Bing Zhang is currently a Lecturer and holding a post-doctoral position at the School of Information Science and Engineering, Yanshan University, China. He received his bachelor's degree from the College of Computer and Information Technology, Three Gorges University, China, in 2012, and the Ph.D. degree from the School of Information Science and Engineering, Yanshan University, China, in 2018. He has ever been with the Norwegian University of Science and Technology as a Visiting Scholar. His research interests include data mining, machine learning, and software security.
Received PHD degree (Major: Computer science and technology) in School of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, China, 2012-2017
Received Bachelor degree (Major: Computer science and technology) in College of Computer and Information Technology, China Three Gorges University, China, 2008-2012
2017.12.30~2018.12.30, As a Visiting scholar in Norwegian University of Science and Technology (NTNU), Trondheim, Norway
2017.1.16~2017.2.20, As a visiting PHD student in University of Hull, Hull, UK.
(1) Software Security (Web Vulnerabilities based on Source codes and Binary code analysis)
(2) Software Structure analysis (Complex network, sequence pattern analysis)
(3) Health data analysis by machine learning/data mining
(4) Air Quality Prediction
(1) Java Web Development Technology
(2) Software Testing and Quality Assurance
(1) National Natural Science Foundation of China，61802332，Research on Early Warning for Online Vulnerabilities during developing Web Applications，2019/01-2021/12，Leader.
(2) The Graduate innovative Funding project of Hebei Province，2016SJBS010，Research on the methods and key technologies of influential node mining in software execution process，2016/01-2017/01，Leader.
(3) National Natural Science Foundation of China，61872449，Research on the analysis approach to the mining of key modules structure in software system and its evolution，2018/01-2021/12，Main Participant.
(4) National Natural Science Foundation of China，61872451，analysis approach to the propagation behavior pattern and evolution of Air Quality based on temporal-spatial dynamic complex network，2018/01-2021/12，Main Participant.
(5) National Natural Science Foundation of China，61572420，Research on multi-level entity mining method and key technology for software system based on complex network，2016/01-2019/12，Main Participant.
(6) Project of university talent training program for innovation team of Hebei Province，LJRC002，Cloud computing for big data analysis，2014/01-2016/12，Participant.
(7) National Natural Science Foundation of Hebei Province，F2014203152，Research on sequence analysis method based on directed graph in software vulnerability detection，2014/01-2016/12，Participant.
(8) National Natural Science Foundation of China，61170190，Modeling and analysis of software security characteristics based on Data Mining，2012/01-2015/12，Participant.
张炳，单纯等. Software Crucial Functions Ranking and Detection in Dynamic Execution Sequence Patterns [J]. International Journal of Software Engineering and Knowledge Engineering, 2020, Inpress. (SCI)
张炳，孙盛廷，郝晓冰. Mining Important Functions in Software Network by Node Vulnerability [C]// 2019 2nd International Conference on Computer Information Science and Artificial Intelligence, 2019, Oct 25-27, Xi’an, China, Journal of Physics: Conference Series 1453 (2020) 012015. (EI: 20201108294035)
Bing Zhang, Jiadong Ren, Yongqiang Cheng, Bing Wang, Zhiyao Wei. Health Data Driven on Continuous Blood Pressure Prediction based on Gradient Boosting Decision Tree Algorithm [J]. IEEE Access, 2019, 7(1): 32423-32433. (JCR2 SCI, IF:3.557)
Bing Zhang, Huihui Ren, Guoyan Huang, Yongqiang Cheng, Changzhen Hu. Predicting blood pressure from physiological index data using the SVR algorithm [J]. BMC Bioinformatics, 20(1): 109. (CCF C, SCI，IF:2.213 )
Bing Zhang, Zhiyao Wei, Jiadong Ren, Yongqiang Cheng, Zhangqi Zheng. An Empirical study on Predicting Blood Pressure using Classification and Regression Trees[J], IEEE Access, 2018,6: 21758-21768. (JCR2 SCI, IF:3.557)
Bing Zhang, Guoyan Huang, Zhangqi Zheng, Jiadong Ren, Changzhen Hu. Approach to mine the Modularity of Software Network Based on the Most Vital Nodes[J]. IEEE Access, 2018,6: 32543 - 32553. (JCR2 SCI, IF:3.557)
Bing Zhang, Guoyan Huang, Haitao He, Jiadong Ren, A novel approach to mine influential functions based on software execution sequence, IET Software, 2017, 11(2): 48-54. (CCF B, SCI)
Bing Zhang, Guoyan Huang, Haitao He, Jiadong Ren. Mining dynamic noteworthy functions in software execution sequences, Plos One, 2017, 12(3): e0173244. (SCI: IF: 3.057)
Guoyan Huang, Bing Zhang, Rong Ren, Jiadong Ren. An algorithm to find critical execution paths of software based on complex network [J]. International Journal of Modern Physics C, 2015, 26(9): 1550101. (SCI, IF:1.26)
Guoyan Huang, Peng Zhang, Bing Zhang, Tengteng Yin, Jiadong Ren. The Optimal Community Detection of Software Based On Complex Networks. International Journal of Modern Physics C, 2016, 27(8): 1650085. (SCI, IF:1.26)
Guoyan Huang, Bing Zhang, Rong Ren, Jiadong Ren. A novel approach to efficiently mine structural patterns from software execution sequence [J]. Journal of Computational Information Systems, 2015, 11(3): 1109-1119. (EI)
Haitao He, Rong Ren, Bing Zhang, Jiadong Ren. Analysis on impact of node failure in software execution network [J]. Journal of Computational Information Systems, 2015, 11(6):2217-2225. (EI)
Jiadong Ren, Hongfei Wu, Tengteng Yin, Lan Bai, Bing Zhang. A Novel Approach for Mining Important Nodes in Directed-Weighted Complex Software Network [J]. Journal of Computational Information Systems, 2015, 11(8). (EI)
Yuan Huang, Guoyan Huang, Bing Zhang, Wanchang Jiang. An improved Grey-Markov model for urban air quality forecast [J]. ICIC Express Letters, Part B: Applications, 2016, 7(8): 1739-1745. (EI)
Yuan Huang, Guoyan Huang, Wanchang Jiang, Bing Zhang. An improved grey neural network for urban air quality forecast [J]. ICIC Express Letters, 2016, 10(3): 555-562. (EI)
Dong Ren, Haiyang Yu, Wenwen Fu, Bing Zhang, Qing Ji. Crop diseases and pests monitoring based on remote sensing: A survey[C].World Automation Congress (WAC), 2012. IEEE, 2012: 177-181.