（1）江苏省“双创博士”；

（2）江苏省科技副总；

（3）江苏省地下空间学会科学技术奖，特等奖；

【主持项目】

（1）国家自然科学基金；

（2）中国博士后科学基金；

（3）JW科技委XXX基金项目；

（4）江苏省高层次人才工程“双创博士”项目；

（5）中央高校基本科研业务费专项资金项目；

（6）中车工业研究院有限公司合作项目；

【参与项目】

（1）JW科技委国防科技创新快速响应项目；

（2）陆军工程大学预研项目；

（3）某XXX军品横向项目；

（4）中国铁路局合作项目；

【期刊论文】

（1）Kun Tang*, Li Yang, Yongfeng Ma, Tangyi Guo, Fang He. Context-Aware Attention Encoder-Decoder Network for Connected Heavy-Duty Vehicle Aggressive Driving Identification Under Naturalistic Driving Conditions[J]. IEEE Transactions on Intelligent Transportation Systems, 25(8): 9710-9722. (SCI, 中科院1区top)

（2）Kun Tang*, Shuyan Chen, Tangyi Guo, Yongfeng Ma, Aemal J. Khattak. An adaptive deep multi-task learning approach for citywide travel time collaborative estimation[J]. Expert Systems with Applications, 244: 123009.  (SCI, 中科院1区top)

（3）Kun Tang*, Tangyi Guo, Fei Shao, Yongfeng Ma, Aemal J. Khattak. Spatial-temporal traffic performance collaborative forecast in urban road network based on dynamic factor model[J]. Expert Systems with Applications, 225: 120090. (SCI, 中科院1区top)

（4）Kun Tang*, Shuyan Chen, Zhiyuan Liu. Citywide spatial-temporal travel time estimation using big and sparse trajectories [J]. IEEE Transactions on Intelligent Transportation Systems, 19(12): 4023-4034.(SCI, 中科院1区top)

（5）Kun Tang, Shuyan Chen*, Zhiyuan Liu, Aemal J. Khattak. A tensor-based Bayesian probabilistic model for citywide personalized travel time estimation[J]. Transportation Research Part C: Emerging Technologies, 90: 260-280. (SCI, 中科院1区top)

（6）Kun Tang, Shuyan Chen*, Aemal J. Khattak. Personalized travel time estimation for urban road networks: A tensor-based context-aware approach[J]. Expert Systems with Applications, 103: 118-132. (SCI, 中科院1区top)

（7）Kun Tang*, Bo Yang, Kai Ding. Deep Attention-based Network Combing Geometric Information for UWB Localization in Complex Indoor Environments[J]. IEEE Access, 12: 31488-31497. (SCI, Q2)

（8）Kun Tang, Shuyan Chen*, Aemal J. Khattak. A spatial-temporal multi-task collaborative learning model for multi-Step traffic flow prediction[J]. Transportation Research Record, 2672(45): 1-13. (SCI, Q3)

（9）Yongfeng Ma*, Kun Tang*, Shuyan Chen, Aemal J. Khattak, Yingjiu Pan. On-line aggressive driving identification based on in-vehicle kinematic parameters under naturalistic driving conditions[J]. Transportation Research Part C: Emerging Technologies, 114: 554-571. (SCI, 中科院1区top)

（10）Kun Tang, Shuyan Chen*, Aemal J. Khattak. Deep architecture for citywide travel time estimation incorporating contextual information[J]. Journal of Intelligent Transportation Systems, 25(3), 313-329. (SCI, Q2)

【会议论文】

（1）Tian Xu, Kun Tang*, Tangyi Guo. Attention encoder-decoder network based autonomous risk driving identification for connected heavy-duty vehicles[C]. International Conference on Autonomous Unmanned Systems (ICAUS). No. ICAUS2023-0144. (EI)

（2）Kun Tang*, Haochen Lv, Xuekun Zhong, Tian Xu, Tangyi Guo. Path-oriented green wave speed control model towards autonomous vehicle[C]. International Conference on Autonomous Unmanned Systems (ICAUS). No. ICAUS2023-0202. (EI)

（3）Kun Tang*, Xinyu Liu, Tian Xu, Tangyi Guo. Abrupt lane change recognition model towards autonomous vehicle based on lane line inclination[C]. International Conference on Autonomous Unmanned Systems (ICAUS). No. ICAUS2023-0181. (EI)

（4）Wanqian Yu, Kun Tang*, Jihan Jin, Jiyang Jiang. Multi-sensing pedestrian detection method based on an improved EPNet[C]. International Conference on Autonomous Unmanned Systems (ICAUS). No. ICAUS2023-0179. (EI)

（5）Kun Tang*, Tian Xu, Tangyi Guo. Research on topological characteristic and resilience of metro network based on hypergraph[C]. International Conference on Intelligent Transportation Engineering (ICITE). No. TE23-4606. (EI)

（6）Tian Xu, Kun Tang*, Mengmeng Yin, Tangyi Guo. Hypergraph-based node value evaluation for high-speed railway network using operation data[C]. The 103th Transportation Research Board (TRB). No. TRBAM-24-04710. (TRB)

（7）Kun Tang*, Tian Xu, Mengmeng Yin, Tangyi Guo. HyperTraffic: a hypergraph convolution network for urban traffic forecasting with high-order and multi-modal semantic correlations[C]. The 103th Transportation Research Board (TRB). No. TRBAM-24-04694. (TRB)

（8）Kun Tang*, Tian Xu, Tangyi Guo. Aggressive driving identification for connected heavy-duty vehicle under naturalistic driving condition: a context-aware attention encoder-decoder model[C]. The 103th Transportation Research Board (TRB). No. TRBAM-24-04668. (TRB)

（9）Mengmeng Yin, Kun Tang*, Tian Xu, Tangyi Guo. Construction and node value evaluation of road-rail-air multi-modal travel network: from a hyper-network perspective[C]. The 103th Transportation Research Board (TRB). No. TRBAM-24-04729. (TRB)

（10）Zhengyang Bei, Kun Tang*, Tangyi Guo. Constructing and Analyzing the Resilience of Integrated Multi-modal Transportation Hyper-network: A case Study of the United Kingdom [C]. The 104th Transportation Research Board (TRB). No. TRBAM-25-05782. (TRB)

【发明专利】

（1）基于动态因子模型的城市路网时空交通状态协同预测方法，国家发明专利，授权，专利号：ZL202110082897.7

（2）基于自适应多任务深度学习的城市路网行程时间估计方法，国家发明专利，授权，专利号：ZL201810141263.2

（3）融合多模式高阶语义相关性的城市交通超图卷积预测方法，国家发明专利，授权，专利号：ZL 202310268121.3

（4）结构性数据缺失下基于超图神经网络的城市交通预测方法，国家发明专利，授权，专利号：ZL 202311435923.5

（5）基于深度注意力机制和几何信息的超宽带室内定位方法，国家发明专利，授权，专利号：ZL 202310001992.9

（6）基于动态时空图卷积循环网络的交通流预测方法、设备及存储介质，国家发明专利，授权，专利号：ZL 202111575360.0

（7）基于“自下而上”策略的GPS轨迹出行方式链识别方法，国家发明专利，授权，专利号：ZL 202210466596.9

（8）一种基于uwb声模块组合定位的方法，国防发明专利，授权，专利号：ZL 202118000456.9

（9）基于Encoder-Decoder注意力网络与LSTM的异常驾驶行为在线识别方法，国家发明专利，受理，专利号：202111675120.8

（10）基于超图深度网络的城市多方式交通超网络态势协同预测方法，国家发明专利，受理，专利号：202210916015.7

研究生课程
（1）专业必修课：《交通数据分析与应用》；

本科生课程

（1）专业基础课：《智能优化算法》

欢迎具有机器学习基础，有志于数据分析、网络分析与控制、目标探测与识别等方向研究的同学报考。