个人信息：

2012.9—2015.7 北京邮电大学 博士

2015.9—2017.7 北京科技大学 博士后

2018.3—2019.3 德国洪堡大学 访问学者

2015.7—2021.7 北京科技大学 副教授

2021.7—至今 北京科技大学 教授

王卫苹，教授，北京科技大学发展规划处挂职副处长，计算机系科研主任，德国洪堡大学高级访问学者。北京物联网学会理事，北京物联网学会青年委员会秘书长，北京图象图形学学会女科技工作者委员会秘书长，中国自动化学会智能自动化专业委员会委员，中国神经科学学会类脑分会专委会委员。智能系统学报客座编辑，MMR期刊以及Brain-X科学编辑。IEEE Transactions on Neural Networks and Learning System、IEEE Transactions on Cybernectics、Neural Networks等知名国际SCI期刊审稿专家。主持与重点参与国家自然科学基金、国际联合基金重点项目、科技部国际合作项目、重点研发计划子课题、博士后基金、广东省创新发展项目及横向课题等项目30余项。发表SCI等高水平科技论文90余篇，获得软著与专利20余项，获得河南省科技进步二等奖，中国通信学会最佳论文奖等奖项。曾指导硕博研究生30余名。

研究方向：

类脑计算， 脑认知机理， 医工交叉， 主动健康， 人工智能， 工控网络安全， 网络信息安全

在顺德创新学院的基础科研条件：

团队目前教授2人，副教授2人，讲师1人，博士后1人，培养硕士生10余人，依托实验室开展了面向 “碳中和”这一重大需求，与澳门大学智慧城市物联网国家重点实验室开展智慧能源合作研究，共同申请并完成佛山市人民政府科技创新专项资金项目“大数据驱动的智能光伏楼宇能量管理技术”的研究。并且实验室还开展了“大数据驱动的风电机组动态发电性能监测技术”研究工作。在智慧医疗领域，实验室与南方医科大学顺德医院神经内科合作，申报并开展了“数据驱动的阿尔兹海默病早期预测与干预控制研究”的研究工作，以及进行了“面向CT影像数据的急性缺血性卒中梗死灶分割模型研究”工作。在成果转化方面，所研究的成果在医院也进行了落地转化，以及与深圳璀月科技有限公司等签订了多项成果转化协议。

依托顺德创新学院科研项目：

大数据驱动的风电机组动态发电性能监测技术，北京科技大学顺德创新学院科技创新专项,2020.1.1-2021.12.31，参与；

大数据驱动的智能光伏楼宇能量管理技术，北京科技大学顺德创新学院科技创新专项,2021.9.1-2023.8.31，参与；

数据驱动的阿尔兹海默病早期预测与干预控制研究，北京科技大学顺德创新学院科技创新专项,2021.9.1-2023.8.31，项目负责人；

面向CT影像数据的急性缺血性卒中梗死灶分割模型研究，北京科技大学顺德创新学院科技创新专项,2021.9.1-2023.8.31，参与。

代表性成果：

[1] M. Yuan, W. Wang*, Z. Wang, X. Luo. Exponential synchronization of delayed memristor-based uncertain complex-valued neural networks for image protection[J]. IEEE Transactions on Neural Networks and Learning Systems. 2020.DOI：10.1109/TNNLS.2020.2977614.

[2] W. Wang*, C. He, Z. Wang, X. Mo, K.Tian, D. Fan, X. Luo, M. Yuan, J. Kurths. Dynamic analysis of disease progression in Alzheimer's Disease under the influence of hybrid synapse and spatially correlated noise[J]. Neurocomputing, 2021, 456: 23-35.

[3] W. Wang*, C. He, Z. Wang, D. Fan, M. Yuan, X. Luo, J. Kurths. Dynamic analysis of synaptic loss and synaptic compensation in the process of associative memory ability decline in Alzheimer's Disease[J]. Applied Mathematics and Computation, 2021, 408: 126372.

[4] Wang W, Sun Y, Yuan M, et al. Projective synchronization of memristive multidirectional associative memory neural networks via self-triggered impulsive control and its application to image protection[J]. Chaos, Solitons & Fractals, 2021, 150: 111110.

[5] Wang W, Wang Z, Zhou Z, et al. Anomaly detection of industrial control systems based on transfer learning[J]. Tsinghua Science and Technology, 2021, 26(6): 821-832.

[6] Wang W, Le J, Wang Z, Luo X, Kurths J,Yuan M, and Ma Y. Event-Triggered Consensus Control for High-Speed Train With Time-Varying Actuator Fault[J]. IEEE Access, 2020, 8: 50553-50564.

[7] Wang W , Han B , Guo Y , et al. Fault-tolerant platoon control of autonomous vehicles based on event-triggered control strategy[J]. IEEE Access, 2020, PP(99):1-1.

[8] W. Wang, X. Jia, X. Luo, J. Kurths, M. Yuan. Fixed-time Synchronization Control of Memristive MAM Neural Networks With Mixed Delays and Application in Chaotic Secure Communication, Chaos Solitons & Fractals, 2019, 126, 85-96.

[9] W. Wang, X. Wang, X. Luo, M. Yuan. Finite-time Projective Synchronization of Memristor-based BAM Neural Networks and Applications in Image Encryption[J], IEEE ACCESS, 2018, 6: 56457-56476.

[10] W. Wang, X. Yu, X. Luo, Jürgen Kurths. Synchronization Control of Memristive Multidirectional Associative Memory Neural Networks And Applications in Network Security Communication[J]. IEEE Access, 2018, 6: 36002-36018.

[11] W. Wang, X. Yu, X. Luo, et al. Finite-time Synchronization of Chaotic Memristive Multidirectional Associative Memory Neural Networks And Applications in Image Encryption[J]. IEEE Access, 2018:35764-35779.

[12] W. Wang, L. Li, H. Peng, J. Kurths, J. Xiao, Y. Yang. Anti-synchronization of coupled memristive neutral-type neural networks with mixed time-varying delays and stochastic perturbations via randomly occurring control[J]. Nonlinear Dynamics, 2016, 83:2143-2155.

[13] Wang W, Jia X, Wang Z, et al. Fixed-time synchronization of fractional order memristive MAM neural networks by sliding mode control[J]. Neurocomputing, 2020, 401: 364-376.

[14] Wang, W., Wang, C., Guo, Y., Luo, X., & Gao, Y. (2020). Self-triggered Consensus of Vehicle Platoon System with Time-varying Topology. Frontiers in Neurorobotics, 14, 53.

[15] W. Wang, X. Yu, X. Luo, L. Wang, L. Li, Jürgen Kurths, W. Zhao, J. Xiao. The Stability of Memristive Multidirectional Associative Memory Neural Networks With Time-varying Delays in the Leakage Terms via Sampled-data Control[J]. Plos One, 2018, 13(9):e0204002.

[16] W. Wang, M. Yu, X. Luo, L. Liu, M. Yuan, W. Zhao. Synchronization of memristive BAM neural networks with leakage delay and additive time-varying delay components via sampled-data control[J]. Chaos, Solitons & Fractals. 2017, 104: 84-97.

[17] M. Yuan, W. Wang, X. Luo, et al. Finite-time anti-synchronization of memristive stochastic BAM neural networks with probabilistic time-varying delays[J]. Chaos Solitons & Fractals, 2018, 113:244-260.

[18] W Wang，C Wang，Y Guo，M Yuan，Y Gao. Industrial Control Malicious Traffic Anomaly Detection System Based on Deep Autoencoder.Frontiers in Energy Research, 2021, 8: 380.

[19] W. Wang, X. Yu, X. Luo, L. Li. Stability Analysis of Memristive Multidirectional Associative Memory Neural Networks and Applications in Information Storage[J]. Modern Physics Letters B, 2018, 32(18):1-28.

[20] W. Wang, M. Wang, X. Luo, et al. Passivity of memristive BAM neural networks with leakage and additive time-varying delays[J]. Modern Physics Letters B, 104(1):84-97.

[21] W. Wang, M. Yuan, X. Luo, et al. Anti-synchronization control of BAM memristive neural networks with multiple proportional delays and stochastic perturbations[J]. Modern Physics Letters B, 2018, 32(3):1850028

[22] Wang, W., Wang, M., Luo, X., Li, L., & Zhao, W. (2018). Passivity of memristive BAM neural networks with probabilistic and mixed time-varying delays. Mathematical Problems in Engineering, 2018 . DOI:10.1155/2018/5830160

[23] Guo Y , Han B , Wang W , et al. State Estimation and Event-Triggered Control for Cyber-Physical Systems under Malicious Attack[J]. Mathematical Problems in Engineering, 2019, 2019(8):1-10.

[24] M. Yuan, W. Wang, X. Luo, L. Li. Asymptotic Anti-synchronization of Memristor-based BAM Neural Networks with Probabilistic Mixed Time-varying Delays and Its Application [J]. Modern Physics Letters B, 2018, 32(24): 1850287.

[25] M. Yu, W. Wang, M. Yuan, et al. Exponential Antisynchronization Control of Stochastic Memristive Neural Networks with Mixed Time-Varying Delays Based on Novel Delay-Dependent or Delay-Independent Adaptive Controller[J]. Mathematical Problems in Engineering,2017. DOI: 10.1155/2017/8314757

[26] X. Luo, X. Yang, W. Wang, X. Chang, X. Wang, Z. Zhao. A novel hidden danger prediction method in cloud-based intelligent industrial production management using timeliness managing extreme learning machine[J]. China Communications, 2016, 13(7): 74-82.

[27] M. Yuan, W. Wang, X. Luo, et al. Synchronization of a Class of Memristive Stochastic Bidirectional Associative Memory Neural Networks with Mixed Time-Varying Delays via Sampled-Data Control[J]. Mathematical Problems in Engineering, 2018：1-24.

[28] Zhao, H., Zheng, M., Li, S., & Wang, W. (2018). New results on finite-time parameter identification and synchronization of uncertain complex dynamical networks with perturbation. Modern Physics Letters B, 32(09), 1850112.

[29] M. Yuan, W. Wang, X. Luo, Lixiang Li, Jürgen Kurths. Exponential Lag Function Projective Synchronization of Memriive Memory Neural Networks via Hybrid Control [J]. Modern Physics Letters B, 2018, 32(9):1850116.

[30] Weiping Wang, Chunyang Wang, Zhen Wang, Baijing Han, Chang He, Jun Cheng, Xiong Luo, Manman Yuan, Jürgen Kurths. Nonlinear consensus-based autonomous vehicle platoon control under event-triggered strategy in the presence of time delays[J]. Applied Mathematics and Computation, 2021, 404: 126246.

[31] M. Chen, Y. Li, X. Luo, W. Wang, L. Wang, W. Zhao. A Novel Human Activity Recognition Scheme for Smart Health Using Multilayer Extreme Learning Machine. IEEE Internet of Things Journal, 2018, 6(2):1410 - 1418.

[32] X. Luo, J. Sun, L. Wang, W. Wang*, W. Zhao, J. Wu, J. Wang. Short-Term Wind Speed Forecasting via Stacked Extreme Learning Machine With Generalized Correntropy, IEEE Transactions on Industrial Informatics, 2018, 14(11): 4963-4971.

[33] X. Luo, Y. Xu, W. Wang, M. Yuan, X. Ban, Y. Zhu, W. Zhao. Towards enhancing stacked extreme learning machine with sparse autoencoder by correntropy[J]. Journal of The Franklin Institute, 2018, 355(4): 1945-1966.

[34] X. Luo, C. Jiang, W. Wang*, Y. Xu, J. Wang, W. Zhao. User behavior prediction in social networks using weighted extreme learning machine with distribution optimization. Future Generation Computer Systems, 2019, 93:1023-1035.

[35] X. Luo, W. Zhou, W. Wang*, Y. Zhu, J. Deng. Attention-Based Relation Extraction with Bidirectional Gated Recurrent Unit and Highway Network in The Analysis of Geological Data. IEEE Access, 2018,6(1):5705 - 5715.

[36] X. Luo, J. Liu, D. Zhang, W. Wang, Y. Zhu. An Entropy-Based Kernel Learning Scheme toward Efficient Data Prediction in Cloud-Assisted Network Environments[J]. Entropy, 2016, 18:1-18.

[37] W. Wang, L. Li, H. Peng, J. Kurths, J. Xiao, Y. Yang. Finite-time anti-synchronization control of memristive neural networks with stochastic perturbations[J]. Neural Processing letters, 2016, 43:49-63.

[38] W. Wang, L. Li, H. Peng, J. Kurths, J. Xiao, Y. Yang. Anti-synchronization control of memristive neural networks with multiple proportional delays[J]. Neural Processing letters, 2016, 43:269-283.

[39] Y. Guo, Y. Luo, W. Wang, X. Luo, C. Ge, J. Kurths, M. Yuan, Y. Gao. Fixed-Time Synchronization of Complex-Valued Memristive BAM Neural Network and Applications in Image Encryption and Decryption[J], International Journal of Control, Automation and Systems, 2019:1-15.

[40] M. Yuan, X. Luo, W. Wang, et al. Pinning Synchronization of Coupled Memristive Recurrent Neural Networks with Mixed Time-Varying Delays and Perturbations[J]. Neural Processing Letters, 2018:1-24.

[41] Y. Xu, X. Luo, W. Wang, W. Zhao. Efficient DV-HOP localization for wireless cyber-physical social sensing system: A correntropy-based neural network learning scheme[J]. Sensors, 2017, 17(1):1-17.

[42] X. Luo, J. Deng, J. Liu, W. Wang, X. Ban, J. Wang. A quantized kernel least mean square scheme with entropy-guided learning for intelligent data analysis.[J] China Communations, 2017, 14(7): 127-136.

[43] X. Luo, J. Deng, W. Wang, J. Wang, W. Zhao. A quantized kernel learning algorithm using a minimum kernel risk-sensitive loss criterion and bilateral gradient technique[J]. Entropy, 2017, 19(7):1-15

[44] X. Luo, Y. Lv, M. Zhou, W. Wang, W. Zhao. A laguerre neural network-based ADP learning scheme with its application to tracking control in the Internet of Things[J]. Pers Ubiquit Comput, 2016, 20:361-372.

[45] M. Yu, W. Wang, M. Yuan, X. Luo, L. Liu. Exponential antisynchronization control of stochastic memristive neural networks with mixed time-varying delays based on novel delay-dependent or delay-independent adaptive controller[J]. Mathematical Problems in Engineering, 2017, 2017:1-16.

[46] Ping Y, Song W, Zhang Z, Wang W, Wang B. A Multi-Keyword Searchable Encryption Scheme Based on Probability Trapdoor over Encryption Cloud Data[J]. Information, 2020, 11(8): 394.

代表性科研项目：

1. 2017.6-2020.12

科技部国家重点研发计划子课题

题目：基于高通量实验和计算的材料结构-性能数据采集与数据库融合技术

2. 2022.1-2024.12

国家自然科学基金面上项目，62271045

题目：跨模态多尺度AD脑网络机制分析及早期预警和个性化脑功能重塑研究

3. 2020.1-2022.12

国家自然科学基金中俄地区合作国际联合基金，81961138010

题目：基于网络分析的人脑精神类疾病整合动力学研究

4. 2019.1-2021.12

国家自然科学基金，U1836106

题目：深度强化学习框架下基于序列分析的工控系统恶意软件识别及预警技术研究

5. 2021.9-2022.9

人工智能与材料专业交叉项目

题目：基于生成式对抗网络的新型析氧反应电催化剂

6. 2016.4-2017.4

博士后基金面上项目

题目：忆阻神经网络在联想记忆应用中的关键基础理论研究

7. 2017.01-2019.12

国家自然科学青年基金，61603032

题目：具有联想记忆的忆阻神经网络稳定性分析及应用研究，

8. 2022.1-2024.1

北医三院创新转化基金，BYSYZHKC2021107

题目：阿尔茨海默病早期筛查预警系统研发

9. 2021.9-2023.9

佛山市科技创新专项资金项目，BK211603

题目：数据驱动的阿尔茨海默病早期预测与干预控制研究

获得奖励/专利：

获得软著与专利10余项获

得河南省科技进步二等奖

中国通信学会最佳论文奖