Kunsong Zhao

Department of Computing
The Hong Kong Polytechnic University

Chow Yei Ching Building, PolyU, Hung Hom, Kowloon, Hong Kong SAR

Email: kunsong.zhao[at]connect[dot]polyu[dot]hk

Google Scholar DBLP CV

Kunsong is currently a PhD candidate in Computer Science at Department of Computing, The Hong Kong Polytechnic University, under the supervision of Prof. Daniel Xiapu Luo and co-supervision of Prof. Lei Xue. He received his Master and Bachelor degrees in Software Engineering from Wuhan University in 2022 and Hubei University in 2019, respectively.

His research interests lie in designing security systems and improving software quality with the help of program analysis, data mining, machine learning and deep learning techniques. Currently, he mainly focuses on program analysis, blockchain and smart contract security.

Research Interests

Blockchain and Smart Contract Security; Binary Analysis; Software Engineering

Publications

# indicates that the authors contributed equally to this work.

Conference

  • Yu Nong, Richard Fang, Guangbei Yi, Kunsong Zhao, Xiapu Luo, Feng Chen, and Haipeng Cai. "VGX: Large-Scale Sample Generation for Boosting Learning-Based Software Vulnerability Analyses". Proceedings of the 46th International Conference on Software Engineering (ICSE), 2024. [PDF]
  • Kunsong Zhao, Zihao Li, Jianfeng Li, He Ye, Xiapu Luo, and Ting Chen. "DeepInfer: Deep Type Inference from Smart Contract Bytecode". Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE), 2023. [PDF]
  • Kunsong Zhao, Jin Liu, Zhou Xu, Li Li, Meng Yan, Jiaojiao Yu, and Yuxuan Zhou. "Predicting Crash Fault Residence via Simplified Deep Forest Based on A Reduced Feature Set". Proceedings of the 29th IEEE/ACM International Conference on Program Comprehension (ICPC), 2021. [PDF]
  • Kunsong Zhao, Zhou Xu, Meng Yan, Yutian Tang, Ming Fan, and Gemma Catolino. "Just-in-Time Defect Prediction for Android Apps via Imbalanced Deep Learning Model". Proceedings of the 36th ACM/SIGAPP Symposium On Applied Computing (SAC), 2021. [PDF]
  • Zhiwen Xie, Runjie Zhu, Kunsong Zhao, Jin Liu, Guangyou Zhou, and Jimmy Xiangji Huang. "A Contextual Alignment Enhanced Cross Graph Attention Network for Cross-lingual Entity Alignment". Proceedings of the 28th International Conference on Computational Linguistics (COLING), 2020. [PDF]

Journal

  • Geng Zhang, Jin Liu, Guangyou Zhou, Kunsong Zhao, Zhiwen Xie, and Bo Huang. "Question-directed Reasoning with Relation-aware Graph Attention Network for Complex Question Answering over Knowledge Graph". IEEE/ACM Transactions on Audio, Speech, and Language Processing (TASLP), 2024.
  • Kunsong Zhao, Zhou Xu, Meng Yan, Tao Zhang, Lei Xue, Ming Fan, and Jacky Keung. "The Impact of Class Imbalance Techniques on Crashing Fault Residence Prediction Models". Empirical Software Engineering (EMSE), 2023. [PDF]
  • Jiaojiao Yu, Xu Zhou, Xiao Liu, Jin Liu, Zhiwen Xie, and Kunsong Zhao. "Detecting Multi-Type Self-Admitted Technical Debt with Generative Adversarial Network-based Neural Networks". Information and Software Technology (IST), 2023. [PDF]
  • Kunsong Zhao, Jin Liu, Zhou Xu, Xiao Liu, Lei Xue, Zhiwen Xie, Yuxuan Zhou, and Xin Wang. "Graph4Web: A Relation-Aware Graph Attention Network for Web Service Classification". Journal of Systems and Software (JSS), 2022. (Invited to SANER'2023 as part of the Journal First Track) [PDF]
  • Jiaojiao Yu, Kunsong Zhao, Jin Liu, Xiao Liu, Zhou Xu, and Xin Wang. "Exploiting Gated Graph Neural Network for Detecting and Explaining Self-Admitted Technical Debts". Journal of Systems and Software (JSS), 2022. [PDF]
  • Tian Cheng, Kunsong Zhao, Song Sun, Muhammad Mateen, and Junhao Wen. "Effort-Aware Cross-project Just-in-Time Defect Prediction Framework for Mobile Apps". Frontiers of Computer Science (FCS), 2022. [PDF]
  • Zhiwen Xie, Runjie Zhu, Kunsong Zhao, Jin Liu, Guangyou Zhou, and Jimmy Xiangji Huang. "Dual Gated Graph Attention Networks with Dynamic Iterative Training for Cross-Lingual Entity Alignment". ACM Transactions on Information Systems (TOIS), 2021. [PDF]
  • Kunsong Zhao, Zhou Xu, Meng Yan, Lei Xue, Wei Li, and Gemma Catolino. "A Compositional Model for Effort-Aware Just-In-Time Defect Prediction on Android Apps". IET Software, 2021. [PDF]
  • Kunsong Zhao, Zhou Xu, Meng Yan, Tao Zhang, Dan Yang, and Wei Li. "A Comprehensive Investigation of the Impact of Feature Selection Techniques on Crashing Fault Residence Prediction Models". Information and Software Technology (IST), 2021. [PDF]
  • Zhou Xu, Kunsong Zhao, Tao Zhang, Chunlei Fu, Meng Yan, Zhiwen Xie, Xiaohong Zhang, and Gemma Catolino. "Effort-Aware Just-in-Time Bug Prediction for Mobile Apps via Cross-triplet Deep Feature Embedding". IEEE Transactions on Reliability (TRel), 2021. [PDF]
  • Kunsong Zhao, Zhou Xu, Tao Zhang, Yutian Tang, and Meng Yan. "Simplified Deep Forest Model based Just-In-Time Defect Prediction for Android Mobile Apps". IEEE Transactions on Reliability (TRel), 2021. [PDF]
  • Zhou Xu#, Kunsong Zhao#, Meng Yan, Peipei Yuan, Ling Xu, Yan Lei, and Xiaohong Zhang. "Imbalanced Metric Learning for Crashing Fault Residence Prediction". Journal of Systems and Software (JSS), 2020. (Invited to ICPC'2021 as part of the Journal First Track) [PDF]

Awards & Grants (Selected)

Teaching

Services