姓名: 曹阳
职称: 教授、博士、硕士生导师
部门: 2026世界杯官网
联系方式: 0513-85012660
Email: caoyangnt@ntu.edu.cn
学历及学术经历：
曹阳，男，江苏如皋人，1986年1月生，中共党员，博士，教授，博士生导师。2012年毕业于苏州大学计算数学专业，2017.6-2017.9赴英国莱斯特大学、2019.1-2020.1赴瑞典乌普萨拉大学信息技术系访学，江苏省优秀硕士学位论文(2010年)和江苏省优秀博士学位论文(2013年)获得者。入选江苏省“青蓝工程”优秀青年骨干教师(2016年)、江苏省第五期“333工程”第三层次人才(2018年)、江苏省“青蓝工程”中青年学术带头人(2021年)、交通运输部“交通运输青年科技英才”(2021年)。主要从事深度学习中的科学计算问题、超大规模集成电路版图布局优化设计、数值代数、偏微分方程数值解、灰色系统理论与算法、大数据分析等方面的研究。主持国家自然科学基金青年基金1项、国家自然科学基金面上项目2项、市厅级课题6项。获得中国计算数学学会“应用数值代数奖”、中国自动化学会科技进步二等奖、中国智能交通协会科学技术三等奖、中国产学研合作创新成果二等奖、南通市第九届自然科学学术论文三等奖等科研奖励。指导学生获全国研究生数学建模竞赛一等奖、二等奖多项。
担任Advanced Engineering Informatics (SCI)、Advances in Mechanical Engineering (SCI)、Advances in Computational Mathematics (SCI)、Applied Mathematics and Computation (SCI)、Applied Mathematics Letters (SCI)、Applied Mathematical Modelling (SCI)、Applied Numerical Mathematics (SCI)、Computational and Applied Mathematics (SCI)、Computers & Mathematics with Applications (SCI)、Engineering Applications of Artificial Intelligence (SCI)、Information Fusion (SCI)、Information Sciences (SCI)、International Journal of Computational Methods (SCI)、International Journal of Computer Mathematics (SCI)、International Journal of Modeling, Simulation, and Scientific Computing (EI)、Journal of Applied Mathematics and Computing (SCI)、Journal of Computational and Applied Mathematics (SCI)、Journal of Computational Mathematics (SCI)、Journal of Numerical Mathematics (SCI)、Neural Networks (SCI)、Neurocomputing (SCI)、Numerical Algorithms (SCI)、Numerical Linear Algebra with Applications (SCI)、Numerical Mathematics Theory, Methods and Applications (SCI)、Pattern Recognition (SCI)、SIAM Journal on Imaging Sciences (SCI)、SIAM Journal on Numerical Analysis (SCI)、Transportation Research Part E(SCI)、系统工程理论与实践、控制与决策、计算数学、数值计算与计算机应用、高等学校计算数学学报、数学杂志、力学季刊等三十多个国内外著名期刊的审稿人。
研究领域：深度学习中的科学计算问题；交通流预测与仿真；数值代数；偏微分方程数值解；灰色系统理论与算法；目标检测。
主要成果：
1、科研项目：
[1] 国家自然科学基金委员会，面上项目(12471354)，超大规模集成电路布局设计中鞍点型线性互补问题的快速算法与收敛性理论，2025/01-2028/12，主持，在研.
[2] 国家自然科学基金委员会，面上项目(11771225)，压电结构无网格离散中结构化鞍点问题的高效预处理方法与收敛性理论，2018/01-2021/12，主持，已结题.
[3] 国家自然科学基金委员会，青年基金(11301290)，弹性力学中鞍点问题的高效预处理方法与理论，2014/01-2016/12，主持，已结题.
[4] 国家自然科学基金委员会，面上项目(71771127)，工厂侵入市场的外包供应链运行决策研究，2018/01-2021/12，主研(排名第二)，已结题.
[5] 国家自然科学基金委员会，面上项目(11572210)，压电智能层合板壳结构的3-D无网格方法研究”, 2016/01-2019/12，主研(排名第二)，已结题.
2、科研论文：
[1] Yin-Xin Bao, Qin-Qin Shen, Yang Cao and Quan Shi, Sparse mobile crowdsensing for traffic flow prediction with neighborhood perception enhanced multi-factor causal gated network, IEEE Internet of Things Journal, Accepted (SCI, EI)
[2] 唐晟玮，沈琴琴，曹阳，LA-DETR: 面向无人机航拍图像的轻量化小目标检测算法，计算机工程与应用，已录用（EI，中文核心）
[3] 曹阳，高涵，沈琴琴，包银鑫，施佺，面向复杂海况和轻量化特性的SAP-YOLOv8船舶检测算法，中国舰船研究，已录用.（中文核心）
[4] 刘晓菲，沈琴琴，曹阳，孙敏，含虚拟变量的改进型灰色多变量幂模型新能源汽车销量预测, 数学的实践与认识, 已录用. (中文核心，卓越期刊)
[5] 曹阳，王鲁欣，杨爱利，周晨璨，集成电路布局设计合法化问题中鞍点矩阵的特征值估计，计算数学，2026，48(2): 281-294. (中文核心)
[6] 杨林云，曹阳，沈琴琴，多变量阻尼累加非线性时滞离散灰色模型及其应用，控制与决策，2026, 41(5): 1321-1330. (EI，中文核心，卓越期刊)
[7] 高涵，曹阳，沈琴琴，包银鑫，施佺，基于多尺度特征的RAMW-YOLOv8船舶目标检测算法，电子测量技术，2026, 49(8): 215-223. (中文核心)
[8] Yang Cao, Min Sun, Qin-Qin Shen and Quan Shi, Lithium-ion battery remaining useful life prediction based on a hybrid method of improved GM(1,N) model and Gaussian process regression, The Journal of Grey System, 2026, 38(1): 28-40. (SCI)
[9] Yang Cao, Wei Liu and Qin-Qin Shen, Two-step modulus-based matrix splitting iteration method for horizontal implicit complementarity problems, Computational and Applied Mathematics, 2026, 45(3): 116. (SCI, EI)
[10] Min Sun, Yang Cao, Qin-Qin Shen, Dynamic information priority fractional discrete multivariate grey polynomial model for lithium-ion battery health monitoring, Applied Mathematical Modelling, 2026, 154: 116707. (SCI, EI)
[11] Chen-Can Zhou, Yang Cao, Fan Yang, Xiao-Qing Wen, Quan Shi, Rong Rong and Ai-Li Yang, An accelerated Newton-based matrix splitting iteration method for mixed-cell-height circuit legalization, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2026, 45(3): 1535-1548. (SCI)
[12] Qin-Qin Shen, Lin-Yun Yang and Yang Cao, An improved conformable fractional grey multivariate model and its application, The Journal of Grey System, 2025, 37(4): 79-90. (SCI)
[13] Yang Cao, Min Sun, Qin-Qin Shen and Xiao-Fei Liu, A variable-order nonlinear discrete grey multivariate model with new information priority accumulation and its applications, The Journal of Grey System, 2025, 37(3): 37-49. (SCI)
[14] 沈琴琴, 杨林云, 曹阳，可变一致分数阶非线性离散灰色多变量模型及应用[J]，控制与决策，2025, 40(9): 2797-2806. (卓越期刊，EI, 中文核心)
[15] Lu-Xin Wang, Yang Cao, Qin-Qin Shen and Chen-Can Zhou, Two-step nonlinear modulus-based matrix splitting iteration method for implicit complementarity problems, Numerical Algorithms, 2025, 100(3): 1289-1314. (SCI)
[16] 吴伶，曹阳，沈琴琴，施佺，预训练增强的时空网络交通流预测，计算机工程与设计，2025, 46(8): 2380-2387. (中文核心)
[17] 翟志鹏，曹阳，沈琴琴，施佺，基于多时空图融合与动态注意力机制的交通流预测，计算机工程，2025, 59(9): 139-148. (中文核心)
[18] Lu-Xin Wang, Qin-Qin Shen, Yang Cao, Modulus-based matrix splitting iteration method for horizontal linear complementarity problems, Communications on Applied Mathematics and Computation, 2025, 7(4): 1308-1332. (SCI, EI)
[19] Lu-Xin Wang, Yang Cao, Qin-Qin Shen, Two variants of robust two-step modulus-based matrix splitting iteration methods for mixed-cell-height circuit legalization problem, Communications on Applied Mathematics and Computation, 2025, 7(5): 1769-1790. (SCI, EI)
[20] 沈琴琴，党耀国，曹阳，朱镕琦，基于新息优先分数阶累加的改进型灰色Verhulst模型，系统工程理论与实践，2025, 45(2): 539-553. (CSSCI，卓越期刊，EI, 中文核心)
[21] Yin-Xin Bao, Qin-Qin Shen, Yang Cao and Quan Shi, DA-RMN: denoising attention enhanced recurrent multigraph convolutional network for traffic flow prediction, IEEE Internet of Things Journal, 2025, 12(5): 4820-4833. (SCI, EI)
[22] Yin-Xin Bao, Qin-Qin Shen, Yang Cao and Quan Shi, Spatial-temporal clustering enhanced multi-graph convolutional network for traffic flow prediction, Applied Intelligence, 2025, 55: 445. (SCI, EI)
[23] Lu-Xin Wang, Yang Cao and Qin-Qin Shen, Improved modulus-based matrix splitting iteration methods for a class of horizontal implicit complementarity problems, Journal of Computational and Applied Mathematics, 2025, 454: 116183. (SCI, EI)
[24] Chen-Can Zhou, Yang Cao, Lu-Xin Wang, Quan Shi, A robust Newton iteration method for mixed-cell-height circuit legalization under technology and region constraints, ACM Transactions on Design Automation of Electronic Systems, 2024, 29(6): Article 96. (SCI, EI)
[25] Qin-Qin Shen, Yang Cao, Shuang Liang and Quan Shi, Remaining Useful Life Prediction of Lithium Battery Based on LSTM and Improved GM (1, N) Model, The Journal of Grey System, 2024, 36(6): 79-93. (SCI)
[26] 沈琴琴，曹阳，王鲁欣，高赛昆，新息优先一致分数阶累加离散GM(1,1)模型及其应用，控制与决策，2024, 39(12): 3964-3972. （卓越期刊，EI, 中文核心)
[27] 肖培成，曹阳，沈琴琴，施佺，基于ARMA过滤器的时空图卷积网络短时交通流预测, 计算机工程与应用，2024, 60(21): 308-314. (EI, 中文核心)
[28] Yin-Xin Bao, Qin-Qin Shen, Yang Cao, Wei-Ping Ding and Quan Shi, Residual attention enhanced time-varying multi-factor graph convolutional network for traffic flow prediction, Engineering Applications of Artificial Intelligence, 2024, 133: 108135. (SCI, EI)
[29] Yin-Xin Bao, Qin-Qin Shen, Yang Cao and Quan Shi, PLU-MCN: perturbation learning enhanced U-shaped multi-graph convolutional network for traffic flow prediction, Information Fusion, 2024, 104: 102213. (SCI, EI)
[30] Lu-Xin Wang, Yang Cao, Qin-Qin Shen and Chen-Can Zhou, Modified two-step modulus-based matrix splitting iteration methods for implicit complementarity problems, Computational and Applied Mathematics, 2024, 43: 337. (SCI, EI)
[31] 曹阳，杨庚辰，沈琴琴，周晨璨，水平线性互补问题投影迭代法和模系矩阵分裂迭代法的等价性，计算数学，2024, 46(1): 17-37. (中文核心)
[32] Chen-Can Zhou, Yang Cao, Qin-Qin Shen and Quan Shi, A modified Newton-based matrix splitting iteration method for generalized absolute value equations, Journal of Computational and Applied Mathematics, 2024, 442: 115747. (SCI, EI)
[33] 曹阳，朱镕琦，沈琴琴，施佺，基于时域图卷积神经网络的交通流预测模型，计算机工程与设计，2023, 44(12): 3700-3706. (中文核心)
[34] Yin-Xin Bao, Jia-Li Liu, Qin-Qin Shen, Yang Cao, Wei-Ping Ding and Quan Shi, PKET-GCN: Prior knowledge enhanced time-varying graph convolution network for traffic flow prediction, Information Sciences, 2023, 634: 359-381. (SCI , EI)
[35] Yin-Xin Bao, Jia-Shuang Huang, Qin-Qin Shen, Yang Cao, Wei-Ping Ding, Zhen-Quan Shi and Quan Shi, Spatial-temporal complex graph convolution network for traffic flow prediction, Engineering Applications of Artificial Intelligence, 2023, 121: 106044. (SCI , EI)
[36] Chen-Can Zhou, Yang Cao, Quan Shi and Jie Qiu, A robust two-step modulus-based matrix splitting iteration method for mixed-size cell circuit legalization problem, Journal of Circuits, Systems and Computers, 2023, 32(8): 2350129. (SCI, EI)
[37] Yang Cao, Geng-Chen Yang and Qin-Qin Shen, Projected successive overrelaxation iteration method for a class of vertical linear complementarity problems, Computational and Applied Mathematics, 2023, 42: 191. (SCI, EI)
[38] 曹阳, 梁爽, 沈琴琴, 施佺, 阻尼累加离散GM(1,1)模型及其应用, 控制与决策, 2023, 38(6):1687-1694. (EI, 中文核心, 梯队期刊)
[39] Chen-Can Zhou, Jie Qiu, Yang Cao, Geng-Chen Yang, Qin-Qin Shen and Quan Shi, An accelerated modulus-based matrix splitting iteration method for mixed-size cell circuits legalization, Integration the VLSI Journal, 2023, 88(1): 20-31. (SCI, EI)
[40] 曹阳，茅一波，施佺，基于编码器-解码器深度学习模型的日交通流预测，计算机工程与应用，2022, 58(22): 284-290. (中文核心)
[41] Yang Cao, Qin-Qin Shen and Ying-Ting Chen, Additive inexact block triangular preconditioners for saddle point problems from piezoelectric equations with meshfree discretization, East Asian Journal on Applied Mathematics, 2022, 12(2):381-405. (SCI)
[42] Yang Cao and Maya Neytcheva, Cell-by-cell approximate Schur complement technique in preconditioning of meshfree discretized piezoelectric equations, Numerical Linear Algebra with Applications, 2021，28(4):e2362. (SCI)
[43] Qin-Qin Shen, Yang Cao, Lin-Quan Yao and Zhong-Kui Zhu, An optimized discrete grey multi-variable convolution model and its applications, Computational and Applied Mathematics, 2021, 40(2)：Article 58. (SCI, EI)
[44] 曹阳，陈莹婷，姚林泉，无单元Galerkin方法施加本质边界条件研究进展，力学季刊，2020，41(4)：591-612. (中文核心)
[45] Yang Cao, Zhen-Quan Shi and Quan Shi, Regularized DPSS preconditioners for generalized saddle point linear systems, Computers & Mathematics with Applications, 2020, 80: 956-972. (SCI, EI)
[46] Yang Cao, A block positive-semidefinite splitting preconditioner for generalized saddle point linear systems, Journal of Computational and Applied Mathematics, 2020, 374: 112787. (SCI, EI)
[47] 曹阳，陈莹婷，正则化HSS预处理鞍点矩阵的特征值估计，计算数学，2020，42(1)：49-60.（中文核心）
[48] Yang Cao, Zhi-Ru Ren, A local positive-(semi)definite shift-splitting preconditioner for non-Hermitian saddle point problems with applications to time-harmonic eddy current models, East Asian Journal on Applied Mathematics, 2020, 10(1): 135-157. (SCI)
[49] Yang Cao, Zhi-Ru Ren and Lin-Quan Yao, Improved relaxed positive-definite and skew-Hermitian splitting preconditioners for saddle point problems, Journal of Computational Mathematics, 2019, 37(1): 95-111. (SCI)
[50] Yang Cao, A general class of shift splitting preconditioners for non-Hermitian saddle point problems with applications to time harmonic eddy current models, Computers & Mathematics with Applications, 2019, 77: 1124-1143. (SCI, EI)
[51] Yang Cao, Shift-splitting preconditioners for a class of block three-by-three saddle point problems, Applied Mathematics Letters, 2019, 96: 40-46. (SCI, EI)
[52] Yang Cao, Sen Li, Block triangular preconditioners based on symmetric-triangular decomposition for generalized saddle point problems, Applied Mathematics and Computation, 2019, 358: 262-277. (SCI, EI)
[53] Yang Cao, An Wang, Two-step modulus matrix splitting iteration methods for implicit complementarity problems, Numerical Algorithms, 2019, 82(4): 1377-1399. (SCI)
3、专利：
[1] 朱森来，郭柯，施佺，曹阳，沈琴琴，确定车道的交通信号灯冗余时长的方法及系统，国家发明专利，授权时间：2019.12.17，中国，专利号：ZL201710414447.7.
[2] 曹阳，沈琴琴，一种基于Fourier级数改进残差的短时交通流预测方法及系统，国家发明专利，授权时间：2020.05.29，中国，专利号：ZL201810297913.2.
[3] 曹阳，沈琴琴，王玥，黄悦，刘恒孜，一种基于Markov的灰色Verhulst短时交通流预测方法及系统，国家发明专利，授权时间：2021.06.18，中国，专利号：ZL201811532341.8.
[4] 曹阳，张宇，施佺，荆彬彬，沈琴琴，张添豪，朱森来，周晨璨，一种基于混合处理的季节性交通流灰色预测方法，国家发明专利，授权时间：2023.09.22，中国，专利号：201911079213.7.
[5] 曹阳，茅一波，施佺，沈琴琴，基于Encoder-Decoder的长时交通流预测方法，国家发明专利，授权时间：2024.08.06，中国，专利号：202110480861.4.
[6] 周晨璨，施佺，曹阳，邱洁，一种应用两步模迭代法的混合尺寸单元电路设计方法，国家发明专利，授权时间：2025.05.06，中国，专利号：202210327630.4.