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谢世文，中南大学特聘副教授，博士生、硕士生导师。2019年获中南大学控制科学与工程博士学位（导师谢永芳教授），2017年5月至2019年5月，受国家留学基金委资助到美国韦恩州立大学访问2年，与IEEE Fellow应浩教授合作开展智能控制理论与应用研究。2020年1月被中南大学聘为特聘副教授。现为中国自动化学会大数据专业委员会副秘书长，中国自动化学会青年工作委员会委员，中国指挥与控制学会智能控制与系统专委会委员，担任IEEE Trans. on Industrial Electronics、IEEE Trans. on Industrial Informatics、IEEE Trans. on Cybernetics、Journal of Process Control、IET Control Theory and Application、ISA Transactions、Neurocomputing、《自动化学报》等十多个国内外高水平期刊的审稿人。

主要研究方向为工业人工智能，机器视觉，知识自动化，深度学习，智能检测等，在IEEE汇刊、IFAC旗舰期刊等国内外高水平期刊发表论文30余篇，国际会议论文8篇，申请国家发明专利24项，其中授权国家发明专利7项，获中国有色金属工业科学技术一等奖，获2020年中国自动化学会优秀博士学位论文奖。主持国家自然科学基金面上项目1项、青年科学基金1项，湖南省自然科学杰出青年基金1项、湖南省自然科学面上项目1项，中国自动化学会青年人才托举工程1项、长沙市自然科学基金1项，参与国家自然科学基金杰出青年科学基金、国家自然科学基金人工智能应急管理重点项目、国家自然科学基金重大科研仪器研制项目、工信部工业互联网创新工程项目等项目。

每年招收自动化专业、人工智能专业、控制专业等专业学位和学术学位的硕士研究生（3名）和博士研究生（1名），课题包括工业人工智能、大数据机器学习、机器视觉感知、工业机器人、工业过程知识获取与表示、模糊控制等，详情咨询：QQ 790270819。

招生原则：

1. 单纯混学历，不想做点东西做出成绩的，请绕开！

2. 心里素质好。

3. 一起搞点研究，做点事情，出点成绩，拿点奖学金。

4. 善于想事，主动做事，自觉自律。

指导研究生发表学术成果：

近3年指导博士研究生发表IEEE汇刊论文18篇、IFAC旗舰期刊论文10篇，指导硕士研究生发表SCI/EI论文15篇，一硕士研究生获2023YAC最佳应用论文奖，获国际会议IAI最佳论文奖。带领研究生到湖北宜昌、福建厦门、重庆、云南昆明、新疆乌鲁木齐、黑龙江哈尔滨、安徽合肥等地参加学术会议。

本博期间所获奖励：

2015年，获博士研究生国家奖学金

2013年，获硕士研究生国家奖学金

2013年，获第十届“华为杯”全国研究生数学建模竞赛二等奖

2011年，获全国大学生电子设计竞赛全国二等奖

2011年，获全国大学生电子设计竞赛湖南赛区一等奖

2011年，获第六届全国大学生“飞思卡尔”杯智能汽车竞赛华南赛区电磁组二等奖

2011年，获第三届湖南省大学生“时代杯”智能汽车竞赛电磁组一等奖

2010年，获第五届全国大学生“飞思卡尔”杯智能汽车竞赛华南赛区电磁组二等奖

发表论文（*为通讯作者）：

[1]    Ye Zhu, Shiwen Xie*, Yongfang Xie, Xiaofang Chen. Temperature prediction of aluminum reduction cell based on integration of dual attention LSTM for non-stationary sub-sequence and ARMA for stationary sub-sequences. Control Engineering Practice, 2023, 138, 105567.  September 2023

[2]    Jie Wang, Shiwen Xie*, Yongfang Xie, Xiaofang Chen. Label propagation with contrastive anchors for deep semi-supervised superheat degree identification in aluminum electrolysis process. IEEE Transactions on Automation Science and Engineering, Early Access, DOI: 10.1109/TASE.2023.3256443.

[3]    Lei He, Yongfang Xie, Shiwen Xie*, Zhipeng Chen. Structure-preserving texture smoothing via scale-aware bilateral total variation. IEEE Transactions on Circuits and Systems for Video Technology, 2023, 33(4): 1493-1506.  

[4]    Yongfang Xie, Weitao Hu, Shiwen Xie*, Lei He. Surface defect detection algorithm based on feature-enhanced YOLO. Cognitive Computation. 2023, 15: 565–579. 

[5]    Jie Wang, Yongfang Xie, Shiwen Xie*, Xiaofang Chen. Optimization of aluminum fluoride addition in aluminum electrolysis process based on pruned sparse fuzzy neural network. ISA Transactions, 2023, 133: 285-301. 

[6]    Ziqing Deng, Xiaofang Chen, Shiwen Xie*, Yongfang Xie, Hongliang Zhang. Semi-supervised discriminative projective dictionary pair learning and its application for industrial process monitoring. IEEE Transactions on Industrial Informatics, 2023, 19(3): 3119-3132.

[7]    Jie Wang, Yongfang Xie, Shiwen Xie*, Xiaofang Chen. Cooperative particle swarm optimizer with depth first search strategy for global optimization of multimodal functions. Applied Intelligence, 2022, 52: 10161-10180. 

[8]    Ziqing Deng, Xiaofang Chen, Shiwen Xie*, Yongfang Xie, Yubo Sun. Distributed process monitoring based on joint mutual information and projective dictionary pair learning. Journal of Process Control, 2021, 106: 130-141. 

[9]    Shiwen Xie, Yongfang Xie*, Tingwen Huang, Weihua Gui. Multiobjective-based optimization and control for iron removal process under dynamic environment. IEEE Transactions on Industrial Informatics, 2021, 17(1): 569-577. 

[10] Shiwen Xie, Yongfang Xie*, Hao Ying, Zhaohui Jiang, Weihua Gui. Neurofuzzy-based plant-wide hierarchical coordinating optimization and control: An application to zinc hydrometallurgy plant. IEEE Transactions on Industrial Electronics, 2020, 67(3): 2207-2219. 

[11] Shiwen Xie, Yongfang Xie*, Fanbiao Li, Chunhua Yang, Weihua Gui. Optimal setting and control for iron removal process based on adaptive neural network soft-sensor. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2020, 50(7): 2408-2420. 

[12] Mingxi Ai, Yongfang Xie, Shiwen Xie*, Jin Zhang, Weihua Gui. Fuzzy association rule-based set-point adaptive optimization and control for the flotation process. Neural Computing & Applications, 2020, 32(17): 14019-14029. 

[13] Shiwen Xie, Yongfang Xie*, Tingwen Huang, Weihua Gui, Chunhua Yang. Generalized predictive control for industrial process based on neuron adaptive splitting and merging RBF neural network, IEEE Transactions on Industrial Electronics, 2019, 66(2): 1192-1202. 

[14] Yongfang Xie, Jinjin Yu, Shiwen Xie*, Tingwen Huang, Weihua Gui. On-line prediction of ferrous ion concentration in goethite process based on self-adjusting structure RBF neural network. Neural Networks, 2019, 116: 1-10. 

[15] Shiwen Xie, Yongfang Xie, Fanbiao Li*, Zhaohui Jiang, Weihua Gui. Hybrid fuzzy control for the goethite process in zinc production plant combining type-1 and type-2 fuzzy logics. Neurocomputing, 2019, 366: 170-177. 

[16] Mingxi Ai, Yongfang Xie, Shiwen Xie*, Fanbiao Li, Weihua Gui, Data-driven-based adaptive fuzzy neural network control for the antimony flotation plant. Journal of the Franklin Institute, 2019, 356: 5944-5960. 

[17] Mingxi Ai, Yongfang Xie, Shiwen Xie*, Weihua Gui, Shape-weighted bubble size distribution based reagent predictive control for the antimony flotation process. Chemometrics and Intelligent Laboratory Systems, 2019, 192: 103821. 

[18] Shiwen Xie, Yongfang Xie*, Tingwen Huang, Weihua Gui, Chunhua Yang. Coordinated optimization for the descent gradient of technical index in the iron removal process. IEEE Transactions on Cybernetics, 2018, 48(12): 3313-3322. 

[19] Shiwen Xie, Yongfang Xie*, Hao Ying, Weihua Gui, Chunhua Yang. A hybrid control strategy for real-time control of the iron removal process of the zinc hydrometallurgy plants. IEEE Transactions on Industrial Informatics, 2018, 14(12): 5278-5288. 

[20] Shiwen Xie, Yongfang Xie*, Weihua Gui, Chunhua Yang. Weighted-coupling CSTR modeling and model predictive control with parameter adaptive correction for the goethite process. Journal of Process Control, 2018, 68, 254-267.

[21] Shiwen Xie, Yongfang Xie*, Chunhua Yang, Weihua Gui, Yalin Wang. Distributed parameter modeling and optimal control of the oxidation rate in iron removal process. Journal of Process Control, 2018, 61, 47-57. 

[22] Yongfang Xie, Shiwen Xie*, Yonggang Li, Chunhua Yang, Weihua Gui, Dynamic modeling and optimal control of goethite process based on the rate-controlling step. Control Engineering Practice, 2017, 58, 54-65. 

[23] Yongfang Xie, Shiwen Xie, Xiaofang Chen*, Weihua Gui, Chunhua Yang, Louis Caccetta. An integrated predictive model with an on-line updating strategy for iron precipitation in zinc hydrometallurgy. Hydrometallurgy, 2015, 151: 62-72. 

EI论文：

[1]    谢世文, 谢永芳*, 李勇刚, 阳春华, 桂卫华. 湿法炼锌沉铁过程氧化速率优化控制. 自动化学报, 2015, 41(12): 2036-2046. 

[2]    谢世文, 谢永芳, 阳春华, 蒋朝辉*, 桂卫华. 针铁矿法沉铁过程亚铁离子浓度预测. 自动化学报, 2014, 40(5): 830-837. 

[3]    丁浩峰, 谢永芳, 谢世文*, 王杰. 基于特征层密集连接与注意力机制的宽度学习系统及其在锌浮选过程的应用. 控制理论与应用,2023,40(6):1069-1078.

[4]    谢永芳, 李理, 谢世文*, 陈晓方. 基于半定量概率图模型的溯因分析方法. 控制理论与应用,2023,40(3):419-429.

会议论文：

[1]    Shiwen Xie, Jinjin Yu, Yongfang Xie*, Zhaohui Jiang, Weihua Gui. A two-layer optimization and control strategy for zinc hydrometallurgy process based on RBF neural network soft-sensor. 2019 1st International Conference on Industrial Artificial Intelligence (IAI), Shenyang, China, July 23-27, 2019.

[2]    Cheng Hu, Shiwen Xie*, Yongfang Xie, Xiaofang Chen. Development of domain knowledge graph: A case study on flotation process. 6th International Conference on Robotics and Automation Engineering (ICRAE), GuangZhou, China, Nov., 19-22, 2021.

[3]    Xi Chen, Shiwen Xie*, Yongfang Xie, Xiaofang Chen. Classification of Anode Current Signals Based on 1D Convolutional Neural Networks. 6th International Conference on Robotics and Automation Engineering (ICRAE), GuangZhou, China, Nov., 19-22, 2021.

[4]    Haofeng Ding, Shiwen Xie*, Yongfang Xie, Jie Wang. Broad learning system based on Elastic Net feature sparsity and dense. 2021 China Automation Congress (CAC), Beijing, China, Oct., 22-24 2021.

[5]    Ziqing Deng, Xiaofang Chen, Shiwen Xie, Jue Shi. Unsupervised feature selection based on robust self-representative dictionary pair learning with application to aluminum electrolysis. 2021 Chinese Automation Congress (CAC), Beijing, China, Oct., 22-24, 2021.

[6]    Jiuliang Zhou, Xiaofang Chen, Shiwen Xie, Yongfang Xie. Anode current for aluminum electrolysis cell condition identification based on improved temporal convolutional network[C]. 6th International Conference on Robotics and Automation Engineering, GuangZhou, China, Nov. 19-22, 2021.

[7]    Ye Zhu, Shiwen Xie*, Yongfang Xie, Xiaofang Chen. Recognition of aluminum electrolysis overheat trend based on DA-LSTM Neural Network. The 2021 International Conference on Information, Cybernetics, and Computational Social Systems, Beijing, China, Nov. 13-15, 2021.

[8]    Zixiong Ning, Shiwen Xie*, Yongfang Xie, Xiaofang Chen. Dual-stream multidimensional network for aluminum electrolysis process Superheat identification. 2022 China Automation Congress, Xiamen, China, Nov., 25-27, 2022.