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张永清

2018-03-04

姓名: 张永清 工学博士副教授

Email: zhangyq@cuit.edu.cn

科研和研究生招生方向:

1、人工智能与数据挖掘

2、机器学习与生物信息学

 

个人简介

张永清博士,副教授,研究生导师。由四川大学和美国加州大学圣地亚哥分校(UCSD, University of California, San Diego)博士联合培养,长期从事机器学习、数据挖掘、生物信息学、脑机接口方面的应用研究。目前在国内外具有影响力期刊和国际会议上发表SCI、EI论文30余篇,申请发明专利5项。高质量期刊包括:Nucleic Acids Research, BMC Bioinformatics, Engineering Applications of Artificial Intelligence, International Journal of Machine Learning and Cybernetics、Chemometrics and Intelligent Laboratory、自动化学报等。主持国家自然科学基金1项、中国博士后面上基金1项、四川省教育厅重点项目1项,参研国家自然科学基金2项、军委科技委基金2项;获得2016年ACM成都分会优秀博士论文奖。目前担任CCF生物信息专业委员会委员、CCF YOCSEF成都分论坛副主席、中国自动化学会分数阶系统与控制专业委员会委员,CCF会员、ACM会员、CAA会员,国家基金委项目评审专家,TCBB、NCAA、IEEE J BIOMED HEALTH、IEEE ACCESS、J BIOINF COMPUT BIOL等期刊审稿人。

目前承担科研项目:

  1. 国家自然科学基金青年科学基金项目(61702058),高通量数据和深度学习在基因调控层次网络构建中的应用研究,2018-2020年,主持。

  2. 中国博士后科学基金面上资助(2017M612948),基于膜电压驱动的Spiking神经网络学习算法研究,2017-2018年,主持。

  3. 成都信息工程大学中青年学术带头人科研基金(J201706),基于智能计算的基因网络研究,2017-2020年,主持。

     

    目前授课:

     “计算机组成原理”,本科生.

    “人工智能”,本科生

    “人工智能”,研究生

    近年发表论文: 


  1. Yongqing Zhang, Shaojie Qiao*, Rongzhao Lu, Nan Han, Dingxiang Liu, Jiliu Zhou, “How to balance the bioinformatics data: pseudo-negative sampling”, BMC Bioinformatics. 20, 695(2019). https://doi.org/10.1186/s12859-019-3269-4

  2. Yongqing Zhang, Shaojie Qiao*, Shengjie Ji, Yizhou Li, “DeepSite: Bidirectional LSTM and CNN Models for Predicting DNA-protein Binding”, International Journal of Machine Learning and Cybernetics. 11, 841-851(2020).

  3. Yongqing Zhang, Shaojie Qiao*, Shengjie Ji, Nan Han, Dingxiang Liu, Jiliu Zhou, “Identification of DNA-Protein Binding Sites by Bootstrap Multiple Convolutional Neural Networks”, Engineering Applications of Artificial Intelligence, Volume 79, March 2019, Pages 58-66.

  4. Yongqing Zhang, Shaojie Qiao*, Shengjie Ji, Jiliu Zhou, “ENSEMBLE-CNN: Predicting DNA binding sites in protein sequences by an ensemble deep learning method”, 2018 International Conference on Intelligent Computing, August 15-18, 2018 Wuhan, China. Pp.301-306(2018).Springer.

  5. Yongqing Zhang, Tianyu Geng*, Xi Wu, Jiliiu Zhou, “ICANet: A Simple Cascade Linear Convolution Network for Face Recognition”, EURASIP Journal on Image and Video Processing, (2018) 2018:51.

  6. Yongqing Zhang, Tianyu Geng, Malu Zhang, Xi Wu, Jiliu Zhou, Hong Qu*, “An Efficient and Robustness Supervised Learning Algorithm for Spiking Neural Networks”, Sensing and Imaging, (2018)19:8

  7. Zhang, Yongqing; Cao, Xiaoyi; Zhong, Sheng*, “GeNemo: a search engine for web-based functional genomic data”, Nucleic Acids Research, 20 April, 2016,44,W122-127

  8. Yongqing Zhang*, YifeiPu, Haisen Zhang, Yong Cong, Jiliu Zhou, “An extended fractional Kalman filter for inferring gene regulatory networks using time-series data”, Chemometrics and Intelligent Laboratory, Volume 138, 15 November 2014, Pages 57-63.

  9. Yongqing Zhang*, YifeiPu, Haisen Zhang, Yabo Su, Lifang Zhang, Jiliu Zhou, “Using gene expression programming to infer gene regulatory networks from time-series data”, Computational Biology and Chemistry, Volume 47, 10 December 2013, Pages 198-206.

  10. Yongqing Zhang, Danling Zhang, Gang Mi, DaichuanMa,GongbingLi,YanzhiGuo, Menglong Li*, Min Zhu*, “Using ensemble methods to deal with imbalanced data in predicting protein-protein interactions,” Computational Biology and Chemistry, vol 36, page 36-41, 15 Feb 2012.

Curriculum Vitae

Dr. Yongqing Zhang

Associate Professor

Department of Computer Science

Chengdu University of Information Technology

Contact: zhangyq@cuit.edu.cn

 

Dr. Yongqing Zhang received the Ph.D. degree in computer science and technology from the Sichuan University, Chengdu, China, in 2016. From 2013 to 2016, he was a visiting Ph.D. student at the Department of Bioengineering, University of California, San Diego, USA. Currently, he is an associate professor in School of Computer Science, Chengdu University of Information and Technology. His research interests include machine learning and bioinformatics.

 

Research interests:

1. Artificial Intelligence and data mining

2. Machine learning and bioinformatics

 

Courses:

Principles of Computer Organization for undergraduate

Artificial Intelligence for undergraduate

Artificial Intelligence for graduate

 

Publications:

  1. Yongqing Zhang, Shaojie Qiao*, Rongzhao Lu, Nan Han, Dingxiang Liu, Jiliu Zhou, “How to balance the bioinformatics data: pseudo-negative sampling”, BMC Bioinformatics. 20, 695(2019). https://doi.org/10.1186/s12859-019-3269-4

  2. Yongqing Zhang, Shaojie Qiao*, Shengjie Ji, Yizhou Li, “DeepSite: Bidirectional LSTM and CNN Models for Predicting DNA-protein Binding”, International Journal of Machine Learning and Cybernetics. 11, 841-851(2020).

  3. Yongqing Zhang, Shaojie Qiao*, Shengjie Ji, Nan Han, Dingxiang Liu, Jiliu Zhou, “Identification of DNA-Protein Binding Sites by Bootstrap Multiple Convolutional Neural Networks”, Engineering Applications of Artificial Intelligence, Volume 79, March 2019, Pages 58-66.

  4. Yongqing Zhang, Shaojie Qiao*, Shengjie Ji, Jiliu Zhou, “ENSEMBLE-CNN: Predicting DNA binding sites in protein sequences by an ensemble deep learning method”, 2018 International Conference on Intelligent Computing, August 15-18, 2018 Wuhan, China. Pp.301-306(2018).Springer.

  5. Yongqing Zhang, Tianyu Geng*, Xi Wu, Jiliiu Zhou, “ICANet: A Simple Cascade Linear Convolution Network for Face Recognition”, EURASIP Journal on Image and Video Processing, (2018) 2018:51.

  6. Yongqing Zhang, Tianyu Geng, Malu Zhang, Xi Wu, Jiliu Zhou, Hong Qu*, “An Efficient and Robustness Supervised Learning Algorithm for Spiking Neural Networks”, Sensing and Imaging, (2018)19:8

  7. Zhang, Yongqing; Cao, Xiaoyi; Zhong, Sheng*, “GeNemo: a search engine for web-based functional genomic data”, Nucleic Acids Research, 20 April, 2016,44,W122-127

  8. Yongqing Zhang*, YifeiPu, Haisen Zhang, Yong Cong, Jiliu Zhou, “An extended fractional Kalman filter for inferring gene regulatory networks using time-series data”, Chemometrics and Intelligent Laboratory, Volume 138, 15 November 2014, Pages 57-63.

  9. Yongqing Zhang*, YifeiPu, Haisen Zhang, Yabo Su, Lifang Zhang, Jiliu Zhou, “Using gene expression programming to infer gene regulatory networks from time-series data”, Computational Biology and Chemistry, Volume 47, 10 December 2013, Pages 198-206.

  10. Yongqing Zhang, Danling Zhang, Gang Mi, DaichuanMa,GongbingLi,YanzhiGuo, Menglong Li*, Min Zhu*, “Using ensemble methods to deal with imbalanced data in predicting protein-protein interactions,” Computational Biology and Chemistry, vol 36, page 36-41, 15 Feb 2012.