] LLCNN: A convolutional neural network for low-light image enhancement, Li Tao, Chuang Zhu, Guoqing Xiang, Yuan Li, Huizhu Jia, Xiaodong Xie, VCIP 2017.

[2017- 📑] [PDF] Low-light image enhancement using CNN and bright channel prior, Li Tao, Chuang Zhu, Jiawen Song, Tao Lu, Huizhu Jia, Xiaodong Xie, ICIP 2017.

[2016- 📑] [PDF] Smart query expansion scheme for CDVS based on illumination and key features, Tao Lu, Chuang Zhu, Huizhu Jia, Lingyu Duan, Li Tao, Jiawen Song, Xiaodong Xie, Wen Gao, ICPR 2016.

[2014- 📑] [PDF] Multi-level low-complexity coefficient discarding scheme for video encoder, Chuang Zhu, Huizhu Jia, Jie Liu, Xianghu Ji, Hao Lv, Xiaodong Xie, Wen Gao, ISCAS 2014.

[2013- 📑] [PDF] On a highly efficient RDO-based mode decision pipeline design for AVS, Chuang Zhu, Huizhu Jia, Shanghang Zhang, Xiaofeng Huang, Xiaodong Xie, Wen Gao, IEEE Transactions on Multimedia, 2013.

[2011- 📑] [PDF] A highly efficient pipeline architecture of RDO-based mode decision design for AVS HD video encoder, Chuang Zhu, Yuan Li, Hui-zhu Jia, Xiao-dong Xie, Hai-bing Yin, ICME 2011.