Luefeng Chen received the B.S. degree in automation and the M.S. degree in control science and engineering from Central South University, Changsha, China, in 2009 and 2012, respectively, and the Ph.D. degree in computational intelligence and systems science from the Tokyo Institute of Technology, Tokyo, Japan, in 2015.

He is currently an Associate Professor with the School of Automation, China University of Geosciences, Wuhan, China, where he was a Lecturer from 2015 to 2017. His current research interests include computational intelligence, human-robot interaction, deep learning, intelligent system, pattern recognition, machine learning, emotion recognition and intention understanding, multi-robot behavior coordination, and intelligent control of industrial process.

Dr. Chen was recipient of the Best Paper Award of International Journal of Advanced Computational Intelligence and Intelligent Informatics in 2017 and the Best Paper Award in ASPIRE League Symposium 2012. He is a member of IEEE, the Chinese Association of Automation, the Chinese Association for Artificial Intelligence, and the Japan Society for Fuzzy Theory and Intelligent Informatics.

Education

2015   Ph.D.   Tokyo Institute of Technology, Tokyo, Japan

2012   M.S.    Central South University, Changsha, China

2009   B.S.     Central South University, Changsha, China

Working Experiences

2018-           Associate Professor, School of Automation, China University of Geosciences, Wuhan, China

2015-2018   Lecture, School of Automation, China University of Geosciences, Wuhan, China

Research Interests

— Computational Intelligence

— Human-Robot Interaction

— Deep Learning

— Intelligent System

— Pattern Recognition

— Machine Learning

— Process Control

Professional Activities 

Editoral Board                 2016-   International Journal of Advanced Computational Intelligence and Intelligent Informatics (IFSA Cooperative Journal)

Program Committee        2018-   International Symposium on Computational Intelligence and Industrial Applications (ISCIIA)

                                         2017-   International Workshop on Advanced Computational Intelligence and Intelligent Informatics (IWACIII)

Organizing Committee    2018-   China Intelligent Geological Equipment Technology Development Forum (CIGET)

                                         2015    NSFC-CAS-JSPS The 3rd Interational Workshop on Frontier of Science and Technology (FST 2015)

Journal Review     IEEE Transactions on Fuzzy Systems, IEEE Transactions on Systems, Man, and Cybernetics: Systems, IEEE Transactions on Cybernetics, IEEE Transactions on Cognitive and Developmental Systems, IEEE Transactions on Industrial  Electronics, Control Engineering Practice, Information Sciences, Knowledge-Based Systems

Seleted Publications  

[1] Luefeng Chen, Wanjuan Su, Min Wu, Witold Pedrycz, Kaoru Hirota. A Fuzzy Deep Neural Network with Sparse Autoencoder for Emotional Intention Understanding in Human-Robot Interaction. IEEE Transactions on Fuzzy Systems, 2020, DOI: 10.1109/TFUZZ.2020.2966167.

[2] Luefeng Chen, Min Wu, Mengtian Zhou, Zhentao Liu, Jinhua She, Kaoru Hirota. Dynamic Emotion Understanding in Human-Robot Interaction Based on Two-Layer Fuzzy SVR-TS Model. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2020, 50 (2): 490-501.

[3] Luefeng Chen, Wanjuan Su, Yu Feng, Min Wu, Jinhua She, Kaoru Hirota. Two-layer Fuzzy Multiple Random Forest for Speech Emotion Recognition in Human-Robot Interaction. Information Sciences, 2020, 509: 150-163.

[4] Luefeng Chen, Wanjuan Su, Min Li, Min Wu, Witold Pedrycz, Kaoru Hirota. A Population Randomization Based Multiobjective Genetic Algorithm for Gesture Adaptation in Human-Robot Interaction. SCIENCE CHINA Information Sciences, 2020, DOI: 10.1007/s11432-019-2749-0.

[5] Luefeng Chen, Yu Feng, Mohamed A. Maram, Yawu Wang, Min Wu, Kaoru Hirota, Witold Pedrycz. Multi-SVM based Dempster-Shafer Theory for Gesture Intention Understanding Using Sparse Coding Feature. Applied Soft Computing, 2019, DOI: 10.1016/j.asoc.2019.105787.

[6] Luefeng Chen, Min Li, Wanjuan Su, Min Wu, Kaoru Hirota, Witold Pedrycz. Adaptive Feature Selection-Based AdaBoost-KNN with Direct Optimization for Dynamic Emotion Recognition in Human-Robot Interaction. IEEE Transactions on Emerging Topics in Computational Intelligence, 2019, DOI: 10.1109/TETCI.2019.2909930.

[7] Luefeng Chen, Mengtian Zhou, Min Wu, Jinhua She, Zhentao Liu, Fangyan Dong, Kaoru Hirota. Three-Layer Weighted Fuzzy Support Vector Regression for Emotional Intention Understanding in Human-Robot Interaction. IEEE Transactions on Fuzzy Systems, 2018, 26 (5): 2524-2538.

[8] Luefeng Chen, Min Wu, Mengtian Zhou, Jinhua She, Fangyan Dong, Kaoru Hirota. Information-Driven Multi-Robot Behavior Adaptation to Emotional Intention in Human-Robot Interaction. IEEE Transactions on Cognitive and Developmental Systems, 2018, 10 (3): 647-658.

[9] Luefeng Chen, Mengtian Zhou, Wanjuan Su, Min Wu, Jinhua She, Kaoru Hirota. Softmax Regression Based Deep Sparse Autoencoder Network for Facial Emotion Recognition in Human-Robot Interaction. Information Sciences, 2018, 428: 49-61.

[10] Luefeng Chen, Zhentao Liu, Min Wu, Min Ding, Fangyan Dong, Kaoru Hirota. Emotion-Age-Gender-Nationality Based Intention Understanding in Human-Robot Interaction Using Two-Layer Fuzzy Support Vector Regression. International Journal of Social Robotics, 2015, 7 (5): 709-729.

[11] Luefeng Chen, Zhentao Liu, Min Wu, Fangyan Dong, Yoichi Yamazaki, Kaoru Hirota. Multi-Robot Behavior Adaptation to Local and Global Communication Atmosphere in Humans-Robots Interaction. Journal on Multimodal User Interfaces, 2014, 8 (3): 289-303.

[12] Min Wu, Zhentao Liu, Luefeng Chen. Affective Computing and Affective Robot Systems. Science Press, 2018.