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2016.09— 2019.06 中南大学 交通运输工程 博士
2018.10—2019.01 莫纳什大学 机械与航空航天工程系 联合培养
2013.09—2016.06 中南大学 交通运输工程 硕士
2009.09—2013.06 中南大学 交通设备信息工程 学士
2019.07—至今 raybetapp官网 交通运输学院 副教授
2024.04—2024.09 铁科院电子所挂职锻炼
本科生课程：
铁路货物运输组织与技术
综合交通规划与设计
研究生课程：
现代货物运输技术
学术写作能力
A vulnerability assessment with freight flow data of railway freight transportation network in Northeast China[J]. Journal of Transport Geography, 2025, 129: 104416.(SCI 中科院一区 top，IF:6.3)
Distributed Traffic Signal Control Model for Accurate Policy Learning Under Dynamic Traffic Flow: A GraphForecast-State Vector Driven Deep Reinforcement Learning Framework[J].IEEE Transactions on Intelligent Transportation Systems, 2025,DOI:10.1109/TITS.2025.3567841. (SCI 中科院一区 top，IF: 8.5)
WGformer: A Weibull-Gaussian Informer based model for wind speed prediction[J]. Engineering Applications of Artificial Intelligence, 2024, 131: 107891. (SCI 中科院一区 top，IF: 8)
多层级协同的地铁应急救援基地地址优化[J]. 铁道运输与经济, 2024.
MRIformer: A multi-resolution interactive transformer for wind speed multi-step prediction[J]. Information Sciences, 2024, 661: 120150 (SCI 中科院一区 top，IF: 8.1)
Data Analysis and Preprocessing Techniques for Air Quality Prediction: A Survey[J]. Stochastic Environment Research and Risk Assessment, 2024. (SCI 中科院二区，IF: 4.2)
A multi-factor driven spatiotemporal wind power prediction model based on ensemble deep graph attention reinforcement learning networks[J]. Energy, 2023, 263: 126034. (SCI 中科院一区 top，IF: 9)高速铁路预售期旅客购票量分布预测[J]. 铁道科学与工程学报, 2023.
Attention mechanism is useful in spatio-temporal wind speed prediction: Evidence from China[J]. Applied Soft Computing, 2023, 148: 110864. (SCI 中科院一区 top，IF: 8.7)
An ensemble convolutional reinforcement learning gate network for metro station PM2.5 forecasting[J]. Stochastic Environment Research and Risk Assessment, 2023. (SCI 中科院二区，IF: 4.2)
Wind-speed prediction model based on variational mode decomposition, temporal convolutional network, and sequential triplet loss[J]. Sustainable Energy Technologies and Assessments, 2022, 52: 101980. （中科院二区，IF: 8）Improving Synchronization in High-Speed Railway and Air Intermodality: Integrated Train Timetable Rescheduling and Passenger Flow Forecasting[J]. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(3): 2651-2667. (SCI 中科院一区 top，IF: 8.5)
A new ensemble deep graph reinforcement learning network for spatio-temporal traffic volume forecasting in a freeway network[J]. Digital Signal Processing, 2022, 123: 103419. (SCI 中科院三区，IF: 2.9)
Integrated optimization model for hierarchical service network design and passenger assignment in an urban rail transit network: A Lagrangian duality reformulation and an iterative layered optimization framework based on forward-passing and backpropagation[J]. Transportation Research Part C, 2022, 144: 103877. (SCI 中科院一区 top，IF: 8.3)
A dynamic ensemble deep deterministic policy gradient recursive network for spatiotemporal traffic speed forecasting in an urban road network[J]. Digital Signal Processing. 2022, 129:103643. (SCI 中科院三区，IF: 2.9)
A new multi-data-driven spatiotemporal forecasting model based on an ensemble graph reinforcement learning convolutional network [J]. Atmospheric Pollution Research, 2021, 12: 101197. (SCI 中科院三区，IF: 4.5)
Wind speed prediction based on singular spectrum analysis and neural network structural learning [J]. Energy Conversion and Management, 2020, 216:112956. (SCI 中科院一区 top，IF: 10.4)Wind speed prediction model using singular spectrum analysis, empirical mode decomposition and convolutional support vector machine[J]. Energy Conversion and Management, 2019, 180: 196-205. (SCI 中科院一区 top，IF: 10.4，1%高被引论文)
Smart wind speed deep learning based multi-step forecasting model using singular spectrum analysis, convolutional Gated Recurrent Unit network and Support Vector Regression[J]. Renewable Energy, 2019, 143: 842–854. (SCI 中科院一区 top，IF: 8.7)
Wind Speed Forecasting Method Using Wavelet, Extreme Learning Machine and Outlier Correction Algorithm [J]. Energy Conversion and Management, 2017, 151: 709-722. (SCI 中科院一区 top，IF: 10.4)
城轨系统全生命周期成本关键要素辨识与分析方法研究[J]. 中国基础科学, 2018, 20(126): 31-35.
Comparison of three new intelligent wind speed forecasting approaches based on Wavelet Packet Decomposition, Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Artificial Neural Networks[J]. Energy Conversion and Management, 2018, 155: 188-200. (SCI 中科院一区 top，IF: 10.4，1%高被引论文)
Wind speed forecasting method based on deep learning strategy using empirical wavelet transform, long short term memory neural network and Elman neural network[J]. Energy Conversion and Management, 2018, 156: 498-514. (SCI 中科院一区 top，IF: 10.4，0.1%热点论文)
Smart multi-step deep learning model for wind speed forecasting based on variational mode decomposition, singular spectrum analysis, LSTM network and ELM[J]. Energy Conversion and Management, 2018, 159: 54-64. (SCI 中科院一区 top，IF: 10.4，1%高被引论文)
An experimental investigation of three new hybrid wind speed forecasting models using multi-decomposing strategy and ELM algorithm[J]. Renewable Energy, 2018, 123: 694-705. (SCI 中科院一区 top，IF: 8.7，1%高被引论文)
Smart deep learning based wind speed prediction model using wavelet packet decomposition, convolutional neural network and convolutional long short term memory network[J]. Energy Conversion and Management, 2018, 166: 120-131. (SCI 中科院一区 top，IF: 10.4，1%高被引论文)
一种车货协同的铁路运输履带货物的轮挡装置[P]. 中国专利：ZL 2024 2 2034729.2, 2025-05-23.（已授权）
一种角度和位置纵向可调的铁路运输履带式货物固定装置[P]. 中国专利：ZL202110676715.9, 2025-01-03.（已授权）
一种基于轮式货物运输的多用途铁路平车车体[P].中国专利：ZL202110203487.3, 2022-10-04.（已授权）
一种铁路敞车用钢座架卡挡[P].中国专利：ZL202121732472.8, 2022-01-25.（已授权）
一种履带式货物加固装置[P]. 中国专利：ZL202110885821.8, 2022-06-28.（已授权）
一种铁路运输途中货物位移量实时远程在线监测系统[P].中国专利：ZL202011192556.7, 2021-08-10.（已授权）
一种基于气象传感时序模式的运载机器人智能识别楼层的方法[P].中国专利：ZL201710631966.9, 2018-03-27.（已授权）
一种运载机器人识别楼层的气象参数智能融合处理方法[P].中国专利：ZL201710631218.0, 2018-03-27.（已授权）
一种智能环境运载机器人识别楼层的参数化测量多模型智能融合方法[P].中国专利：ZL201710630336.X, 2018-04-13.（已授权）
一种强风高速铁路沿线风速空间网络构造预测方法[P].中国专利：ZL201611024045.8, 2017-07-28.（已授权）
一种融合多测风站实测数据的铁路沿线风速预测方法[P].中国专利：ZL201611029514.5, 2017-08-18.（已授权）
一种强风高速铁路沿线风速自适应分解预测方法[P].中国专利：ZL201611029592.5, 2018-01-09.（已授权）
基于神经网络的空铁联运客流预测软件V1.0.
基于嵌入式的铁路货物装载加固安全状态监测系统V1.0.
铁路大风智能预警管控系统.
铁路货物装载加固智能分析系统V1.0.
期刊审稿：IEEE Transactions on intelligent transportation systems、Journal of Transport Geography、Transportmetrica A、Information Sciences、Engineering Applications of Artificial Intelligence、Applied Energy、Energy Conversion and Management、Applied Intelligence、Energy、Renewable Energy、Journal of Cleaner Production、Journal of Vibration and Control、Physica A、Measurement、中南大学学报、铁道科学与工程学报、铁道运输与经济等
会议审稿：TRB、COTA、ISROR等
世界交通运输大会轨道交通学部委员、中国人工智能学会自然计算与数字智能城市委员、中国计算机学会（智能交通、大数据、计算机视觉）委员
中国运筹学会会员、中国管理科学与工程学会会员
国标无损检测超声波、磁粉2级资质；美标超声波检测2级资质