李敏，女，汉族，1995年生，山西太原人，中共党员，工学博士。现任人工智能学院专任教师。2018年6月毕业于中国地质大学（武汉）测控技术与仪器专业，获工学学士学位；2025年6月毕业于中国地质大学（武汉）控制科学与工程专业，获工学博士学位。2025年8月入职香港六宝合典资料大全人工智能学院。

研究方向：计算智能、情感计算、人机交互、智能机器人

主要论文成果：

[1]Min Li, Luefeng Chen, Min Wu, and Kaoru Hirota. A broad-deep fusion network-based fuzzy emotional intention inference model for teaching validity evaluation. Information Sciences, 654: 119837, 2024.

[2]Min Li, Luefeng Chen, Min Wu, Kaoru Hirota, and Witold Pedrycz. Broad-Deep Network-Based Fuzzy Emotional Inference Model with Personal Information for Intention Understanding in Human-Robot Interaction. Annual Reviews in Control, 57: 100951, 2024.

[3] Luefeng Chen,Min Li, Min Wu, Witold Pedrycz, Kaoru Hirota. Coupled Multimodal Emotional Feature Analysis Based on Broad-Deep Fusion Networks in Human-Robot Interaction. IEEE Transactions on Neural Networks and Learning Systems, 35(7): 9663-9673, 2024.

[4] Luefeng Chen,Min Li, Min Wu, Witold Pedrycz, Kaoru Hirota. Convolutional Features-Based Broad Learning with LSTM for Multidimensional Facial Emotion Recognition in Human-Robot Interaction. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 54 (1): 64-75, 2024.

[5] Luefeng Chen,Min Li, Wanjuan Su, Min Wu, Kaoru Hirota, and 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, 5 (2): 205-213, 2021.（入选ESI前1%高被引论文）

[6] Luefeng Chen,Min Li, Xuzhi Lai, Kaoru Hirota, and Witold Pedrycz. CNN-based broad learning with efficient incremental reconstruction model for facial emotion recognition. IFAC-PapersOnline, 53 (2): 10236-10241, 2020.

[7]Min Li, Luefeng Chen, Min Wu, Kaoru Hirota, and Witold Pedrycz. Broad-Deep Network-based Fuzzy Emotional Inference Model with Personal Information for Intention Understanding. IFAC-PapersOnLine, 56 (2): 7653-7658, 2023.

[8]Min Li, Luefeng Chen, Min Wu, Kaoru Hirota, and Witold Pedrycz. Dynamic expression recognition-based quantitative evaluation of teaching validity using V-A emotion space. Proceedings of the 13th Asian Control Conference (ASCC2022), Gangnam-gu, Korea, May. 4-7, 1079-1083, 2022.

[9]Min Li, Wanjuan Su, Luefeng Chen, Min Wu, Kaoru Hirota, and Witold Pedrycz. Multimodal information-based broad and deep learning model for emotion understanding. Proceedings of the 40th Chinese Control Conference (CCC2021), Shanghai, China, Jul. 26-28, 7410-7414, 2021.

[10]Min Li, Wanjuan Su, Luefeng Chen, Min Wu, and Kaoru Hirota. AdaBoost-KNN for dynamic emotion recognition. Proceedings of the 8th International Symposium on Computational Intelligence and Industrial Applications (ISCIIA2018) & The 12th China-Japan International Workshop on Information Technology and Control Applications (ITCA2018), Tengzhou, China, Nov. 2-6, 2018.

专利成果：

[1]陈略峰,吴敏,李敏,苏婉娟,王亚午.一种基于Adaboost-KNN的动态人脸情感识别方法.专利号: ZL201910139587.7,授权日: 2020. 11.24. 

电子邮箱：[email protected]