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伍冬睿

职称:教授

邮箱:drwu@hust.edu.cn

主要研究方向:机器学习,脑机接口,计算智能,情感计算

欢迎感兴趣的同学加入本实验室进行硕士博士研究!

个人简介

个人简介:

    伍冬睿,男,1982年出生,2003年中国科技大学自动化专业学士,2005年新加坡国立大学电子与计算机工程专业硕士,2009年美国南加州大学电子工程专业博士。曾任美国通用电器公司(GE)全球研发中心(纽约)主管研究员和数个初创公司首席科学家。现任华中科技大学自动化学院教授,博导。主要从事情感计算、脑机接口、机器学习、计算智能和智能控制相关研究。2016年入选第12批国家青年“千人计划”。

    出版学术专著《Perceptual Computing》一部,在国际学术期刊和会议上发表论文90余篇,其中SCI 31篇(一作23篇,IEEE汇刊20篇),ESI高引2篇,被引用4300余次。获得三项美国和国际专利。获得2017 IEEE Systems, Man and Cybernetics (SMC) Society Early Career Award2014 IEEE Transactions on Fuzzy Systems Outstanding Paper Award2014 NAFIPS Early Career Award2012 IEEE Computational Intelligence Society (CIS) Outstanding PhD Dissertation Award2005 IEEE International Conference on Fuzzy Systems Best Student Paper Award。入围2017 International Conference on Neural Information Processing (ICONIP) Best Student Paper Award2016 IEEE Brain Initiative Best Paper Award2015 IEEE Transactions on Affective Computing Most Influential Paper Award。国际情感计算促进会执委会成员,北美模糊信息处理协会(NAFIPS)董事会成员和杰出演讲者,IEEE SMC人机接口系统技术委员会成员,IEEE CIS情感计算工作组副主席,波兰和哈萨克斯坦国家科技项目评审,IEEE Transactions on Fuzzy Systems (IF=7.671), IEEE Transactions on Human-Machine Systems (IF=2.493)IEEE Computational Intelligence Magazine(IF=6.343)副编。

   2013年入选德国海德堡阿贝尔/菲尔兹/图灵奖基金会全球200名杰出青年学者。作为美国国家工程院选出的30名美国杰出青年工程师之一,2015 年赴德国与德国洪堡基金会选出的30名德方代表交流。2015年作为美国国家科学院、工程院和医学院共同邀请的60名杰出学者之一,参加National Academies Keck Futures Initiative。在GE参与和领导的项目涵盖金融、医疗保健、油气田开发、交通运输、能源发电、水处理等各个领域。两次获得美国《首席信息官》(CIO)“100最佳项目”(CIO 100)奖,10次获得GE研发中心杰出贡献表彰。

奖励和荣誉:

1. 2017 IEEE 系统、人和控制论协会青年成就奖

2. 2017神经处理国际会议最佳学生论文奖Finalist

3. 2016 IEEE脑计划最佳论文奖Finalist

4. 2016国家青年千人计划

5. 2015 IEEE情感计算汇刊最具影响力论文奖Finalist

6. 入选2015由美国国家科学院、工程院和医学院联合主办的Kech未来计划(总共60人)

7. 入选2015德国洪堡基金会和美国国家工程院联合主办的德国-美国工程前沿研讨会(总共60人)

8. 2014年美国首席信息官杂志100最佳项目奖(车队管理)

9. 2014年北美模糊信息处理协会首届青年成就奖

10. 2014IEEE模糊系统汇刊最佳论文奖(一作)

11. 2010-2014年间10次获得美国通用电气公司杰出贡献奖

12. 2013年应邀参加德国海德堡阿贝尔、菲尔兹、图灵奖获得者论坛(全球200人)

13. 2013年美国首席信息官杂志100最佳项目奖(水处理)

14. 2012IEEE计算智能协会最佳博士论文奖

15. 2009年美国南加州大学维特比工学院最佳博士论文提名奖

16. 2007 IEEE计算智能协会Walter Karplus 暑期研究奖

17. 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 (IEEE Transactions on Fuzzy Systems, IF=7.671), 副编, 2011-

IEEE人机系统汇刊 (IEEE Transactions on Human-Machine Systems, IF=2.493),副编, 2014-

IEEE计算智能杂志 (IEEE Computational Intelligence Magazine, IF=6.343), 副编, 2017-

IEEE计算智能杂志计算智能与情感计算特刊,主编,2013

IEEE 模糊系统汇刊脑机接口特刊,主编,2016

国际情感计算协会,执委会成员,2011-

IEEE 系统、人和控制论学会,脑机接口技术委员会成员,2014-

IEEE计算智能协会,情感计算工作组,主席/副主席,2012- 

代表性论文:

1. J. M. Mendel and D. Wu, Perceptual Computing: Aiding people in making subjective judgments, Wiley-IEEE Press, April 2010. (专著)

2. 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 Transactions on Neural Systems and Rehabilitation Engineering, in press.

3. D. Wu, B. J. Lance, V. J. Lawhern, Stephen Gordon, Tzyy-Ping Jung and Chin-Teng Lin, “EEG-Based User Reaction Time Estimation Using Riemannian Geometry Features”, IEEE Transactions on Neural Systems and Rehabilitation Engineering, in press.

4. 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 Transactions on Fuzzy Systems, in press. . (IEEE模糊系统汇刊20174月最热门论文)

5. D. Wu, B. Lance and V. Lawhern, "Guest Editorial for the Special Issue on Brain Computer Interface (BCI)," IEEE Transactions on Fuzzy Systems, 25(1), pp. 1-2, 2017.

6. 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 Transactions on Fuzzy Systems, 2017, in press.

7. D. Wu, "Online and Offline Domain Adaptation for Reducing BCI Calibration Effort," IEEE Transactions on Human-Machine Systems, vol. 47, no. 4, pp. 550-563, 2017. . (IEEE人机系统汇刊20177月最热门论文)

8. J.M Mendel and D. Wu, "Critique of 'A New Look at Type-2 Fuzzy Sets and Type-2 Fuzzy Logic Systems'," IEEE Transactions on Fuzzy Systems, 2017, 25(3), pp. 725-727. (IEEE模糊系统汇刊20176月和7月最热门论文)

9. D. Wu, V. Lawhern, D. Hairston and B. Lance, "Switching EEG Headsets Made Easy: Reducing Offline Calibration Effort Using Active Weighted Adaptation Regularization," IEEE Transactions on Neural Systems and Rehabilitation Engineering, 24(11), pp. 1125-1137, 2016.

10. A. Marathe, V. Lawhern, D. Wu, D. Slayback and B. Lance, “Improved Neural Signal Classification in a Rapid Serial Visual Presentation Task using Active Learning,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, 24(3), pp. 333-343, 2016.

11. S.M. Salaken, A. Khosravi, S. Nahavandi and D. Wu, “Approximation of centroid end-points and switch points for replacing type reduction algorithms,” International Journal of Approximate Reasoning, 66, pp. 39-52, 2015.

12. D. Wu, “A reconstruction decoder for computing with words,” Information Sciences, 255, pp. 1-15, 2014.

13. D. Wu, B. Lance, and T.D. Parsons, “Collaborative filtering for brain-computer interaction using transfer learning and active class selection,” PLoS ONE, 2013.

14. D. Wu, “Approaches for reducing the computational cost of interval type-2 fuzzy logic controllers: Overview and comparison,” IEEE Transactions on Fuzzy Systems, 21(1), pp. 80-99, 2013. (IEEE CIS Publication Spotlight)

15. J.M. Mendel and D. Wu, “Challenges for perceptual computer applications and how they were overcome,” IEEE Computational Intelligence Magazine, 7(3), pp 36-47, 2012.

16. D. Wu, “On the fundamental differences between interval type-2 and type-1 fuzzy logic controllers,” IEEE Transactions on Fuzzy Systems, 20(5), pp. 832-848, 2012. (IEEE计算智能协会亮点论文)

17. D. Wu, S. Coupland and J.M. Mendel, “Enhanced interval approach for encoding words into interval type-2 fuzzy sets and its convergence analysis,” IEEE Transactions on Fuzzy Systems, 20(3), pp. 499-513, 2012.

18. X. Liu, J.M. Mendel and D. Wu, “Study on Enhanced Karnik-Mendel algorithms: Initialization explanations and computation improvements,” Information Sciences, 184(1), pp. 75-91, 2012.

19. X. Liu, J.M. Mendel and D. Wu, “Analytical solution methods for the fuzzy weighted average,” Information Sciences, 187, pp. 151-170, 2012.

20. D. Wu and J. M. Mendel, “On the continuity of type-1 and interval type-2 fuzzy logic systems,” IEEE Transactions on Fuzzy Systems, 19(1), pp. 179-192, 2011. (IEEE计算智能协会亮点论文; 2014 IEEE模糊系统汇刊最佳论文奖)

21. D. Wu and J. M. Mendel, “Linguistic summarization using IF-THEN rules and interval type-2 fuzzy sets,” IEEE Transactions on Fuzzy Systems, 19(1), pp. 136-151, 2011.

22. 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 Transactions on Affective Computing, 1(2), pp. 109-118, 2010. (IEEE情感计算汇刊最有影响力论文奖入围; 最多下载文章)

23. D. Wu and J.M. Mendel, “Computing with words for hierarchical decision making applied to evaluating a weapon system,” IEEE Transactions on Fuzzy Systems, 18(3), pp. 441-460, 2010.

24. H. Acosta, D. Wu and B. M. Forrest, “Fuzzy experts on recreational vessels, a risk modeling approach for marine invasions,” Ecological Modeling, 221(5), pp. 850-863, 2010.

25. D. Wu and J. M. Mendel, “Enhance Karnik-Mendel algorithms,” IEEE Transactions on Fuzzy Systems, 17, pp. 923-934, 2009.

26. 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), pp. 1169-1192, 2009. (最热25篇文章)

27. D. Wu and J. M. Mendel, “Perceptual reasoning for perceptual computing: A similarity-based approach,” IEEE Transactions on Fuzzy Systems, 17(6), pp. 1397-1411, 2009.

28. J. M. Mendel and D. Wu, “Perceptual reasoning for perceptual computing,” IEEE Transactions on Fuzzy Systems, 16(6), pp. 1550-1564, 2008.

29. D. Wu and J. M. Mendel, “A vector similarity measure for linguistic approximation: interval type-2 fuzzy sets and type-1 fuzzy sets,” Information Sciences, 178, pp. 381-402, 2008.

30. D. Wu and J. M. Mendel, “Aggregation using the linguistic weighted average and interval type-2 fuzzy sets,” IEEE Transactions on Fuzzy Systems, 15(6), pp. 1145-1161, 2007.

31. D. Wu and J. M. Mendel, “Uncertainty measures for interval type-2 fuzzy sets,” Information Sciences, 177, pp. 5378-5393, 2007.

32. D. Wu and W. W. Tan, “Genetic learning and performance evaluation of type-2 fuzzy logic controllers,” Engineering Applications of Artificial Intelligence, 19(8), pp. 829-841, 2006.

33. D. Wu and W. W. Tan, “A simplified type-2 fuzzy controller for real-time control,” ISA Transactions, 15(4), pp. 503-516, 2006.

34. D. Wu, V. Lawhern, S. Gordon, B. Lance and C-T Lin, "Spectral Meta-Learner for Regression (SMLR) Model Aggregation: Towards Calibrationless Brain-Computer Interface (BCI)" IEEE Int'l. Conf. on Systems, Man and Cybernetics, pp. 743-749, Budapest, Hungary, 2016. (IEEE脑计划最佳论文奖入围)

35. D. Wu and T.D. Parsons, “Customized cognitive state recognition using minimal user-specific data,” Military Health Systems Research Symposium, Fort Lauderdale, FL, August 2012. (大会主旨报告;3%接收率)

36. D. Wu, T. Parsons, E. Mower and S. Narayanan, “Speech emotion estimation in 3D space,” IEEE International Conference on Multimedia & Expo (ICME), Singapore, July 2010. (10%接收率)

37. D. Wu and W. W. Tan, “Type-2 FLS modeling capability analysis,” IEEE International Conference on Fuzzy Systems, pp. 242-247, Reno, USA, May 2005. (最佳学生论文奖)


美国/国际专利:

1. A. Kumar, B. Ellis, Z. Wan, C. Pierce, M. Dokucu, D. Wu and S. Balram, Dynamic monitoring, diagnosis, and control of cooling tower systems, WO 2015012832.

2. S. Gustfason and D. Wu, Influencer analyzer platform for social and traditional media document authors, US 20150348216.

3. C. Johnson, A. pandey, D. Wu, J. Reimann, S. Evans, and R. Cheinhample, System and method using generative model to supplement incomplete industrial plant information, US 20160004794.