Prof. Zhenghua Xu

Prof. Zhenghua Xu

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Zhenghua XU (许铮铧)

Professor of Computer Science and Technology
Awardee of “100 Talents Plan” of Hebei Province (河北省“百人计划”入选者)
PI of Excellent Young Scientist Fund of Hebei Province (河北省“优秀青年科学基金”获得者)
State Key Laboratory of Reliability and Intelligence of Electrical Equipment
School of Health Sciences and Biomedical Engineering
Hebei University of Technology
Address: No. 8 Guangrongdao, Hongqiao, Tianjin, 300130, China
E-mail: firstname.lastname@hebut.edu.cn

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News

  • Great news: our paper “Inferring Neural Activity Before Plasticity: A Foundation for Learning Beyond Backpropagation” has been ACCEPTED to publish in $\color{red}{Nature}$ $\color{red}{Neuroscience}$ (SCI Q1, IF: 25.0).
  • Our paper “Multi-ConDoS: Multimodal Contrastive Domain Sharing Generative Adversarial Networks for Self-Supervised Medical Image Segmentation” is accepted to publish in IEEE Transactions on Medical Imaging (SCI Q1, IF: 11.037).
  • I am invited to serve as the Senior Program Committee (SPC) member in AAAI 2024.
  • My Google Scholar profile reaches 1000 citations in Apr 2023.
  • Our paper “Multi-Modal Contrastive Mutual Learning and Pseudo-Label Re-Learning for Semi-Supervised Medical Image Segmentation” is published in Medical Image Analysis (SCI Q1, IF: 13.828).
  • I am invited to serve as the Senior Program Committee (SPC) member in AAAI 2023.
  • The paper “RSG: A Simple But Effective Module for Learning Imbalanced Datasets” is accepted by CVPR 2021 (CCF A).
  • The paper “Detecting Beneficial Feature Interactions for Recommender Systems” is accepted by AAAI 2021 (CCF A).
  • I am invited to serve as the Senior Program Committee (SPC) member in IJCAI 2021.
  • The paper “Can the Brain Do Backpropagation” is accepted by NeurIPS 2020 (CCF A).
  • I am routinely invited to serve as the Program Committee Member in top-tier AI conferences since 2019, e.g., AAAI, IJCAI, and ECAI.
  • Two papers “Arena: A General Evaluation Platform and Building Toolkit for Multi−Agent Intelligence” and “Mega−Reward: Achieving Human−Level Play without Extrinsic Rewards” are accepted by AAAI 2020 (CCF A).
  • I serve as the session chair in IJCAI 2019.
  • The paper “Diversity-Driven Extensible Hierarchical Reinforcement Learning” is accepted for oral presentation in AAAI 2019 (CCF A).

Research Interests

  • My research interests include Deep Learning, Reinforcement Learning, Medical Image Computing, Biologically Plausible Neural Networks, and Recommender Systems.

Selected Representative Publications

Please refer to [Publications] for the full list of ALL my publications.
(* stands for corresponding author, and # stands for co-first author.)

[1] Yuhang Song*, Beren Millidge, Tommaso Salvatori, Thomas Lukasiewicz*, Zhenghua Xu*, Rafal Bogacz*. Inferring Neural Activity Before Plasticity: A Foundation for Learning Beyond Backpropagation. Accepted to publish in Nature Neuroscience, 2023. (SCI Q1, IF: 25.0)

[2] Jiaojiao Zhang, Shuo Zhang, Xiaoqian Shen, Thomas Lukasiewicz, Zhenghua Xu*. Multi-ConDoS: Multimodal Contrastive Domain Sharing Generative Adversarial Networks for Self-Supervised Medical Image Segmentation. Accepted to publish in IEEE Transactions on Medical Imaging (TMI), 2023. (SCI Q1, IF: 10.6)
[Download paper here]

[3] Shuo Zhang, Jiaojiao Zhang, Biao Tian, Thomas Lukasiewicz, Zhenghua Xu*. Multi-Modal Contrastive Mutual Learning and Pseudo-Label Re-Learning for Semi-Supervised Medical Image Segmentation. Medical Image Analysis, 2023. (SCI Q1, IF: 10.9)
[Download paper here] [Code Release]

[4] Jianfeng Wang, Thomas Lukasiewicz‚ Xiaolin Hu, Jianfei Cai, Zhenghua Xu*. RSG: A Simple But Effective Module for Learning Imbalanced Datasets, CVPR 2021, CCF A.
[Download paper here] [Code Release]

[5] Yixin Su, Rui Zhang*‚ Sarah Erfani, Zhenghua Xu*. Detecting Beneficial Feature Interactions for Recommender Systems, AAAI 2021, CCF A.
[Download paper here] [Code Release]

[6] Yuhang Song, Thomas Lukasiewicz‚ Zhenghua Xu*, Rafal Bogacz. Can the Brain Do Backpropagation? —— Exact Implementation of Backpropagation in Predictive Coding Networks, NeurIPS 2020, CCF A.
[Details] [Download paper here]

[7] Yuhang Song‚ Andrzej Wojcicki‚ Thomas Lukasiewicz‚ Jianyi Wang‚ Abi Aryan‚ Zhenghua Xu*‚ Mai Xu‚ Zihan Ding and Lianlong Wu. Arena: A General Evaluation Platform and Building Toolkit for Multi−Agent Intelligence, AAAI 2020, CCF A.
[Details] [Download paper here] [Arena Building Toolkit] [Arena Baselines]

[8] Yuhang Song‚ Jianyi Wang‚ Thomas Lukasiewicz‚ Zhenghua Xu*‚ Shangtong Zhang‚ Andrzej Wojcicki and Mai Xu. Mega−Reward: Achieving Human−Level Play without Extrinsic Rewards, AAAI 2020, CCF A.
[Details] [Download paper here]

[9] Yuhang Song, Jianyi Wang, Thomas Lukasiewicz, Zhenghua Xu* and Mai Xu. Diversity-Driven Extensible Hierarchical Reinforcement Learning, AAAI 2019, CCF A.
[Details] [Download paper here] [Code Release] [Oral Presentation]

[10] Zhenghua Xu, Thomas Lukasiewicz, Cheng Chen, Yishu Miao and Xiangwu Meng. Tag-Aware Personalized Recommendation Using a Hybrid Deep Model, IJCAI 2017, CCF A.
[Details] [Download paper here]

[11] Andy Yuan Xue, Rui Zhang, Yu Zheng, Xing Xie, Jin Huang and Zhenghua Xu. Destination Prediction by Sub-trajectory Synthesis and Privacy Protection against Such Prediction, ICDE 2013, CCF A, citations: 332.
[Details] [Download paper here]