AI团队

宁念文  博士/讲师/硕导

主要从事图神经网络、智能交通、时空信息处理和智能医学数据处理等相关研究。主持河南省重点研发与推广专项（科技攻关）项目1项，bevictor伟德官网医工交叉项目1项；作为项目骨干分别参与了国家重点基础研究发展计划（973项目）、国家重点研发、国家自然科学联合基金重点支撑、国家自然科学基金面上等项目。参与专著撰写2部，发表学术论文20余篇，授权专利多项。任中国计算机学会会员。

电子邮箱：nnw@henu.edu.cn

教育及工作经历：

2021.06-至今，bevictor伟德官网，伟德国际BETVLCTOR, 教师

2017.09-2021.06，北京邮电大学，计算机学院，博士

2014.09-2017.06，河南理工大学，计算机科学与技术学院，硕士

研究领域：

图深度学习、时空大数据分析、智能交通、医学数据挖掘

主要荣誉:

2013年，取得软件设计师资格认证

2017年，获得优秀专业实践成果奖

2020年，获得优秀研究生干部

主讲课程：

《人工智能编程基础》（本科课程）

《大数据分析与处理》（本科课程）

《概率图模型》（本科、研究生课程）

《图深度学习》（研究生课程）

论文：

n 2023：

[1] Zhou Y, Wang H, Ning N*, et al. A bidirectional trajectory contrastive learning model for driving intention prediction [J]. Complex & Intelligent Systems, 2023: 1-15.

[2] 于泽，宁念文*，郑燕柳等. 深度强化学习驱动的智能交通信号控制策略综述, 计算机科学. 2023,50(04): 159-171

n 2022：

[1] Zhu Y, Hu L, Ning N, et al. A lexical psycholinguistic knowledge-guided graph neural network for interpretable personality detection[J]. Knowledge-Based Systems, 2022, 249: 108952.

[2] Hou H, Ning N*, Shi H, et al. Spatial-Temporal Multiscale Fusion Graph Neural Network for Traffic Flow Prediction[C]//2022 IEEE 7th International Conference on Intelligent Transportation Engineering (ICITE). IEEE, 2022: 272-277.

[3] Cheng X, Shi H, Jin Z, Ning N，et al. Energy Efficiency Aware Collaborative Multi-UAV Deployment for Intelligent Traffic Surveillance[C]//2022 IEEE Latin-American Conference on Communications (LATINCOM). IEEE, 2022: 1-6.

n 2021：

[1] Ning N, Li Q, Zhao K, et al. Multiplex network embedding model with high-order node dependence[J]. Complexity, 2021, 2021: 1-18.

[2] Ning N, Yang Y, Song C, et al. An adaptive node embedding framework for multiplex networks[J]. Intelligent Data Analysis, 2021, 25(2): 483-503.

[3] Song C, Ning N, Zhang Y, et al. A multimodal fake news detection model based on crossmodal attention residual and multichannel convolutional neural networks[J]. Information Processing & Management, 2021, 58(1): 102437.

[4] Song C, Ning N, Zhang Y, et al. Knowledge augmented transf-ormer for adversarial multidomain multiclassification multimodal fake news detection[J]. Neurocomputing, 2021, 462: 88-100.

[5] Chang H, Ning N. An intelligent multimode clustering mechanism using driving pattern recognition in cognitive internet of vehicles[J]. Sensors, 2021, 21(22): 7588.

[6] Zhang Y, Ning N, Zhou P, et al. UT-ATD: Universal Transformer for Anomalous Trajectory Detection by Embedding Trajectory Information[C]//DMSVIVA. 2021: 70-77.

[7] Zhan S, Ning N, Zhao K, et al. Disentangled-based Adver-sarial Network for Multiplex Network Embedding[C]//2021 International Joint Conference on Neural Networks (IJCNN). IEEE, 2021: 1-8.

[8] Li Z, Ning N, Peng C, et al. Dependency parsing represent-ation learning for open information extraction[C]//Know-ledge Science, Engineering and Management(KSEM), 2021: 433-444.

[9] Li Q, Ning N, Wu B, et al. Embedding-Based Network Alignment Using Neural Tensor Networks[C]//Knowledge Science, Engineering and Management(KSEM), 2021: 401-413.

[10] Wang H, Zhou D, Zhang Y, Ning N,et al. SACS-LSTM: A Vehicle Trajectory Prediction Method Based on Self-Attention Mechanism#[C]//Proceedings of the 2021 5th International Conference on Electronic Information Technology and Computer Engineering. 2021: 1061-1067.

n 2020:

[1] Zhou P, Luo Y, Ning N, et al. Continuous Similarity Learning with Shared Neural Semantic Representation for Joint Event Detection and Evolution[J]. Computational Intelligence and Neuroscience, 2020, 2020.

[2] Ning N, Long F, Wang C, et al. Nonlinear structural fusion for multiplex network[J]. Complexity, 2020, 2020: 1-17.

[3] Long F, Ning N, Zhang Y, et al. Mining latent academic social relationships by network fusion of multi-type data [J]. Social Network Analysis and Mining, 2020, 10: 1-16.

n 2019:

[1] Zhang Y, Wu B, Ning N, et al. Dynamic topical community detection in social network: A generative model approach[J]. IEEE Access, 2019, 7: 74528-74541.

[2] Long F, Ning N, Song C, et al. Strengthening social networks analysis by networks fusion[C]//Proceedings of the 2019 IEEE/ACM international conference on advances in social networks analysis and mining. 2019: 460-463.

[3] Sun S, Wu B, Zhang Z, Ning N, et al. A hierarchical insurance recommendation framework using GraphOLAM approach[C]//Proceedings of the 2019 IEEE/ACM Internati-onal Conference on Advances in Social Networks Analysis and Mining. 2019: 757-764.

[4] Yang Y, Ning N, Zhang Y, et al. Community preserving node embedding based on seed-expansion sampling[C]//2019 IEEE Fourth International Conference on Data Science in Cyberspace (DSC). IEEE, 2019: 459-465.

[5] Ning N, Song C, Zhou P, et al. An adaptive cross-layer sampling-based node embedding for multiplex networks[C]// 2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI). IEEE, 2019: 1515-1519.

[6] Zhang Y, Ning N, Lv J, et al. Jointly Modeling Community and Topic in Social Network[C]//Knowledge Science, Enginee-ring and Management, 2019: 209-221.

[7] Zhou P, Zhang B, Wu B, Luo Y, Ning N，et al. A Novel Event Detection Model Based on Graph Convolutional Network[C]// Web Information Systems Engineering，2019: 172-184.

n 2018：

[1] Ning N, Wu B, Peng C. Representation learning based on influence of node for multiplex network[C]//2018 IEEE Third International Conference on Data Science in Cyberspace (DSC). IEEE, 2018: 865-872.

[2] Ning N, Wu B.Community detection in multiplex networks via consensus matrix[J].网络与信息安全学报(英文版),3(9):67-77.

科研项目：

[1] 河南省科技厅, 河南省重点研发与推广专项（科技攻关）：222102210067, 面向城市复杂交通网的异质图深度学习与动态优化策略研究, 2022.01-2023.12, 10万元, 在研, 主持。

[2] bevictor伟德官网，医工交叉项目：基于数字病理认知计算的非小细胞肺癌肿瘤微环境分析及评估研究，2022.06-2023.12, 8万元，在研，主持。

[3] 国家自然科学联合基金重点支撑项目：基于网络行为的人物心理刻画, U1936220, 2020/01–2023/12, 265万元，负责人：仲红教授，在研，参与。

[4] 国家自然科学基金面上项目：融合视频数据的社交网络广度学习算法研究，61972047，2020/01–2023/12，58万元，负责人：吴斌教授，在研，参与。

[5] 国家重点研发计划：司法行政跨区域联合执法协同支撑技术研究: 2018YFC0831500, 2018.07–2021.06, 5407万元，负责人：吴斌教授，结题，参与。

[6] 国家重点基础研究发展计划项目（973项目）：社交网络分析与网络信息传播的基础研究，2013CB329600，2013/01-2017/12，1470万元，负责人：方滨兴院士，结题，参与。

专利：

[1] 基于智能反射面的空地移动网络携能公平通信方法，CN202211472603.2

[2] 一种考虑公平性原则的多智能体协同资源分配方法，CN202210806132.8

[3] 一种基于多智能体协同优化的无人机资源调度方法，CN202111525070.5

[4] 一种社交关系分类模型训练方法、装置、电子设备及介质，CN201711136951.1

[5] 一种网络节点的相似度计算方法，CN201611151942.5

[6] 安全势场下基于informer神经网络的驾驶行为预测方法，CN202211137976.4