姓名:伍冬睿
职称:教授
职务:图像信息处理与智能控制教育部重点实验室副主任
电子邮件:drwu@hust.edu.cn
个人主页:http://faculty.hust.edu.cn/drwu
个人博客:http://blog.sciencenet.cn/u/drwuHUST
研究领域:脑机接口、机器学习、智慧医疗、计算智能、情感计算

教育经历:
2003,中国科学技术大学,自动化专业,学士
2006,新加坡国立大学,电子与计算机工程专业,硕士
2009,美国南加州大学,电子工程专业,博士
奖励荣誉:
- 2021 中国自动化学会 青年科学家奖
- 2021 世界机器人大赛–BCI脑控机器人大赛技术赛 全国特等奖
- 2021 IEEE 神经系统与康复工程汇刊 最佳论文奖
- 2020 USERN Prize in Formal Sciences
- 2020 湖北省杰出青年基金
- 2020 世界机器人大赛–BCI脑控机器人大赛技术赛 全国一等奖
- 2019 第三届中国脑机接口比赛技术赛 全国一等奖
- 2018 IEEE人机系统汇刊 最佳副编奖
- 2017 国家青年特聘专家
- 2017 ICONIP最佳学生论文奖入围
- 2017 IEEE系统、人和控制论学会 青年科学家奖
- 2016 IEEE脑计划 最佳论文奖入围
- 2015 德国-美国工程前沿论坛
- 2015 美国国家科学院、工程院、医学院Kech未来计划
- 2015 IEEE情感计算汇刊 最有影响力论文奖入围
- 2014 首席信息官100项目奖
- 2014 北美模糊信息处理学会 青年科学家奖
- 2014 IEEE模糊系统汇刊 最佳论文奖
- 2013 海德堡阿贝尔、图灵、菲尔兹获奖者论坛
- 2012 首席信息官100项目奖
- 2012 IEEE计算智能协会 最佳博士论文奖
- 2005 IEEE模糊系统国际会议 最佳学生论文奖
学术任职:
- IEEE模糊系统汇刊 (IF=12.029) 副编 (2011–2018; 2020-2021)
- IEEE人机系统汇刊 (IF=2.968) 副编 (2014–)
- IEEE计算智能杂志 (IF=11.356) 副编 (2017–)
- IEEE神经系统和康复工程汇刊 (IF=3.802) 副编 (2019–)
- 2013年客座主编IEEE计算智能杂志“计算智能与情感计算”特刊
- 2016年客座主编IEEE模糊系统汇刊“脑机接口”特刊
- 2018年客座主编IEEE计算智能新兴主题汇刊 “深度迁移学习进展”特刊
- 2021年客座主编IEEE计算智能杂志“智慧医疗中的元学习”特刊
- 海德堡阿贝尔、图灵、菲尔兹获奖者论坛评委
- IEEE计算智能学会武汉分会主席
- IEEE系统、人和控制论学会武汉分会副主席
- IEEE计算智能学会情感计算工作组主席
科研成果:
出版学术专著《Perceptual Computing》一部 (Wiley-IEEE出版社),发表国际学术期刊和会议论文170余篇,其中SCI 84篇 (一作33篇,IEEE汇刊56篇),ESI高引8篇,谷歌学术总引用8500余次(H=47)。1篇IEEE模糊系统汇刊最佳论文,1篇IEEE神经系统和康复工程汇刊最佳论文,1篇IEEE世界机电一体化与自动化会议最佳论文,5篇IEEE计算智能学会亮点论文,1篇在1997-2017年间共1288篇二型模糊系统SCI论文中引用排名12,1篇在Engineering Applications of Artificial Intelligence (IF=4.201) 1988-2018年间发表的2960篇论文中引用排名13。两种模糊系统算法进入Matlab 模糊逻辑工具箱。授权国际专利5项,中国发明专利6项。被中国日报、中国科学报、中新网、长江日报、财新周刊、麻省理工科技评论、DigitalTrends、TechXplore、Geeks等多个网站和媒体采访或报道。据斯坦福大学2021年发布的全球前2%科学家排名,在全球前247516位人工智能科学家中排名331,中国第48。
学术专著:
- J. M. Mendel and D. Wu, “Perceptual Computing: Aiding People in Making Subjective Judgments,” Wiley-IEEE Press, April 2010. (Matlab code) (Book Review)(Google Books)
代表性论文:
Brain-Computer Interface:
- X. Zhang, D. Wu*, L. Ding*, H. Luo, C-T Lin, T-P Jung and R. Chavarriaga, “Tiny noise, big mistakes: Adversarial perturbations induce errors in Brain-Computer Interface spellers,” National Science Review, 8(4), 2021. (Python; TechXplore; TechXplore2)
- Z. Liu, L. Meng, X. Zhang, W. Fang, D. Wu*, “Universal Adversarial Perturbations for CNN Classifiers in EEG-Based BCIs,” Journal of Neural Engineering, 8:0460a4, 2021.
- D. Wu*, Y. Xu and B.-L. Lu, “Transfer Learning for EEG-Based Brain-Computer Interfaces: A Review of Progress Made Since 2016,” IEEE Trans. on Cognitive and Developmental Systems, 2020, accepted.
- W. Zhang and D. Wu*, “Manifold Embedded Knowledge Transfer for Brain-Computer Interfaces,” IEEE Trans. on Neural Systems and Rehabilitation Engineering, 28(5):1117-1127, 2020. (Python; 世界机器人大会)
- H. He and D. Wu*, “Different Set Domain Adaptation for Brain-Computer Interfaces: A Label Alignment Approach,” IEEE Trans. on Neural Systems and Rehabilitation Engineering, 28(5):1091-1108, 2020. (Matlab; IEEE Brain)
- H. He and D. Wu*, “Transfer Learning for Brain-Computer Interfaces: A Euclidean Space Data Alignment Approach,” IEEE Trans. on Biomedical Engineering, 67(2):399-410, 2020. (Matlab; IEEE Brain)
- Y. Cui, Y. Xu and D. Wu*, “EEG-Based Driver Drowsiness Estimation Using Feature Weighted Episodic Training,” IEEE Trans. on Neural Systems and Rehabilitation Engineering, 27(11):2263-2273, 2019. (IEEE TNSRE Cover Article; Python)
- X. Zhang and D. Wu*, “On the Vulnerability of CNN Classifiers in EEG-Based BCIs,” IEEE Trans. on Neural Systems and Rehabilitation Engineering, 27(5):814-825, 2019. (Python)
- D. Wu*, J-T King, C-C Chuang, C-T Lin and T-P Jung, “Spatial Filtering for EEG-Based Regression Problems in Brain-Computer Interface (BCI),” IEEE Trans. on Fuzzy Systems, 26(2):771-781, 2018.
- D. Wu*, B. J. Lance, V. J. Lawhern, S. Gordon, T-P Jung and C-T Lin, “EEG-Based User Reaction Time Estimation Using Riemannian Geometry Features”, IEEE Trans. on Neural Systems and Rehabilitation Engineering, 25(11):2157-2168, 2017.
- D. Wu, V. Lawhern, S. Gordon, B. Lance and C-T Lin, “Driver Drowsiness Estimation from EEG Signals Using Online Weighted Adaptation Regularization for Regression (OwARR),” IEEE Trans. on Fuzzy Systems, 25(6):1522-1535, 2017.
- D. Wu*, “Online and Offline Domain Adaptation for Reducing BCI Calibration Effort,” IEEE Trans. on Human-Machine Systems, 47(4): 550-563, 2017. (ESI Highly Cited Paper)
- D. Wu, V. Lawhern, D. Hairston and B. Lance, “Switching EEG Headsets Made Easy: Reducing Offline Calibration Effort Using Active Weighted Adaptation Regularization,” IEEE Trans. on Neural Systems and Rehabilitation Engineering, 24(11):1125-1137, 2016.
Affective Computing:
- 权学良, 曾志刚, 蒋建华, 张亚倩, 吕宝粮, 伍冬睿*, 基于生理信号的情感计算研究综述. 自动化学报, 2020, in press.
- D. Wu and J. Huang, “Affect Estimation in 3D Space Using Multi-Task Active Learning for Regression,” IEEE Trans. on Affective Computing, 2021, in press.
- D. Wu, C. Courtney, B. Lance, S. Narayanan, M. Dawson, K. Oie, and T.D. Parsons, “Optimal Arousal Identification and Classification for Affective Computing: Virtual Reality Stroop Task,” IEEE Trans. on Affective Computing, 1(2):109-118, 2010. (Top Accessed Article; IEEE Trans. on Affective Computing Most Influential Paper Award Finalist)
Machine Learning:
- X. Zhang, H. Xiong and D. Wu, “Rethink the Connections among Generalization, Memorization, and the Spectral Bias of DNNs,” Int’l Joint Conf. on Artificial Intelligence (IJCAI), Montreal, Canada, August 2021.
- 刘子昂, 蒋雪, 伍冬睿*, “基于池的无监督线性回归主动学习,” 自动化学报, 2021. (Matlab)
- X. Zhang and D. Wu*, “Empirical Studies on the Properties of Linear Regions in Deep Neural Networks,” Int’l. Conf. on Learning Representations (ICLR), Addis Ababa, Ethiopia, April 2020.
- Z. Shi, D. Wu*, C. Guo, C. Zhao, Y. Cui and F-Y Wang*, “FCM-RDpA: TSK Fuzzy Regression Model Construction Using Fuzzy C-Means Clustering, Regularization, DropRule, and Powerball AdaBelief“, Information Sciences, 2021, accepted.
- Z. Liu, X. Jiang, H. Luo, W. Fang, J. Liu and D. Wu*, “Pool-Based Unsupervised Active Learning for Regression Using Iterative Representativeness-Diversity Maximization (iRDM),” Pattern Recognition Letters, 142:11-19, 2021.
- Y. Cui, D. Wu* and J. Huang*, “Optimize TSK Fuzzy Systems for Classification Problems: Mini-Batch Gradient Descent with Uniform Regularization and Batch Normalization,” IEEE Trans. on Fuzzy Systems, 28(12):3065-3075, 2020. (Matlab; Python)
- D. Wu*, Y. Yuan, J. Huang and Y. Tan*, “Optimize TSK Fuzzy Systems for Regression Problems: Mini-Batch Gradient Descent with Regularization, DropRule and AdaBound (MBGD-RDA),” IEEE Trans. on Fuzzy Systems, 28(5):1003-1015, 2020. (Matlab)
- D. Wu* and J.M. Mendel, “Patch Learning,” IEEE Trans. on Fuzzy Systems, 28(9):1996-2008, 2020. (Matlab; IEEE CIS Publication Spotlight)
- D. Wu, C-T Lin, J. Huang* and Z. Zeng*, “On the Functional Equivalence of TSK Fuzzy Systems to Neural Networks, Mixture of Experts, CART, and Stacking Ensemble Regression,” IEEE Trans. on Fuzzy Systems, 28(10):2570-2580, 2020.
- D. Wu* and X. Tan, “Multitasking Genetic Algorithm (MTGA) for Fuzzy System Optimization,” IEEE Trans. on Fuzzy Systems, 28(6):1050-1061, 2020. (Matlab; IEEE CIS Publication Spotlight)
- D. Wu*, C-T Lin and J. Huang*, “Active Learning for Regression Using Greedy Sampling,” Information Sciences, 474:90-105, 2019. (Matlab)
- D. Wu, “Pool-based sequential active learning for regression,” IEEE Trans. on Neural Networks and Learning Systems, 30(5): 1348-1359, 2019. (Matlab)
Smart Healthcare:
- 彭睿旻, 江军, 匡光涛, 杜浩, 伍冬睿*, 邵剑波*. 基于EEG的癫痫自动检测: 综述与展望. 自动化学报, 2021, accepted.
- Z. Fu, X. He, E. Wang, J. Huo, J. Huang, and D. Wu, “Personalized Human Activity Recognition Based on Integrated Wearable Sensor and Transfer Learning,” Sensors, 21(885), 2021.
- X. Yang, Y. Zhang, B. Lo, D. Wu, H. Liao an Y-T Zhang, “DBAN: Adversarial Network with Multi-Scale Features for Cardiac MRI Segmentation,” IEEE Journal of Biomedical and Health Informatics, 2020, accepted.
- X. Song, P. Qian, J. Zheng, Y. Jiang, K. Xia, B. Traughber, D. Wu and R. F. Muzic, “mDixon-Based Synthetic CT Generation via Transfer and Patch Learning,” Pattern Recognition Letters, 138: 51-59, 2020.
- B. Zhang, Y. Cui, M. Wang, J. Li, L. Jin* and D. Wu*, “In Vitro Fertilization (IVF) Cumulative Pregnancy Rate Prediction from Basic Patient Characteristics,” IEEE Access, 7(1):130460-130467, 2019.
- Z. Liu, B. Huang, Y. Cui, Y. Xu, B. Zhang, L. Zhu, Y. Wang, L. Jin* and D. Wu*, “Multi-Task Deep Learning with Dynamic Programming for Embryo Early Development Stage Classification from Time-Lapse Videos,” IEEE Access, 7(1):122153-122163, 2019. (Python)
- Y. Jiang, X. Gu, D. Wu, W. Hang, J. Xue, S. Qiu and C-T Lin, “A Novel Negative-Transfer-Resistant Fuzzy Clustering Model with a Shared Cross-Domain Transfer Latent Space and its Application to Brain CT Image Segmentation,” IEEE/ACM Trans. on Computational Biology and Bioinformatics, 18(1): 40-52, 2021.
- X. Tian, Z. Deng, K-S Choi, D. Wu, B. Qin, J. Wan, H. Shen and S. Wang, “Deep multi-view feature learning for epileptic seizure detection,” IEEE Trans. on Neural Systems and Rehabilitation Engineering, 27(10):1962-1972, 2019.
- Y. Jiang, D. Wu, Z. Deng, P. Qian, J. Wang, G. Wang, F-L Chung, K-S Choi and S. Wang, “Seizure Classification from EEG Signals Using Transfer Learning, Semi-Supervised Learning and TSK Fuzzy System,” IEEE Trans. on Neural Systems and Rehabilitation Engineering, 25(12):2270-2284, 2017.
Intelligent Control:
- 伍冬睿*,曾志刚,莫红,王飞跃,“区间二型模糊集和模糊系统: 综述与展望,” 自动化学报, 46(8):1539-1556, 2020.
- D. Wu* and J.M. Mendel, “Recommendations on Designing Practical Interval Type-2 Fuzzy Systems“, Engineering Applications of Artificial Intelligence, 95:182-193, 2019.
- J. Huang, M. Ri, D. Wu* and S. Ri, “Interval Type-2 Fuzzy Logic Modeling and Control of a Mobile Two-Wheeled Inverted Pendulum,” IEEE Trans. on Fuzzy Systems, 26(4):2030-2036, 2018.
- D. Wu*, “Approaches for Reducing the Computational Cost of Interval Type-2 Fuzzy Logic Controllers: Overview and Comparison,” IEEE Trans. on Fuzzy Systems, 21(1):80-99, 2013. (ESI Highly Cited Paper)
- D. Wu*, “On the Fundamental Differences between Interval Type-2 and Type-1 Fuzzy Logic Controllers,” IEEE Trans. on Fuzzy Systems, 20(5):832-848, 2012. (IEEE CIS Publication Spotlight)
- D. Wu and J. M. Mendel, “On the Continuity of Type-1 and Interval Type-2 Fuzzy Logic Systems,” IEEE Trans. on Fuzzy Systems, 19(1):179-192, 2011. (2014 IEEE TFS Outstanding Paper Award; IEEE CIS Publication Spotlight)
- D. Wu and J. M. Mendel, “Enhance Karnik-Mendel Algorithms,” IEEE Trans. on Fuzzy Systems, 17:923-934, 2009. (ESI Highly Cited Paper; Ranked 12th among all 1,288 SCI papers published worldwide on type-2 fuzzy systems in 1997-2017, according to “A Bibliometric Overview of the Field of Type-2 Fuzzy Sets and Systems,” IEEE Computational Intelligence Magazine, 15(1), pp. 89-98, 2020; Available in Matlab Fuzzy Logic Toolbox)
- D. Wu and W. W. Tan, “Genetic Learning and Performance Evaluation of Type-2 Fuzzy Logic Controllers,” Engineering Applications of Artificial Intelligence, 19(8):829-841, 2006. (Ranked 13th among all 2,960 papers published in EAAI in 1988-2018, according to “Engineering applications of artificial intelligence: A bibliometric analysis of 30 years (1988–2018),” EAAI, 85, pp. 517–532, 2019)
- D. Wu and W. W. Tan, “A Simplified Type-2 Fuzzy Controller for Real-Time Control,” ISA Trans., 15(4):503-516, 2006.
- D. Wu and W. W. Tan, “Type-2 FLS Modeling Capability Analysis,” IEEE Int’l Conf. on Fuzzy Systems, Reno, USA, May 2005. (Best Student Paper Award)
Perceptual Computing & Decision Making:
- J. M. Mendel and D. Wu, “Perceptual Computing: Aiding People in Making Subjective Judgments,” Wiley-IEEE Press, April 2010. (Matlab code) (Book Review)(Google Books)
- D. Wu* and J. M. Mendel, “Similarity Measures for Closed General Type-2 Fuzzy Sets: Overview, Comparisons, and a Geometric Approach,” IEEE Trans. on Fuzzy Systems, 27(3):515-526, 2019.
- D. Wu, H-T Zhang* and J. Huang*, “A Constrained Representation Theorem for Well-Shaped Interval Type-2 Fuzzy Sets, and the Corresponding Constrained Uncertainty Measures,” IEEE Trans. on Fuzzy Systems, 27(6):1237-1251, 2019. (IEEE CIS Publication Spotlight)
- D. Wu*, “A Reconstruction Decoder for Computing with Words,” Information Sciences, 255:1-15, 2014.
- D. Wu and J. M. Mendel, “Linguistic Summarization Using IF-THEN Rules and Interval Type-2 Fuzzy Sets,” IEEE Trans. on Fuzzy Systems, 19(1):136-151, 2011.
- D. Wu and J.M. Mendel, “Computing With Words for Hierarchical Decision Making Applied to Evaluating a Weapon System,” IEEE Trans. on Fuzzy Systems, 18(3):441-460, 2010.
- D. Wu and J. M. Mendel, “Perceptual reasoning for perceptual computing: A similarity-based approach,” IEEE Trans. on Fuzzy Systems, 17(6):1397-1411, 2009.
- D. Wu and J. M. Mendel, “A Comparative Study of Ranking Methods, Similarity Measures and Uncertainty Measures for Interval Type-2 Fuzzy Sets,” Information Sciences, 179(8):1169-1192, 2009. (ESI Highly Cited Paper; Top 25 Hottest Article)
- D. Wu and J. M. Mendel, “Aggregation Using the Linguistic Weighted Average and Interval Type-2 Fuzzy Sets,” IEEE Trans. on Fuzzy Systems, 15(6):1145-1161, 2007.
- D. Wu and J. M. Mendel, “Uncertainty Measures for Interval Type-2 Fuzzy Sets,” Information Sciences, 177:5378-5393, 2007.
发明专利:
- A. Kumar, B. Ellis, Z. Wan, C. Pierce, M. Dokucu, D. Wu and S. Balram, Dynamic monitoring, diagnosis, and control of cooling tower systems, WO2015012832, 1/29/2015.
- S. Gustfason and D. Wu, Influencer analyzer platform for social and traditional media document authors, US20150348216, 12/3/2015.
- J. Reimann, C. Johnson, D. Wu, S. Evans, and R. Cheinhample, A. Pandey, System and method using generative model to supplement incomplete industrial plant information, US20160004794, 1/7/2016.
- A. Can, E. Bas, D. Wu, J. Yu, and L. Wahrmund, Expert guided knowledge acquisition system for analyzing seismic data, WO2017152119, 8/9/2017.
- X. Gui, B. Shi, H. Liu and D. Wu, Target Positioning And Tracking System, Device, And Positioning And Tracking Method, WO2017084240, 5/27/2017.
- 伍冬睿,石振华,一种用于恒河猴眼动决策解码的多视图学习方法和系统,201910586165.4, 2020-07-10
- 伍冬睿,谭显烽,一种适用于云计算系统的多任务处理方法,201811434588.6, 2020-07-10
- 伍冬睿,孟璐斌,一种基于EEG的脑机接口回归系统白盒目标攻击方法,201910896360.7, 2020-08-04
- 伍冬睿,张潇,一种针对以卷积神经网络为基础的EEG脑机接口的攻击方法,201811543220.3,2020-11-10
- 伍冬睿,何赫,一种用于脑机接口校准的异构标签空间迁移学习方法,201911100099.1,2021-08-04
在线讲座:
- 脑机接口中的机器学习, 5/12/2020.
- Affective Computing, 12/6/2011.
媒体报道: