姓名：屈鸿 专业技术职务：教授
联系方式：
邮箱：hongqu@uestc.edu.cn
系别：计算机软件与理论系

联系方式 邮箱 hongqu@uestc.edu.cn
专业技术职务_详情页 教授

个人背景 1996年-2000年:电子科技大学,本科;
2000年-2003年:电子科技大学,硕士;
2003年-2006年:电子科技大学,博士;
2007年-2008年:加拿大Guelph大学,博士后;
2007年-2010年:电子科技大学,讲师;
2010年-2015年:电子科技大学,副教授;
2014年-2015年:柏林洪堡大学,访问****;
2010年-至今:电子科技大学,博导;
2015年-至今:电子科技大学,教授,博导;
研究方向 人工智能、类脑计算、机器学习、神经网络
讲授课程
本 科：《编译原理》
研究生：《机器智能》
研究成果 研究项目：
1.神经元和模块功能特异化研究，科技创新2030-“新一代人工智能”重大项目课题，2019.12-2023.12，主持；
2.具有模块功能特异化性质的新型Spiking神经网络模型研究，国家自然科学基金面上项目，2020.01-2023.12，主持；
3.地质云数据即服务关键技术研究,中国地质调查局发展研究中心, 2021.08-2022.08，主持；
4.渝高智慧成本管理系统,重庆渝高科技产业（集团）股份有限公司, 2020.08-2012.04，主持；
5.具有时序处理能力的Spiking-Deep Learning（脉冲深度学习）方法研究，国家自然科学基金面上项目，2016.01-2019.12，主持；
6. Spiking神经网络机器学习算法研究，国家自然科学基金面上项目，2013.01-2016.12，主持；
7.脉冲耦合神经网络研究及其应用，国家自然科学基金青年项目，2010.01-2012.12，主持；
8.多智能体协调控制技术研究，航空科学基金，2013.10-2016.10，主持；
9.冷热电三联供优化运营管理技术研究与开发，四川省科技支撑计划项目，2013.01-2014.12，主持；
10.交通流视频检测及自适应信号灯控制系统，成都市科技划项目，2012.01-2012.12，主持；
11.非确定环境下多机器人协助系统关键技术研究，教育部博士点新教师基金，2009.01-2012.12，主持；,
12.目标时序数据信息挖掘技术，中电集团29所，2014.12-2015.10,主持;
13.高性能推理引擎技术，中电集团29所，2013.12-2014.03，主持;
14.智能算法应用平台，中电集团29所，2015.07-2016.10，主持;
15.桌面级及静态代码检查技术研究，华为科技有限公司，2015.01-2015.09，主持;
16.C语言MAPO技术（挖掘、关联、推荐），华为科技有限公司，2014.12-2015.08，主持;
17.源码分析加速引擎能力构建，华为科技有限公司，2013.12-2014.05，主持;
期刊论文列表：
(1) L. Huang, W. Chen, Y. Liu, S. Hou andH. Qu*, Summarization With Self-Aware Context Selecting Mechanism,IEEE Transactions on Cybernetics, 2021.
(2) Liwei Huang, Mingsheng Fu, Fan Li,Hong Qu, Yangjun Liu, and Wenyu Chen. A deep reinforcement learning based long-term recommender system.Knowledge-Based Systems, vol. 213, pp. 106706, 2021.
(3) Yun Zhang,Hong Qu*, Xiaoling Luo, Yi Chen, Yuchen Wang, Malu Zhang and Zefang Li. A new recursive least squares-based learning algorithm for spiking neurons,Neural Networks, Accept, 2021.
(4) Liu, Yongsheng,Hong Qu*, Wenyu Chen, S. M. Hasan Mahmud, Kebin Miao. Weakly Supervised Image Classification and Pointwise Localization with Graph Convolutional Networks,Pattern Recognition, vol.15, pp. 107596, 2020.
(5) Malu Zhang, Xiaoling Luo, Yi Chen, Jibin Wu, Ammar Belatreche, Zihan Pan,Hong Qu, Haizhou Li. An Efficient Threshold-Driven Aggregate-Label Learning Algorithm for Multimodal Information Processing[J].IEEE Journal of Selected Topics in Signal Processing, 2020, PP(99):1-1.
(6) Xiaoling Luo,Hong Qu*, Yun Zhang, Chen, Yi. First Error-Based Supervised Learning Algorithm for Spiking Neural Networks[J].Frontiers in Neuroence, 2019, 13:559.
(7) Liu, Yongsheng,Hong Qu*, Wenyu Chen, S. M. Hasan Mahmud. An Efficient Deep Learning Model to Infer User Demographic Information From Ratings,IEEE Access, vol. 7, pp. 53125-53135, 2019.
(8) Mingsheng Fu,Hong Qu*, Zhang Yi, Li Lu and Yongsheng Liu. A Novel Deep Learning-Based Collaborative Filtering Model for Recommendation System,IEEE Transactions on Cybernetics, Vol. 49, no. 3, pp, 1084-1096, 2019.
(9) Huang, Liwei, Hong Qu*, and Lin Zuo. Multi-Type UAVs Cooperative Task Allocation Under Resource Constraints. IEEE Access. Vol. 6, pp. 17841-17850, 2018.
(10) Fu, Mingsheng, Hong Qu*, Attention based collaborative filtering. Neurocomputing. Vol.311,pp. 88-98,2018.
(11) Fu, Mingsheng, Hong Qu*, Li Huang, and Li Lu. Bag of meta-words: A novel method to represent document for the sentiment classification.Expert Systems with Applications, vol.113, pp. 33-43,2018.
(12) Malu Zhang,Hong Qu*, Ammar Belatreche, Chenyi, Zhang Yi. A Highly Effective and Robust Membrane Potential-Driven Supervised Learning Method for Spiking Neurons.IEEE Transactions on Neural Networks and Learning Systems,vol. 30, no. 1, pp. 123-137, 2019.
(13) Malu Zhang,Hong Qu*,Ammar Belatreche,Xiurui Xie. EMPD: An Efficient Membrane Potential Driven Supervised Learning Algorithm for Spiking Neurons，IEEE Transactions on Cognitive and Developmental Systems，DOI：10.1109/TCDS.2017.**，2018.
(14) Minyu Feng，Hong Qu*，Zhang YiandJürgen Kurths. Subnormal Distribution Derived From Evolving Networks With Variable Elements，IEEE Transactions on Cybernetics, Vol. 48, no. 9, pp. 2556 - 2568, 2018.
(15) Xiurui Xie,Hong Qu*, Zhang Yi, Jürgen Kurths. Efficient Training of Supervised Spiking Neural Network via Accurate Synaptic-Efficiency Adjustment Method.IEEE Transactions on Neural Networks and Learning Systems, Vol. 28, No. 6, pp. 1411-1424, 2017.
(16) Xiurui Xie,Hong Qu*，Guisong Liu,Malu Zhang. Efficient training of supervised spiking neural networks via the normalized perceptron based learning rule,Neurocomputing, Vol. 241, pp.152-163, 2017.
(17) Malu Zhang,Hong Qu*,Xiurui Xieand Jürgen Kurths. Supervised Learning in Spiking Neural Networks with Noise-Threshold.Neurocomputing, Vol. 219, pp.333-349, 2017.
(18) Minyu Feng, Hong Qu*, Zhang Yi, Xiurui Xie and Jürgen Kurths. Evolving Scale-Free Networks by Poisson Process: Modeling and Degree Distribution.IEEE Transactions on Cybernetics, Vol. 46, No. 05, pp. 114-1155, 2016.
(19) Minyu Feng，Hong Qu*and Zhang Yi. Highest Degree Likelihood Search Algorithm Using a State Transition Matrix for Complex Networks. IEEE Transactions on Circuits and Systems, Part I: Regular Papers，Vol.61, No.10, pp. 2941- 2950, 2014.
(20) Hong Qu, Zhang Yi and S.X. Yang. Efficient Shortest Path Tree Computation in Network Routing Based on Pulse Coupled Neural Networks.IEEE Transactions on Cybernetics, Vol. 43, No. 03, pp. 995 - 1010, 2013.
(21) Hong Qu, S.X. Yang, Allan R. Willms and Zhang Yi. Real-Time Robot Path Planning Based on a Modified Pulse-Coupled Neural Network Model.IEEE Transcations on Neural Networks: Regular Papers, Vol. 20, No. 11, pp. 1724 - 1739, 2009.
(22) Liwei Huang,Hong Qu*, Peng Ji, Xintong Liu and Zhen Fan. A novel coordinated path planning method using k-degree smoothing for multi-UAVs.Applied Soft Computing，Vol. 48, pp. 182–192, 2016.
(23) Hong Qu, Zhang Yi and HuaJin Tang. Improving Local Minima of Columnar Competitive Model for TSPs.IEEE Transactions on Circuits and Systems, Part I: Regular Papers, Vol. 53, No.6, pp. 1353 - 1362, 2006.
(24) Xiurui Xie，Hong Qu*, Liu G, Zhang M, and Kurths. An Efficient Supervised Training Algorithm for Multilayer Spiking Neural Networks.PLoS ONE, Vol. 11, No. 4: e**, 2016.
(25) Hong Qu, Xiurui Xie, Yongshuai Liu，Malu Zhang and Li Lu. Improved perception-based spiking neuron learning rule for real-time user authentication.Neurocomputing, Vol. 151, pp. 310 - 318, 2015.
(26) Guisong Liu，Zhao Qiu，Hong Qu* and Luping Ji. Computing k shortest paths using modified pulse-coupled neural network.Neurocomputing, Vol. 149, pp. 1162 - 1176, 2015.
(27) Guisong Liu, Zhao Qiu,Hong Qu, Luping Ji, Alexander Takacs. Computing k shortest paths from a source node to each other node.Soft Computing，Vol. 19, No.8, pp 2391–2402. 2015.
(28) Luping Ji，Xiaorong Pu, Hong Qu and Guisong Liu. One-dimensional pairwise CNN for the global alignment of two DNA sequences. Neurocomputing，Vol. 149, pp. 505 - 514, 2015.
(29) Hong Qu, Xing Ke. An improved genetic algorithm with co-evolutionary strategy for global path planning of multiple mobile robots.Neurocomputing, Vol. 120, No, 23, pp. 509 - 517, 2013.
(30) Daibo Liu，Mengshu Hou，Hong Qu，A simple model for the multiple traveling salesmen problem with single depot and multiple link,Compel-The International Journal for Computation and Mathematics in Electrical and Electronic Engineering，Vol. 32, No. 2, pp. 556-574, 2013.
(31) Hong Qu,S.X. Yang, Zhang Yi. A Novel Neural Network Method for Shortest Path Tree Computation.Applied Soft Computing,Vol. 12, No. 10, pp. 3246 - 3259, 2012.
(32) Wei Suo andHong Qu*. Automatic Image Segmentation Based on PCNN with Adaptive Threshold Time Constant.Neurocomputing, Vol. 74, No. 9, pp. 1485 - 1491, 2011.
(33) Hong Qu, Zhang Yi and Xiaobin Wang. A Winner-Take-All Networks of N Linear Threshold Neurons without Self-Excitatory Connections.Neural Processing Letters，Vol. 29, No.3, pp. 143 - 154 ,2009.
(34) Xiaobin Wang,Hong Qu, and Zhang Yi. A modified pulse coupled neural network for Shortest Path Problem.Neurocomputing,Vol. 72, No. 13 - 15. pp. 3028 - 3033, 2009.
(35) Hong Qu, Zhang Yi and Xiaobin Wang. Switching Analysis of Neural Networks with Nonsaturating Linear Threshold Transfer Functions.Neurocomputing,Vol. 72, No.1 - 3, pp. 413 - 419, 2008.
(36) Hong Qu, Zhang Yi and HuaJin Tang. A Columnar Competitive Model for Solving Multi-Traveling Salesman Problem.Chaos, Solitons and Fractals, Vol. 31, pp. 1009 - 1029, 2007.
(37) Hong Qu, and Zhang Yi. A new algorithm for finding the shortest paths using PCNNs.Chaos, Solitons and Fractals，Vol. 33, No. 4, pp. 1220 - 1229, 2007.
(38) Hong Quand Zhang Yi. Convergence and Periodicity of Solutions for a Class of Discrete-Time Recurrent Neural Network with Two Neurons.Lecture Notes in Computer Science, Vol. 3971, pp.291 - 296, 2006.
(39) Hong Qu, Zhang Yi and XiaoLin Xiang. Theoretical Analysis and Parameter Setting of Hopfield Neural Networks.Lecture Notes in Computer Science, Vol. 3496, pp. 739 - 745, 2005.
会议论文列表：
(1) Yi Chen,Hong Qu*, Malu Zhang and Yuchen Wang. Deep Spiking Neural Network with Neural Oscillation and Spike-Phase information,AAAI 2021: Thirty-Fifth AAAI Conference on Artificial Intelligence. 02.02-02.09, virtual conference, 2021.
(2) Jiaxu Zhao, Li Huang, Ruixuan Sun, Liao Bing andHong Qu*. Twin-GAN for Neural Machine Translation,inICAART 2021: International Conference on Agents and Artificial Intelligence. 04.02-06.02 ,Online, 2021.
(3) Niyongabo, Rubungo Andre,Qu Hong*, Julia Kreutzer, and Li Huang. KINNEWS and KIRNEWS: Benchmarking Cross-Lingual Text Classification for Kinyarwanda and Kirundi. InCOLING 2020:Proceedings of the 28th International Conference on Computational Linguistics, pp. 5507-5521. 12.08-12.13, Barcelona,Spain, 2020.
(4) Li Zhou，TingyuWang，Hong Qu*，Li Huang，Yuguo Liu. A Weighted GCN with Logical Adjacency Matrixfor Relation Extraction,ECAI 2020: European Conference on Artificial Intelligence. 08.29-09.05, Santiago de Compostela,Chile, 2020.
(5) Li. Huang, Wenyu. Chen, andHong Qu*, Accelerating Transformer for Neural Machine Translation, Proceedings of the 13th International Conference on Machine Learning and Computing. 03.26-04.01，Shen Zhen, China，2021.
(6) Huang Liwei,Qu Hong*, Fu Mingsheng, and Deng Wu. Reinforcement Learning for Mobile Robot Obstacle Avoidance Under Dynamic Environments.Pacific Rim International Conference on Artificial Intelligence. Springer, Cham, 08.27-08.31, 2018.CCF B
(7) Mingsheng Fu,Hong Qu*, Fan Li, Yanjun Liu. A New Deep Neural Network Based Learning to Rank Method for Information Retrieval.IEEE International Conference on Informati on and Automation, 08.11-08.13, Wuyi Mountain, China, 2018.
(8) Zhang, Xiaomin, Li Huang, andHong Qu. "AHNN: an attention-based hybrid neural network for sentence modeling."National CCF Conference on Natural Language Processing and Chinese Computing. Springer, Cham, 2017.
(9) Lin Zuo, Sang Chen,Hong Qu*, and Malu Zhang. A Fast Precise-Spike and Weight-Comparison Based Learning Approach for Evolving Spiking Neural Networks. The 25th International Conference on Neural Information Processing (ICONIP 2017), pp. 797-804, Nov. 8-12, 2017, Guangzhou, China.
(10) Lin Zuo, Linyao Ma, Yanqing Xiao Malu Zhang andHong Qu*. A Dynamic Region Generation Algorithm for Image Segmentation Based on Spiking Neural Network.The 25th International Conference on Neural Information Processing (ICONIP 2017), pp. 816-824, Nov. 8-12, 2017, Guangzhou, China.
(11) Yongqing Zhang, Yi Chen, Malu Zhang, Xi Wu, Jiliu Zhou andHong Qu*. ERMPD:An Efficient and Robustness Membrane Potential Driven Supervised Learning in Spiking Neural Networks.2017 IEEE Symposium Series on Computational Intelligence (SSCI 2017), pp. 816-824, Nov. 8-12. 2017, HAWAII, US
(12) Hong Qu*，Zhi Zeng，Chuangle Chen. An optimization method of SNNs for shortest path problem.The 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems (IES 2014)，Singapore，2014.11.10 - 2014.11.12, Oral Report.
(13) Xiurui Xie，Hong Qu*，Guisong Liu. Recognizing Human Actions by Using the Evolving Remote Supervised Method of Spiking Neural Networks.The 21-st International Conference Neural Information Processing (ICONIP 2014), Kuching，2014.11.03 - 2014.11.06, Oral Report.
(14) Malu Zhang,Hong Qu*，A New Supervised Learning Algorithm for Spiking Neurons.The 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems (IES 2014)，Singapore，2014.11.10 - 2014.11.12, Oral Report.
(15) Wang Xiaobin, Li Hao, Wu Lijuan and Hong Qu*. Genetic Algorithm Based Neural Network for License Plate Recognition. The 10th International Symposium on Neural Networks (ISNN 2013), Dalian, China, 2013.07.04 - 2013.07.06，Posted Report.
(16) Minyu Feng，Hong Qu*，Yi Xu，Xing Ke，The high degree seeking algorithms with k steps for complex networks，The 9th International Symposium on Neural Networks (ISNN 2012)，Shenyang, China，2012.7.11-2012.7.14，Posted Report.
(17) Daibo Liu，Mengshu Hou，Hong Qu*,Pu Xiong，A new high-efficiency global optimization algorithm for solving Traveling Salesman Problem，The 2nd World Congress on Computer Science and Information Engineering(CSIE 2011)，Changchun, China，649-656, 2011.6.17-2011.6.19.
(18) Fang Xu, Lei Zhang andHong Qu.Convergence analysis of background neural networks with two sub-networks.IEEE Conference on Cybernetics and Intelligent Systems, pp. 440 - 444, 2008.
(19) Haixian Zhang, Stones Lei Zhang, Jiali Yu, andHong Qu, Continuous attractors of a class of recurrent neural networks without lateral inhibition.IEEE Conference on Cybernetics and Intelligent Systems, pp.7 - 11, 2008.
(20) Manli Li, Jiali Yu, Stones Lei Zhang, andHong Qu. Solving TSP using Lotka-Volterra neural networks without self-excitatory.IEEE Conference on Cybernetics and Intelligent Systems, pp.786 - 790, 2008.
(21) Hong Quand Zhang Yi. Global Attractivity of Discrete-Time Recurrent Neural Networks With Un-saturating Piecewise Linear Activation Functions.2005 International Conference on Neural Networks, pp. 140 - 143, 2005.
研究成果获奖：
2012年获教育部自然科学一等奖；
2007年获四川省科技进步二等奖，
社会兼职及荣誉
………


授权专利
ZL1.1一种基于多层spiking卷积神经网络的图像分类方法
ZL0.5一种基于反馈的混合多智能体协同控制方法
ZL7.4一种基于神经网络语言模型的重复代码检测方法
ZL9.0一种基于神经网络语言模型的代码分类方法
ZL3.X一种基于状态的路径敏感的符号化函数摘要算法
ZL7.5一种基于C/C++代码库的API调用模式挖掘方法
ZL8.0一种基于Spiking的图像角点检测方法
ZL4.2一种基于灰度图像的spiking角点检测方法
ZL5.4一种资源限制条件下多类型无人机协同任务分配方法
ZL9.7一种基于本体的电子商务推荐方法
ZL1.3一种基于Spiking-卷积网络模型的图像边缘检测方法
ZL6.8一种代码静态检测方法
ZL1.4一种基于链接分析的聚焦爬虫方法
ZL4.X一种基于社区发现的社交网络好友推荐方法
ZL7.0一种优化训练样本集的KNN文本分类方法
ZL9.7一种基于Spiking神经网络的图像分割方法
ZL3.1一种基于BP-PSO模糊神经网络的信号灯智能控制方法
ZL5.4一种动态环境下移动机器人路径规划方法
ZL1.5一种基于拟退火算法的三维人脸识别方法