钟圣华
2013年毕业于香港理工大学电子计算学系，2013-2014在美国约翰霍普金斯大学心理学与脑科学系担任博士后，2014年回国任教，2019年任深圳大学计算机与软件学院副教授。深圳市海外高层次人才（孔雀计划）、深圳市后备级人才、深圳市南山区高层次人才。研究领域主要有脑机接口、深度学习、人工智能、机器学习、多媒体内容分析。负责主持过国家、省部级以上项目7项。以第一作者或通讯作者在重要期刊／国际会议发表论文90余篇，包括：IEEE Transactions on Affective Computing、IEEE Transactions on Multimedia、ACM Transactions onMultimedia Computing, Communications, and Applications、IEEE/ACM Transactions on Audio, Speech,and Language Processing、IEEE Transactions on Human-Machine Systems、 Neural Networks、Patter Recognition等著名期刊，还有 AAAI、SIGIR、ACM International Conference on Multimedia 等CCF A类国际会议。Google引用超过3000次，高被引论文2篇。
专注于脑机接口(算法、临床结合)、复杂场景下的视觉及情感计算、多模态大模型问题。
欢迎各位同学申请/报考2025级硕士研究生！做一颗滚石吧，期待在思想的交锋中碰撞出智慧的火花。
欢迎大家使用本小组推出的情感脑机接口的专用工具箱TorchEEG：https://torcheeg.readthedocs.io/en/latest/ ！ 该工具箱2022年上线至今，下载量超过1万8千余次，Github加🌟数超过400次。 该工作的相关论文已经发表，也欢迎大家提出建议：https://www.sciencedirect.com/science/article/pii/S0957417424004159
项目组动态：2025.3 论文“Intellectual property protection for deep models: pioneering cross-domain fingerprinting solutions”被CCF A期刊 IEEE Transactions on Information Forensics and Security接收，祝贺徐天华同学！ 2024.12 论文“Attention-guided universal adversarial perturbations for EEG-based brain-computer interfaces”被中科院一区期刊 Expert Systems with Applications接收，祝贺赵思嘉同学！ 2024.11 钟圣华获得广东省自然科学基金面上项目。 2024.8 钟圣华获得国家自然科学基金面上项目(面向脑卒中患者脑电信号的情绪识别及脑电-多媒体交互情绪改善的关键技术研究)，50万元，继续加油！ 2024.6 钟圣华申请并获得大数据国家工程实验室开放课题基金。 2024.4 三篇论文“Fingerprinting in EEG Model IP Protection Using Diffusion Model”, “MarginFinger: Controlling Generated Fingerprint Distance to Classification boundary Using Conditional GANs”, “Discovering Multi-Relational Integration for Knowledge Tracing with Retentive Networks”被CCF推荐的B类国际会议ICMR接收，祝贺王天怡、刘伟星、周林好同学！ 2024.3 论文“TorchEEGEMO: A Deep Learning Toolbox towards EEG-based Emotion Recognition Toolbox Towards EEG-based Emotion Recognition”被中科院一区期刊 Expert Systems with Applications接收，祝贺张智同学！ 2024.3 论文“Sal-guide Diffusion: Saliency Maps guide Emotional Image Generation Through Adapter”被国际会议ICME接收，祝贺林相如同学！ 2023.12 论文“Deep Data Augmentation with Emotional Subspace Constraints for EEG-based Emotion Recognition”被顶会AAAI接收，祝贺张智同学！ 2023.10 论文“Knowledge-guided Network Pruning for EEG-based Emotion Recognition”被国际会议BIBM接收，祝贺饶文杰同学！ 2023.4 论文“基于多示例学习图卷积网络的隐写者检测”被CCF发布的计算领域顶级T1期刊自动化学报接收，祝贺张智同学！ 2023.4 论文“EEG Model Compression by Network Pruning for Emotion Recognition”被国际会议IJCNN接收，祝贺饶文杰同学！ 2023.4 论文“A Robust Deep Learning Enhanced Monocular SLAM System for Dynamic Environments”被国际会议ICMR接收，祝贺黎耀庆同学！ 2023.3 论文“EEG-Based Emotion Recognition via Knowledge-Integrated Interpretable Method”被国际期刊Mathematics接收，祝贺张莹、崔晨同学！ 2023.3 论文“Protecting Intellectual Property of EEG-based Model with Watermarking”被国际会议ICME接收，祝贺徐天华同学！ 2023.2 钟圣华申请并获得广东省自然科学基金面上项目，10万元。 2022.8 论文“Explanations of Deep Networks on EEG Data via Interpretable Approaches”被国际会议CBMS接收，祝贺崔晨、张莹同学！
2022.5 论文“GANSER: A Self-Supervised Data Augmentation Framework for EEG-based Emotion Recognition”被IEEE Transactions on Affective Computing接收，祝贺张智同学！ 2022.4 论文“Training Entire-Space Models for Target-Oriented Option Words Extraction”被SIGIR接收，祝贺李云聪同学、王芳同学！ 2022.4 钟圣华申请并获得光明实验室开放课题基金，10万元。 2022.3 论文“Detecting Abnormality with Separated Foreground and Background: Mutual Generative Adversarial Networks for Video Abnormal Event Detection”被CVIU接收，祝贺张智同学！
代表性成果： [1] Tianhua Xu, Sheng-hua Zhong*, Zhi Zhang, Yan Liu. Intellectual Property Protection for Deep Models: Pioneering Cross-Domain Fingerprinting Solutions. IEEE Transactions on Information Forensics and Security, Accept, 2025. CCF A, 中科院大类一区 Code: https://github.com/munchidelufu/primary-evolvedfinger Paper: https://ieeexplore.ieee.org/document/10937062 [2] Sheng-hua Zhong, Sijia Zhao, Zhijiao Xiao*, Zhi Zhang, Yan Liu. “Attention-Guided Universal Adversarial Perturbations for EEG-Based Brain-Computer Interfaces”, Expert Systems with Applications, vol. 268, 126362, pp. 1-12, 2025. 中科院大类一区 Code: https://github.com/scar0101/AUAP [3] Zhi Zhang, Sheng-hua Zhong*, Yan Liu*. "Beyond Mimicking Under-represented Emotions: Deep Data Augmentation with Emotion Subspace Constraints for EEG-based Emotion Recognition", In Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI’24), 38(9), pp. 10252-10260, 2024. CCF A, CSRanking [4] Zhi Zhang, Sheng-hua Zhong*, Yan Liu*. TorchEEGEMO: A Deep Learning Toolbox Towards EEG-based Emotion Recognition Toolbox Towards EEG-Based Emotion Recognition. Expert Systems with Applications, vol. 249(B), Sep.1 2024. 中科院大类一区 [5] 钟圣华，张智. “基于多示例学习图卷积网络的隐写者检测”, 自动化学报 (ACTA AUTOMATICA SINICA), 2023. CCF发布的计算领域高质量科技期刊顶级期刊 [6] Zhi Zhang, Sheng-hua Zhong*, Yan Liu. “GANSER: A Self-Supervised Data Augmentation Framework for EEG-based Emotion Recognition”, IEEE Transactions on Affective Computing (TAFFC), 2022. 中科院大类一区 [7] Zhi Zhang, Mingjie Zheng, Sheng-hua Zhong*, Yan Liu. Steganographer Detection via Similarity Accumulation Graph Convolutional Network. Neural Networks (NN), vol. 136, pp. 97-111, 2021. 中科院升级版大类一区 [8] Sheng-hua Zhong, Peiqi Liu, Zhong Ming*, Yan Liu. How to Evaluate Single-Round Dialogues Like Humans: an Information-Oriented Metric. IEEE/ACM Transactions on Audio, Speech, and Language Processing (TASLP), vol. 28, pp. 2211-2223, June 22 2020. 中科院升级版大类一区 [9] Jiaxin Wu, Sheng-hua Zhong*, Yan Liu. Dynamic Graph Convolutional Network for Multi-Video Summarization. Patter Recognition (PR), vol. 107, Nov. 2020. 中科院升级版大类一区 [10] Songtao Wu, Sheng-hua Zhong*, Yan Liu. A Novel Convolutional Neural Network for Image Steganalysis With Shared Normalization. IEEE Transactions on Multimedia (TMM), 22(1), June, 2020. 中科院小类一区 [11] Jianmin Jiang#, Ahmed Fares#, Sheng-hua Zhong*. A Context-Supported Deep Learning Framework for Multimodal Brain Imaging Classification. IEEE Transactions on Human-Machine Systems (THMS), 49(6), pp. 611-622, 2019. [12] Sheng-hua Zhong, Yuantian Wang, Tongwei Ren*, Mingjie Zheng, Yan Liu, Gangshan Wu. Steganographer Detection via Multi-scale Embedding Probability Estimation. ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), vol. 15(4), 103, 2019. [13] Yuncong Li, Cunxiang Yin, Sheng-hua Zhong*, Xu Pan. Multi-Instance Multi-Label Learning Networks for Aspect-Category Sentiment Analysis. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP’20), 2020. CSranking [14] Sheng-hua Zhong, Ahmed Fares, Jianmin Jiang. An Attentional-LSTM for Improved Classification of Brain Activities Evoked by Images. In Proceedings of 27th ACM International Conference on Multimedia (SIG MM’ 19), pp. 1295-1303, 2019. CCF A [15] Jiaxin Wu, Sheng-hua Zhong*, Yan Liu. MvsGCN: A Novel Graph Convolutional Network for Multi-Video Summarization. In Proceedings of 27th ACM International Conference on Multimedia (SIG MM’ 19), pp. 827-835, 2019. CCF A
已毕业学生去向:
WU Jianxin: Phd student in the City University of Hong Kong （香港城市大学博士研究生） Zheng Mingjie: Phd student in the Hong Kong Polytechnic University （香港理工大学博士研究生） Wang Fang: Customer value manager in Cigna&CMB （招商信诺客户价值经理） Huang Xinsheng: AI image algorithm engineer in Shenzhen Ruixin Intelligent Medical Technology Co., Ltd. （深圳睿心智能医疗科技有限公司人工智能图像算法工程师） Liu Peiqi: CMB Network Technology Co., Ltd. （招商银行网络科技人工智能实验室） Peng jianfeng: Shenzhen Xinhe Experimental School （深圳市新合实验学校教师） Zhang Zhi: Phd student in the Hong Kong Polytechnic University （香港理工大学博士研究生） Lin Jingxu: Development engineer in Alibaba Group （阿里巴巴研发工程师） Li Yaoqing: Vision algorithm engineer in Fengtu Technology (Shenzhen) Co., Ltd. （顺丰集团丰图科技视觉算法工程师） Zhang Beichuan: Recommended algorithm engineer in kuaishou （快手推荐算法工程师） Zhang Ying: FinTech in BOCOM （交通银行广东省分行金融科技部） Xu Tianhua: Recommended algorithm engineer in Beijing 58 （北京58同城推荐算法工程师） Rao Wenjie: Test development engineer in Fliggy Alibaba (阿里巴巴飞猪测试开发工程师) Shi Jiahao: Backend development engineer in Wondershare （万兴后端开发工程师） Zhao Sijia：Civil servants of the Chaonan District People's Government（汕头市潮南区政府公务员）
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