彭勇，杭州电子科技大学计算机学院教授、博士生导师，IEEE高级会员、中国生物医学工程学会高级会员，院党委委员、认知与智能计算所书记、副所长，主要从事脑机接口理论、模型与应用研究；主持国家重点研发计划（国合重点专项）、国家自然科学基金3项（青年+面上+面上）、国家高端外专项目（S类和H类）、教育部人文社科基金、浙江省“领雁”攻关计划（国际合作类）、浙江省科技计划（公益）、浙江省自然科学基金、中国博士后科学基金、国防科技重点实验室基金、CCF-腾讯犀牛鸟创意基金、教育部与国家民航局重点实验室开放课题等；发表SCI/SSCI源刊论文85篇，其中ACM/IEEE汇刊论文22篇、ESI高被引论文3篇（其中热点1篇）、编辑首选论文1篇、中文高PCSI论文（高被引论文）1篇，谷歌学术引用2825次，H指数30，H10指数57；申请发明专利40余项，已授权28项（转让9项）；研发脑机接口原型系统3套、获得软件著作权10项；代表性工作发表于IEEE TAFFC、TII、TFUZZ、TIFS、TNSRE、TIM、TETCI、TCDS、TCSVT、TMM、TCAS-II，ACM ToMM以及《控制理论与应用》、《中国生物医学工程学报》等国内外重要期刊；研究工作得到了中、美、英、日等20余位国家院士团队的引用及正面评价。曾获中国科学院院长奖，中国电子学会技术发明三等奖，中国电子学会电子信息教学成果大赛二等奖，浙江省研究生教育成果一等奖，杭州电子科技大学教学成果特等奖；入选校优秀共产党员、校优秀骨干教师、校“科研之星”、校“西湖学者”特聘教授，浙江省高层次人才特殊支持计划，受邀担任J. King Saud Univ. Comput. Inf. Sci.(SCI二区，影响因子6.1)编委（Associate Editor）与Neural Engineering and Neurofeedback副主编(Deputy Editors-in-Chief)。
博士(06/2015), 上海交通大学计算机科学与工程系 国际访学(09/2012—08/2014), 密西根大学安娜堡分校电气工程与计算机科学系 硕士(07/2010), 中国科学院研究生院 本科(07/2006), 中国人民解放军炮兵学院
杭州电子科技大学计算机学院, 教授(01/2022—至今) 杭州电子科技大学计算机学院, 副教授(01/2019-12/2021) 杭州电子科技大学计算机学院, 副研究员(01/2016-12/2018) 杭州电子科技大学计算机学院, 讲师(06/2015—12/2015)
主要课程： 离散数学 人工智能导论 创新实践 人工智能与模式识别（研究生）
教学项目：
全国高等院校计算机基础教育研究会计算机基础教育教学研究项目（2025-AFCEC-387），机器学习课程的多学科交叉和线上线下混合式教学探索，01/2025-11/2026，参与 全国高等院校计算机基础教育研究会计算机基础教育教学研究项目（2024-AFCEC-332），理实交融，创新驱动—新工科背景下计算机专业创新实践能力培养模式探索，07/2024-12/2025，主持 浙江省“十四五”新工科教材建设项目——《机器学习：算法与实践》，06/2024-12/2015，主持 浙江省高等教育学会“人工智能 赋能教育教学应用研究”专项课题（KT2024391），新工科背景下基于“四课”融合的计算机创新创业人才培养体系建设与研究，参与 浙江省研究生教育学会重点课题（2021-003），研究生导师指导能力量化评测研究，01/2022-12/2022，参与已结题 全国高等院校计算机基础教育研究会计算机基础教育教学研究项目（2021-AFCEC-195），面向信息类专业卓越拔尖本科人才培养的科教产协同育人模式探索与实践，05/2021-04/2023，主持已结题 教育部产学协同育人项目（201802164016）：《机器学习与模式识别》创新实践课程的研究性教学改革研究与实践，立项无经费，09/2019-03/2020，主持已结题 浙江省教育科学规划课题（2017SCG003）：基于多学科融合的大数据与人工智能课程STEM项目化学习的研究与实施， 01/2017-12/2017，参与已结题 杭州电子科技大学高等教育改革研究项目，科研导向的人工智能卓越拔尖人才培养模式探索与实践， 07/2020-06/2021，主持已结题 杭州电子科技大学高等教育改革研究项目，机器学习课程研究性教学模式研究与实践，校高等教育改革研究项目，07/2019-06/2020，主持已结题 杭州电子科技大学高等教育改革研究项目，教学科研型高校青年教师早期科研工作规划问题与对策，校高等教育改革研究项目，07/2017-06/2018，主持已结题
指导本科生：
2025年度浙江省“挑战杯”大学生课外学术科技作品竞赛，铜奖（合作指导）
2024年度中国国际大学生创新大赛银奖（合作指导）
2022年度第十二届MathorCup高校数学建模挑战赛，一等奖
2022年度全国大学生算法设计与编程挑战赛，铜奖
2022数维杯大学生数学建模竞赛，三等奖
2021年度第十七届“挑战杯”全国大学生课外学术科技作品竞赛，银奖（合作指导）
2021年度中国国际“互联网+”创新创业大赛，银奖（合作指导）
2021年度中国高校大数据挑战赛，二等奖
2021年度浙江省“互联网+”创新创业大赛，银奖（合作指导）
2021年度浙江省“挑战杯”大学生课外学术科技作品竞赛，二等奖（合作指导）
2020年度浙江省“挑战杯”大学生创业计划竞赛，三等奖（合作指导）
2019年度浙江省“挑战杯”大学生课外学术科技作品竞赛，二等奖（合作指导）
国家级大学生创新创业计划（3项）
省级大学生创新创业计划（1项）
省级新苗人才计划（4项）
计算机学院“当虹杯”卓越科研育人奖学金-本科生（3项）
指导研究生：
纵向科研
主持科研项目：国家重点研发计划-政府间科技创新合作重点专项，言语想象脑机接口高效脑电解码算法与系统研究，01/2024-12/2025，主持 国家自然科学基金-面上项目，脑机接口中混叠情感的度量解析与泛化表征，01/2026-12/2029，主持 国家自然科学基金-面上项目，面向跨被试与跨时段脑电情感识别的知识迁移方法研究，01/2020-12/2023，主持已结题
国家自然科学基金-青年项目，基于低秩模型的联合特征学习与识别算法研究， 01/2017-12/2019，主持已结题
国家高端外专项目（S类），情感脑机接口稳定性解码方法与计算神经机制研究，01/2025-12/2026，负责人
国家高端外专项目（H类），言语想象脑机接口高效脑电解码算法与系统研究，01/2025-12/2026，负责人
教育部人文社科项目，面向抑郁客观评估与调控的脑电模式解析方法研究，01/2025-12/2026，主持
浙江省重点研发计划，面向语言功能障碍人群的言语想象脑机接口解码关键技术与康复训练系统，01/2025-12/2027，共同主持
浙江省科技计划，面向主动交通安全的驾驶员疲劳检测关键技术研究与系统开发，01/2017-12/2019，主持已结题
浙江省自然科学基金，面向结构化图构造的自适应特征权重学习与邻域选择方法研究，01/2021-12/2023，主持已结题
中国博士后科学基金，低秩数据分析及应用，01/2018-07/2019，主持
浙江省级人才项目，机器学习与脑机接口，01/2023-12/2025，主持
浙江省属高校基本科研业务费，脑电情感识别研究，06/2020-06/2022，主持已结题
国防科技重点实验室开放基金，**检测与识别，01/2019-06/2020，主持已结题
国家民航局重点实验室开放基金，基于脑电的飞行员疲劳状态检测关键技术研究，01/2022-12/2023，主持已结题
教育部重点实验室开放课题，集成学习框架下的脑电疲劳回归检测算法研究，01/2020-06/2021，主持已结题
中日青少年科技交流计划（2019年度第二批，SSP20190423358），10/2019，负责人
================================================================================================ 参与科研项目： 国家自然科学基金-企业创新发展联合基金，面向海量视频复杂目标识别的多脑脑机协同智能关键理论与技术，01/2021-12/2024，参与已结题，排名2/10 国家重点研发计划-政府间科技创新合作重点专项，张量表征的深度学习及在大脑运动功能康复中的应用，01/2019-12/2022，参与已结题，排名3/14 国家自然科学基金-面上项目，任务无关脑纹识别的若干关键技术研究，01/2017-12/2020，参与已结题，排名2/10
国家社科基金-青年项目，全媒体时代我国体育新闻传播体系的创新与重构研究， 01/2021-12/2023，参与已结题，排名：2/9
国家社科基金-重大项目，基于大数据的科教评价信息云平台构建和智能服务研究，01/2020-12/2024，参与课题五已结题，排名：x/xx（记不得了）
论文
SCI源刊论文列表: [85] Honggang Liu, Han Yang, Dongjun Liu, Xuanyu Jin, Yong Peng, Wanzeng Kong. DRFNet: Enhancing Identity Discriminability and Feature Robustness for Cross-Session VEP-Based EEG Biometrics. IEEE Journal of Biomedical and Health Informatics, DOI: 10.1109/JBHI.2025.3604620, 2025.
[84] Huang Huang, Xinhui Li, Minchao Wu, Zhao Lv, Yong Peng. Cross-modal knowledge distillation for enhanced depression detection. Complex & Intelligent Systems, DOI: 10.1007/s40747-025-02035-z, 2025.
[83] Yong Peng, Jiangchuan Liu, Honggang Liu, Natasha Padfield, Junhua Li, Wanzeng Kong, Bao-Liang Lu, and Andrzej Cichocki. Prediction Consistency and Confidence-based Proxy Domain Construction for Privacy-Preserving in Cross-subject EEG Classification. IEEE Journal of Biomedical and Health Informatics, DOI: 10.1109/JBHI.2025.3595826, 2025.
[82] Guoguo Ye, Qiqi Chen, Zhiyang Kong, Mingrui Zhou, and Yong Peng. Adaptive Multi-granularity Information Exploration for EEG-based Speech Recognition. IEEE Signal Processing Letters, DOI: 10.1109/LSP.2025.3592109, 2025.
[81] Yibing Li, Zhenye Zhao, Jiangchuan Liu, Yong Peng, Kenneth Camilleri, Wanzeng Kong, Andrzej Cichocki. EEG-based speech imagery decoding by dynamic hypergraph learning within projected and selected feature subspaces. Journal of Neural Engineering, DOI: 10.1088/1741-2552/adeec8, 2025.
[80] Xiaoxiao Gong, Yuxin Chen, Pengfei Zhang, Yong Peng, Jinglong Fang, Andrzej Cichocki. CoAdapt: collaborative adaptation between latent EEG feature representation and annotation for emotion decoding. IEEE Transactions on Instrumentation and Measurement, DOI: 10.1109/TIM.2025.3590828, 2025.
[79] Hongang Liu, Han Yang, Dongjun Liu, Hangjie Yi, Bingfeng He, Yong Peng, Wanzeng Kong. Improving Cross-Session Performance of VEP-Based Biometrics with a Dual Attention Refinement Network. IEEE Transactions on Information Forensics and Security, DOI: 10.1109/TIFS.2025.3587181, 2025.
[78] Mimi Jin, Yiyan Wang, Yong Peng, Feiping Nie, Andrzej Cochicki. Adaptive feature-weighted local-global clustering. IEEE Signal Processing Letters, DOI: 10.1109/LSP.2025.3582536, 2025.
[77] Yiyan Wang, Mimi Jin, Yuxin Chen, Yong Peng, Ziyue Yang, Feiping Nie, Andrzej Cichocki, and Wanzeng Kong. Effective co-clustering by adaptive feature-sample co-weighting. Information Sciences, DOI: 10.1016/j.ins.2025.122427, 2025.
[76] Yuxin Chen, Yong Peng, Jiajia Tang, Tracey Camilleri, Kenneth Camilleri, Wanzeng Kong, Andrzej Cichocki. EEG-based affective brain-computer interfaces: recent progresses and future challenges. Journal of Neural Engineering, DOI: 10.1088/1741-2552/ade290, 2025.（邀请综述论文）
[75] Jiajia Tang, Binbin Ni, Feiwei Zhou, Dongjun Liu, Yu Ding, Yong Peng, Andrzej Cichocki, Qibin Zhao, Wanzeng Kong. Fine-grained semantic disentanglement network for multimodal sarcasm analysis. ACM Transactions on Multimedia Computing, Communications, and Applications, DOI: 10.1145/3722558, 2025.
[74] Zhenye Zhao, Yibing Li, Yong Peng, Kenneth Camilleri, Wanzeng Kong. Multi-view graph fusion of self-weighted EEG feature representations for speech imagery decoding. Journal of Neuroscience Methods, DOI: 10.1016/j.jneumeth.2025.110413, 2025.
[73] Xinhui Li, Ao Li, Wenyu Fu, Xun Song, Fan Li, Qiang Ma, Yong Peng, Zhao Lv. Temporal Relation Modeling and Multimodal Adversarial Alignment Network for Pilot Workload Evaluation. IEEE Journal of Translational Engineering in Health and Medicine, DOI: 10.1109/JTEHM.2025.3542408, 2025.
[72] Hongang Liu, Xuanyu Jin, Dongjun Liu, Jiajia Tang, Yong Peng, and Wanzeng Kong. Joint disentangled representation and domain adversarial training for EEG-based cross-session biometric recognition in single-task protocols. Cognitive Neurodynamics, vol. 19, ID 31, DOI: 10.1007/s11571-024-10214-w, 2025.
[71] Yuhang Ming, Minyang xu, Xingrui Yang, Weicai Ye, Weihan Wang, Yong Peng, Weichen Dai, Wanzeng Kong. VIPeR: Visual incremental place recognition with adaptive mining and continual learning. IEEE Robotics and Automation Letters, DOI: 10.1109/LRA.2025.3539093, 2025.
[70] Shijie Liu, Kang Yan, Feiwei Qin, Ruiquan Ge, Yong Peng, Jie Huang, Nenggan Zheng, Yongquan Zhang, Changmiao Wang. LA-YOLO: location refinement and adjacent feature fusion based infrared small target detection. CAAI Transactions on Intelligence Technology, accepted, 2025.
[69] Yinfeng Fang, Lingfeng Wu, Xixia Yu, Yong Peng, Yuxing Wang, Zhaojie Zhu. A hybrid sEMG-FMG fusion approach under muscle fatigue using cascade fuzzy forest. IEEE Transactions on Fuzzy Systems, DOI: 10.1109/TFUZZ.2024.3505260, 2024.
[68] Diankun Chen, Feiwei Qin, Ruiquan Ge, Yong Peng, Changmiao Wang. ID-UNet: a densly connected Unet architecture for infrared small target segmentation. Alexandria Engineering Journal, vol. 110, 234-244, 2025.
[67] Bowen Pang, Yong Peng, Jian Gao, Wanzeng Kong. Semi-supervised bipartite graph construction with active EEG sample selection for emotion recognition. Medical & Biological Engineering & Computing, vol. 62, 2805–2824, 2024. (编辑首选论文)
[66] Xing Li, Yikai Zhang, Yong Peng, Wanzeng Kong. Enhanced performance of EEG-based brain-computer interfaces by joint sample and feature importance assessment. Health Information Science and Systems, 12(1): 9, 2024.
[65] Keding Chen, Yong Peng, Feiping Nie, and Wanzeng Kong. Soft label guided unsupervised discriminative sparse subspace feature selection. Journal of Classification, 41(1): 129-157, 2024.
[64] Ting Wang, Jianpeng Tang, Xugang Xi, Yong Peng, Maofeng Wang, Lihua Li. Corticomuscular coupling analysis in stroke rehabilitation based on variational mode decomposition-transfer entropy. IEEE Transactions on Neural Systems and Rehabilitation Engineering, DOI: 10.1109/TNSRE.2024.3436077, 2024.
[63] Bing Yang, Xueqin Xiang, Wangzeng Kong, Jianhai Zhang, Yong Peng. DMF-GAN: Deep multimodal fusion generative adversarial networks for text-to-image synthesis. IEEE Transactions on Multimedia, 26: 6956-6967, 2024.
[62] Feiwei Qin, Kang Yan, Changmiao Wang, Ruiquan Ge, Yong Peng, Kai Zhang. LKFormer: large kernel transformer for infrared image super-resolution. Multimedia Tools and Applications, 83(28): 72063-72077, 2024.
[61] Honggang Liu, Xuanyu Jin, Dongjun Liu, Wanzeng Kong, Jiajia Tang, Yong Peng. Affective EEG-based cross-session person identification using hierarchical graph embedding. Cognitive Neurodynamics, DOI:10.1007/s11571-024-10132-x, 2024.
[60] Xuanyu Jin, Xinyu Yang, Wanzeng Kong, Li Zhu, Jiajia Tang, Yong Peng, Yu Ding, Qibin Zhao. TSFAN: tensorized spatial-frequency attention network with domain adaptation for cross-session EEG-based biometric recognition. Journal of Neural Engineering, vol. 21, ID 046005, 2024.
[59] Yifei Chen, Chenyan Zhang, Ben Chen, Yiyu Huang, Yifei Sun, Changmiao Wang, Feiwei Qin, Yong Peng, Yu Gao. Accurate leukocyte detection based on deformable-DETR and multi-level feature fusion for aiding diagnosis of blood diseases. Computers in Biology and Medicine, vol. 170, ID 107917, 2024.(ESI高被引论文，热点论文)
[58] Qi Zhu, Yong Peng. Semi-supervised kernel discriminative low-rank regression for data classification. International Arab Journal of Information Technology, 21(5): 800-815, 2024.
[57] Yong Peng, Honggang Liu, Wanzeng Kong, Feiping Nie, Bao-Liang Lu, Andrzej Cichocki. Joint EEG feature transfer and semi-supervised cross-subject emotion recognition, IEEE Transactions on Industrial Informatics, 19(7): 8104-8115, 2023.
[56] Yong Peng, Wenna Huang, Wanzeng Kong, Feiping Nie, and Bao-Liang Lu. JGSED: an end-to-end spectral clustering model for joint graph Construction, spectral embedding and discretization. IEEE Transactions on Emerging Topics in Computational Intelligence, 7(6): 1687-1701, 2023.
[55] Yong Peng, Honggang Liu, Junhua Li, Jun Huang, Bao-Liang Lu, and Wanzeng Kong. Cross-session emotion recognition by joint label-common and label-specific EEG features exploration. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 31, 759-768, 2023.
[54] Yong Peng, Keding Chen, Feiping Nie, Bao-Liang Lu, Wanzeng Kong. Two-dimensional embedded fuzzy data clustering. IEEE Transactions on Emerging Topics in Computational Intelligence, 7(4):1263-1275, 2023.
[53] Li Zhu, Youyang Liu, Riheng Liu, Yong Peng, Junhua Li, and Wanzeng Kong. Decoding multi-brain motor imagery from EEG using coupling feature extraction and few-shot learning. IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 31, pages 4683-4692, 2023.
[52] Fengzhe Jin, Yong Peng, Feiwei Qin, Junhua Li, and Wanzeng Kong. Graph adaptive semi-supervised discriminative subspace learning for EEG emotion recognition. Journal of King Saud University-Computer and Information Sciences, 35(8), ID 101648, 2023.
[51] Yikai Zhang, Yong Peng, Junhua Li, and Wanzeng Kong. SIFIAE: an adaptive emotion recognition model with EEG feature-label inconsistency consideration. Journal of Neuroscience Methods, 395, ID 109909, 2023.
[50] Tianhui Sha, Yikai Zhang, Yong Peng, and Wanzeng Kong. Semi-supervised regression with adaptive graph learning for EEG-based emotion recognition. Mathematical Biosciences and Engineering, 20(6): 11379-11402, 2023.
[49] Tianhui Sha, and Yong Peng. Orthogonal semi-supervised regression with adaptive label dragging for cross-session EEG emotion recognition. Journal of King Saud University-Computer and Information Sciences, 35(4): 139-151, 2023.
[48] Jin Cao, Ran Xu, Xinnan Lin, Feiwei Qin, Yong Peng, and Yanli Shao. Adaptive receptive field U-shaped temporal convolutional network for vulgar action detection. Neural Computing & Applications, 35(13): 9593-9606, 2023.
[47] Jiajia Tang, Dongjun Liu, Xuanyu Jin, Yong Peng, Qibin Zhao, Yu Ding, Wanzeng Kong. BAFN: bi-direction attention based fusion network for multimodal sentiment analysis. IEEE Transactions on Circuits and Systems for Video Technology, 33(4): 1966-1978, 2023.
[46] Haiting Jiang, Fangyao Shen, Lina Chen, Yong Peng, Hongjie Guo, and Hong Gao. Joint domain symmetry and predictive balance for cross-dataset EEG emotion recognition. Journal of Neuroscience Methods, vol. 400, ID 109978, 2023.
[45] Ben Chen, Feiwei Qin, Yanli Shao, Jin Cao, Yong Peng, and Ruiquan Ge. Fine-grained imbalanced leukocyte classification with global-local attention transformer. Journal of King Saud University-Computer and Information Sciences, 35(8), ID 101661, 2023.
[44] Wanzeng Kong, Shijie Guo, Yanfang Long, Yong Peng, Hong Zeng, Xinyu Zhang, Jianhai Zhang. Weighted extreme learning machine for P300 detection with application to brain computer interface. Journal of Ambient Intelligence and Humanized Computing, vol. 15, 15545-15555, 2023.
[43] Yong Peng, Wenjuan Wang, Wanzeng Kong, Feiping Nie, Bao-Liang Lu, Andrzej Cichocki. Joint feature adaptation and graph adaptive label propagation for cross-subject emotion recognition from EEG signals. IEEE Transactions on Affective Computing, 13(4): 1941-1958, 2022.
[42] Yong Peng, Fengzhe Jin, Wanzeng Kong, Feiping Nie, Bao-Liang Lu, Andrzej Cichocki. OGSSL: a semi-supervised classification model coupled with optimal graph learning for EEG emotion recognition. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 30, 1288-1297, 2022.
[41] Yong Peng, Yikai Zhang, Wanzeng Kong, Feiping Nie, Bao-Liang Lu, Andrzej Cichocki. S3LRR: a unified model for joint discriminative subspace identification and semi-supervised EEG emotion recognition. IEEE Transactions on Instrumentation and Measurement, 71, Article ID 2507313, 2022.
[40] Yong Peng, Feiwei Qin, Wanzeng Kong, Feiping Nie, Yuan Ge, Andrzej Cichocki. GFIL: a unified framework for the analysis of features, frequency bands, channels in EEG-based emotion recognition. IEEE Transactions on Cognitive and Developmental Systems, 14(3): 935-947, 2022. (ESI高被引论文)
[39] Xing Li, Fangyao Shen, Yong Peng, Wanzeng Kong, Bao-Liang Lu. Efficient Sample and Feature Importance Mining in Semi-supervised EEG Emotion Recognition. IEEE Transactions on Circuits and Systems-II: Express Briefs, 69(7): 3349–3353, 2022.
[38] Ruiqi Guo, Yong Peng, Wanzeng Kong, Fan Li. A semi-supervised label distribution learning model with label correlations and data manifold exploration. Journal of King-Saud University-Computer and Information Sciences, 34(10 Part B): 10094-10108, 2022.
[37] Yikai Zhang, Ruiqi Guo, Yong Peng, Wanzeng Kong, Feiping Nie, Bao-Liang Lu. An auto-weighting incremental random vector functional link network for EEG-based driving fatigue detection. IEEE Transactions on Instrumentation and Measurement, vol. 71, Article ID 4010014, 2022.
[36] Wenzheng Li, Yong Peng. Transfer EEG emotion recognition by combining semi-supervised regression with bipartite graph label propagation. Systems, 10(4), Article ID 111 , 2022.
[35] Ziyuan Chen, Shuzhe Duan, Yong Peng. EEG-based emotion recognition by retargeted semi-supervised regression with robust weights. Systems, 10(6), Article ID 236, 2022.
[34] Fangyao Shen, Yong Peng, Guojun Dai, Bao-Liang Lu, Wanzeng Kong. Coupled projection transfer metric learning for cross-session emotion recognition from EEG. Systems, 10(2), Article ID 47, 2022.
[33] Bing Yang, Xueqin Xiang, Wanzeng Kong, Yong Peng, Jinliang Yao. Adaptive multi-task learning using lagrange multiplier for automatic art analysis. Multimedia Tools and Applications, 81(3): 3715-3733, 2022.
[32] Meie Fang, Zhuxin Jin, Feiwei Qin, Yong Peng, Chao Jiang, Zhigeng Pan. Re-transfer learning and multi-modal learning assisted early diagnosis Alzheimer’s disease. Multimedia Tools and Applications, 81(20): 29159-29175, 2022.
[31] Senwei Xu, Li Zhu, Wanzeng Kong, Yong Peng, Hua Hu, Jianting Cao. A novel classification method for EEG-based motor imagery with narrow band spatial filters and deep convolutional neural network. Cognitive Neurodynamics, 16, 379-389, 2022.
[30] Yong Peng, Wanzeng Kong, Feiwei Qin, Feiping Nie, Jinglong Fang, Bao-Liang Lu, Andrzej Cichocki. Self-weighted semi-supervised classification for joint EEG-based emotion recognition and affective activation patterns mining. IEEE Transactions on Instrumentation and Measurement, 70, Article ID 2517111, 2021.
[29] Yong Peng, Xin Zhu, Feiping Nie, Wanzeng Kong, Yuan Ge. Fuzzy graph clustering. Information Sciences, 571: 38-49, 2021.
[28] Yong Peng, Yikai Zhang, Feiwei Qin, Wanzeng Kong. Joint non-negative and fuzzy coding with graph regularization for efficient data clustering. Egyptian Informatics Journal, 22(1): 91-100, 2021.
[27] Wenna Huang, Yong Peng, Yuan Ge, Wanzeng Kong. A new Kmeans clustering model and its generalization achieved by joint spectral embedding and rotation. PeerJ Computer Science, 7, Article ID: e450, 2021.
[26] Yikai Zhang, Yong Peng, Hongyu Bian, Yuan Ge, Feiwei Qin, Wanzeng Kong. Auto-weighted concept factorization for joint feature map and data representation learning. Journal of Intelligent & Fuzzy Systems, 41(1): 69-81, 2021.
[25] Xuanyu Jin, Jiajia Tang, Xianghao Kong, Yong Peng, Jianting Cao, Qibin Zhao, Wanzeng Kong. CTNN: a convolutional tensor-train neural network for multi-task brainprint recognition. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 29, 103-112, 2021.
[24] Haowei Jiang, Feiwei Qin, Jin Cao, Yong Peng, Yanli Shao. Recurrent Neural Network from Adder’s Perspective: Carry-lookahead RNN. Neural Networks, 144, 297-306, 2021.
[23] Xinnan Lin, Feiwei Qin, Yong Peng, Yanli Shao. Fine-Grained Pornographic Image Recognition with Multiple Feature Fusion Transfer Learning. International Journal of Machine Learning and Cybernetics, 12, 73-86, 2021.
[22] Fangyao Shen, Yong Peng, Wanzeng Kong, Guojun Dai. Multi-scale frequency bands ensemble learning for EEG-based emotion recognition. Sensors, 21(4), 1262, 2021.
[21] Yuxuan Zhu, Yong Peng, Yang Song, Kenji Ozawa, Wanzeg Kong. RAMST-CNN: A residual and multiscale spatio-temporal convolution neural network for personal identification with EEG. IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, Vol.E104-A, No.2, pp.563-571, 2021.
[20] Yong Peng, Qingxi Li, Wanzeng Kong, Feiwei Qin, Jianhai Zhang, Andrzej Cichocki. A joint optimization framework to semi-supervised RVFL and ELM networks for efficient data classification. Applied Soft Computing, volume 97, Part A, Article ID 106756, 2020.
[19] Yong Peng, Leijie Zhang, Wanzeng Kong, Feiwei Qin, Jianhai Zhang. Joint low-rank representation and spectral regression for robust subspace learning. Knowledge-Based Systems, 195, 105723, 2020.
[18] Yong Peng, Leijie Zhang, Wanzeng Kong, Feiwei Qin, Jianhai Zhang. Low rank spectral regression via matrix factorization for efficient subspace learning. Journal of Intelligent & Fuzzy Systems, 39(3): 3401-3412, 2020.
[17] Qinghao Ye, Daijian Tu, Feiwei Qin, Zizhao Wu, Yong Peng, Shuying Shen. Dual attention based fine-grained leukocyte recognition for imbalanced microscopic images. Journal of Intelligent & Fuzzy Systems, 37(5): 6971-6982, 2019.
[16] Yong Peng, Wanzeng Kong, Feiwei Qin, Feiping Nie. Manifold adaptive kernelized low-rank representation for semi-supervised image classification. Complexity, Volume 2018 (2018), Article ID 2857594, 2018.
[15] Feiwei Qin, Nannan Gao, Yong Peng, Zizhao Wu, Shuying Shen, Artur Grudtsin. Fine-grained leukocyte classification with deep residual learning for microscopic images. Computer Methods and Programs in Biomedicine, 162: 243-252, 2018.
[14] Feiwei Qin, Haibing Xia, Yong Peng, Zizhao Wu. Integrated modeling, simulation and visualization for nano materials. Complexity, Volume 2018 (2018), Article ID 5083247.
[13] Yong Peng, Bao-Liang Lu. Discriminative extreme learning machine with supervised sparsity preserving for image classification. Neurocomputing, 261: 242-252, 2017.
[12] Yong Peng, Wanzeng Kong, Bing Yang. Orthogonal extreme learning machine for image classification. Neurocomputing, 266: 458-464, 2017.
[11] Yong Peng, Bao-Liang Lu. Robust structured sparse representation via half-quadratic optimization for face recognition. Multimedia Tools and Applications,76(6): 8859-8880, 2017.
[10] Zhi-Jie Wang, Xiao Lin, Mei-E Fang, Bin Yao, Yong Peng, Haibin Guan, MinyiGuo. RE2L: An efficient output-sensitive algorithm for computing boolen operations on circular-arc polygons and its applications. Computer-Aided Design, 83(2):1–14, 2017.
[9] Yong Peng, Bao-Liang Lu. Discriminative manifold extreme learning machine and applications to image and EEG signal classification. Neurocomputing, 174:265–277, 2016.
[8] Yong Peng, Wei-Long Zheng, Bao-Liang Lu. An unsupervised discriminative extreme learning machine and its applications to data clustering. Neurocomputing, 174: 250–264, 2016.
[7] Xianzhong Long, Hongtao Lu, Yong Peng, Xianzhong Wang, Shaokun Feng. Image classification based on improved VLAD. Multimedia Tools and Applications,75(10), 5533–5555, 2016.
[6] Yong Peng, Suhang Wang, Xianzhong Long, Bao-Liang Lu. Discriminative graph regularized extreme learning machine and its application to face recognition. Neurocomputing,149: 340–353, 2015.（ESI高被引论文）
[5] Yong Peng, Bao-Liang Lu, Suhang Wang. Enhanced low rank representation via sparse manifold adaption for semi-supervised learning. Neural Networks, 65: 1–17, 2015.
[4] Yong Peng, Bao-Liang Lu. Hybrid learning clonal selection algorithm. Information Sciences, 296: 128–146, 2015.
[3] Yong Peng, Xianzhong Long, Bao-Liang Lu. Graph based semi-supervised learning via structure preserving low rank representation. Neural Processing Letters, 41(3): 389–406,2015.
[2] Xianzhong Long, Hongtao Lu, Yong Peng, Wenbin Li. Graph regularized discriminative nonnegative matrix factorization for face recognition. Multimedia Tools and Applications, 72(3): 2679–2699, 2014.
[1] Yong Peng, Bao-Liang Lu. A hierarchical particle swarm optimizer with latin sampling based memetic algorithm for numerical optimization. Applied Soft Computing, 13(5): 2823–2836, 2013.
国际会议论文列表： [15] Jiaman Li, Yuxin Chen, Kaiyin Lian, Yong Peng. Data and model fused comparative analysis between speech imagery and idle states by EEG-based connectivity features. International Conference on Automation and Computing (ICAC), Loughborough, UK, August 27-29, 2025.
[14] Natasha Padfield, Stefanie Türk, Kamran Mujahid, Tracey Camilleri, Yong Peng, and Kenneth Camilleri. A spatio-spectral analysis of decoding imagined speech from the idle state. Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Copenhagen, Denmark, July 14-17, 2025.
[13] Yifei Chen, Feiwei Qin, Jin Fan, Yong Peng, Changmiao Wang. Toward robust early detection of Alzheimer’s disease via an integrated multimodal learning approach. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Hyderabad, India, April 6-11, DOI: 10.1109/ICASSP49660.2025.10888363, 2025.
[12] Yikai Zhang, Yong Peng, Ziyue Yang, Feiwei Qin, and Wanzeng Kong. Deep transfer regression for EEG-based driving fatigue detection. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Hyderabad, India, April 6-11, DOI: 10.1109/ICASSP49660.2025.10889729, 2025.
[11] Fangyao Shen, Zehao Zhang, Yong Peng, Hongjie Guo, Lina Chen, Hong Gao. Self-supervised learning for sleep stage classification with temporal augmentation and false negative suppression. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Seoul, Korea, April 14-19, pages 1761-1765, 2024.
[10] Chengxi Zhu, Yong Peng, Yinfeng Fang, and Wanzeng Kong. Label rectified and graph adaptive semi-supervised regression for electrode shifted gesture recognition. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Seoul, Korea, April 14-19, pages 1896-1900, 2024.
[9] Yuhang Ming, Jian Ma, Xingrui Yang, Weichen Dai, Yong Peng, Wanzeng Kong. AEGIS-Net: Attention-guided Multi-Level Feature Aggregation for Indoor Place Recognition. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Seoul, Korea, April 14-19, pages 4030-4034, 2024.
[8] Yong Peng, Qingxi Li, Wanzeng Kong, Jianhai Zhang, Bao-Liang Lu, Andrzej Cichocki. Joint semi-supervised feature auto-weighting and classification model for EEG-based cross-subject sleep quality evaluation. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Barcelona, Spain, May 4-8, pages 946-950, 2020.
[7] Yong Peng, Leijie Zhang, Wanzeng Kong, Feiping Nie, Andrzej Cichocki. Joint structured graph learning and unsupervised feature selection. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brighton, UK, May 12-17, pages 3572-3576, 2019.
[6] Yong Peng, Yanfang Long, Feiwei Qin, Wanzeng Kong, Feiping Nie, Andrzej Cichocki. Flexible non-negative matrix factorization with adaptively learned graph regularization. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brighton, UK, May 12-17, pages 3107-3111, 2019.
[5] Yong Peng, Rixin Tang, Wanzeng Kong, Jianhai Zhang, Feiping Nie, Andrzej Cichocki. Joint structured graph learning and clustering via concept factorization. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brighton, UK, May 12-17, pages 3162-3166, 2019.
[4] Yong Peng, Rixin Tang, Wanzeng Kong, Feiwei Qin, Feiping Nie. Parallel vector field regularized non-negative matrix factorization for image representation. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Calgary, Canada, April 15-20, pages 2216-2220, 2018.
[3] Jianhai Zhang, Shaokai Zhao, Guodong Yang, Jiajia Tang, Tao Zhang, Yong Peng, Wanzeng Kong, Emotional-state brain network analysis revealed by minimum spanning tree using EEG signals. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Madrid, Spain, December 3-6, pages 1045-1048, 2018.
[2] Jianhai Zhang, Na Zhang, Jiajia Tang, Jianting Cao, Wanzeng Kong, Yong Peng. A new method for brain death diagnosis based on phase synchronization analysis with EEG. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Madrid, Spain, December 3-6, pages 1135-1138, 2018.
[1] Wei-Long Zheng, Jia-Yi Zhu, Yong Peng, Bao-Liang Lu. EEG-based emotion classification using deep belief networks. IEEE International Conference on Multimedia and Expo (ICME), Chengdu, China, July 14-18, pages 1–6, 2014.（引用400+次）
中文权威/一级期刊论文列表：
[3] 李文政，王文娟，彭勇，孔万增。联合双映射域适应与图半监督标签估计的脑电情感识别方法。中国生物医学工程学报，42(5): 529-541, 2023. [2] 秦飞巍，沈希乐，彭勇，邵艳利，袁文强，计忠平，白静。无人驾驶中的场景实时语义分割方法。计算机辅助设计与图形学学报，33 (7): 1026-1037, 2021.（高PCSI论文，高被引论文） [1] 林浒，彭勇。面向多目标优化的适应度共享免疫克隆算法。控制理论与应用，28（2）：206-214， 2011.
李平，彭勇，计忠平，徐向华。一种基于稀疏低秩编码的视频动作识别方法。专利号：ZL201610377217.3
彭勇，李平。数据处理方法、装置、终端及存储介质。专利号：ZL201810462144.7
彭勇，李晴熙。一种特征权重自学习的睡眠质量检测关键脑区判定方法。专利号：ZL201911269218.6
彭勇，李晴熙。一种基于结构化数据分解的脑电信号分析方法。专利号：ZL202010114457.0
彭勇，朱琦，张怿恺。一种特征权重自适应学习的脑电情绪识别方法。专利号：ZL202110075007.X
彭勇，李幸，张怿恺。一种样本与特征质量联合量化评估的脑电疲劳检测方法。专利号：ZL202110317792.5
李文政，黄文娜，王文娟，彭勇。联合特征迁移与图半监督标记传播的脑电情感识别方法。专利号：ZL202110428950.4
彭勇，刘鸿刚。一种实时估计脑电情感特征的跨被试迁移学习方法。专利号：ZL202111491551.9
陈子源，段舒哲，沙天慧，彭勇。特征贡献度差异化脑电数据重构的情感激活模式发掘方法。专利号：ZL202111608170.4
彭勇，李幸，张怿恺。一种联合判别子空间发掘与半监督脑电情感识别方法。专利号：202111578215.8
陈子源，高亦心，阮渊鹏，张炜寒，彭勇。基于半监督判别投影的脉搏数据分类方法及装置。专利号：ZL202210547995.8
陈子源，宣欣祎，段舒哲，薛苏琪，彭勇。异常自动检测的半监督自适应标记回归脑电情感识别方法。专利号：ZL202211440751.6
孔万增，崔瑾，彭勇，张建海。基于DDADSM跨被试迁移学习脑电精神状态检测方法。专利号：ZL202011541187.8
彭勇，朱成熙，李逸冰，方银锋。一种稳定性特征发掘的迁移学习肌电手势识别方法。专利号：ZL2024101128595
彭勇，赵振烨，李逸冰。一种自适应图学习的多视图脑电言语想象意图识别方法。专利号：ZL202410708542.8
彭勇，庞博文，赵振烨。一种源域可迁移性自适应学习的言语想象脑电解码方法。专利号：ZL2024100879347
彭勇，朱琦，巩笑晓。具有相邻试次任务混叠度量的脑电言语想象鲁棒解码方法。专利号：ZL202410485170.7
巩笑晓，朱琦，彭勇，方景龙。一种基于成分分解和混叠解析的脑电情感识别方法。专利号：ZL202410648152.6
徐敏阳，明煜航，彭勇，陈高朋。一种基于终身学习的机器人场景识别方法。专利号：ZL202410359890.9
彭勇，李逸冰，赵振烨。一种基于动态超图学习的脑电言语想象识别方法。专利号：ZL202410887130.5
刘江川，彭勇，巩笑晓。一种具有隐私保护功能的跨被试言语想象脑电解码方法。专利号：ZL2024110667246
彭勇，沙天慧。一种基于特征与状态二部图的脑电情感识别方法。专利号：ZL202210514263.9
彭勇，刘鸿刚。一种基于共有与特有脑电特征挖掘的情感识别方法。专利号：ZL202210512240.4
彭勇，李文政，沙天慧。联合半监督回归与图标记传播的脑电迁移情感识别方法。专利号：ZL202210516213.4
靳峰哲，彭勇。一种基于聚类的多任务情感脑电特征提取与识别方法。专利号：ZL202111340210.1
彭勇，靳峰哲。一种基于自适应图学习的半监督脑电情感识别方法。专利号：ZL202111547894.2
彭勇，陈雨欣，王艺谚，杨子玥。一种半监督协同聚类的情感脑电特征与样本耦合分析方法、设备及其存储介质。专利号：ZL202411028849.X
彭勇，柳友洋，朱莉，刘日恒，孔万增，张建海。基于超图表征的协作式运动想象解码方法及脑机系统。专利号：ZL202310353343.5
朱鑫，彭勇。基于在线支持向量回归的多模态驾驶疲劳监测软件。登记号：2020SR0244445 吴欣阳，陈文彬，彭勇，秦飞巍。PCB-DINet缺陷检测分类平台。登记号：2020SR0901573 陈文彬，邢家宝，金倩婷，彭勇。二维亚像素轮廓提取平台。登记号：2020SR0904301 彭勇，李世阳，程诺，李嘉锴。基于深度学习的声呐检测系统。登记号：2021SR1382349 张怿恺，郭瑞琦，陈子源，段舒哲，彭勇。基于脑电信号解码的卒中上肢训练系统。登记号：2022SR1362874 刘日恒，柳友洋，朱莉，彭勇，孔万增，张建海。多脑稳态视觉诱发数字选择系统。登记号：2022SR0533925 柳友洋，刘日恒，朱莉，王鑫洋，杨宇，章杭奎，彭勇，孔万增，张建海。基于注意力的多脑运动想象空闲态识别软件系统。登记号：2022SR0533922 罗臣琪，戴学舟，秦飞巍，彭勇。空对地红外微小目标智能检测系统。登记号：2024SR0308626 王雨荷，明煜航，彭勇。AI智能水务识别系统。登记号：2024SR0432083 叶果果，陈琪琪，孔知洋，周明锐，彭勇。基于言语想象的居家生活辅助系统软件。登记号：2024SR1881238
中国电子学会电子信息教学成果大赛二等奖（2025年7月）
杭州电子科技大学教学成果特等奖（2025年4月）
杭州电子科技大学“星耀杭电”工程之“科研之星”（2024年9月）
杭州电子科技大学优秀共产党员（2024年7月）
杭州电子科技大学来华留学生教育优秀教师（2023年12月）
杭州电子科技大学“西湖学者”特聘教授（聘期：01/2023-12/2026）
浙江省高层次人才特殊支持计划（2022年度）
校优秀硕士论文指导教师（2019届、2021届、2022届、2023届）
校优秀本科毕业设计（论文）指导教师（2020届、2021届、2022届、2025届）
校优秀学科竞赛指导教师（2019年、2020年、2021年、2023年）
浙江省研究生教育学会教育成果奖一等奖（参与） 10/2022
中国电子学会技术发明三等奖（参与） 12/2018
杭州电子科技大学首批优秀骨干教师培养计划（培养期：03/2018-02/2023）
中国科学院院长优秀奖 2009
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