World's Best Scientists 2026 revealed!

Overview

Yanfang Ye is affiliated with the University of Notre Dame in the United States. Their research primarily focuses on the field of Computer Science, with significant contributions in Artificial Intelligence, Information Systems, Signal Processing, Statistical and Nonlinear Physics, and Epidemiology.

The scientist's work covers several advanced topics including:

  • Advanced Graph Neural Networks
  • Topic Modeling
  • Recommender Systems and Techniques
  • Spam and Phishing Detection
  • Cybercrime and Law Enforcement Studies
  • Advanced Malware Detection Techniques
  • Complex Network Analysis Techniques

Yanfang Ye has co-authored frequently with several researchers, including:

  • Chuxu Zhang
  • Mingxuan Ju
  • Zheyuan Zhang
  • Zehong Wang
  • Shifu Hou

The scientist has published extensively in a range of venues. The most frequent venues for their publications include:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence
  • ACM Transactions on Knowledge Discovery from Data
  • Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

Recent representative papers authored or co-authored by Yanfang Ye include:

  • "A Survey on Heterogeneous Graph Embedding: Methods, Techniques, Applications and Sources," 2022, IEEE Transactions on Big Data
  • "Heterogeneous Graph Structure Learning for Graph Neural Networks," 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • "Knowledge-aware Coupled Graph Neural Network for Social Recommendation," 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • "α-Satellite: An AI-Driven System and Benchmark Datasets for Dynamic COVID-19 Risk Assessment in the United States," 2020, IEEE Journal of Biomedical and Health Informatics
  • "TrustLLM: Trustworthiness in Large Language Models," 2024, arXiv (Cornell University)

Best Publications

  • Heterogeneous Graph Attention Network

    Xiao Wang;Houye Ji;Chuan Shi;Bai Wang

  • A Survey on Malware Detection Using Data Mining Techniques

    Yanfang Ye;Tao Li;Donald Adjeroh;S. Sitharama Iyengar

  • A Survey on Heterogeneous Graph Embedding: Methods, Techniques, Applications and Sources

    Xiao Wang;Deyu Bo;Chuan Shi;Shaohua Fan

  • IMDS: intelligent malware detection system

    Yanfang Ye;Dingding Wang;Tao Li;Dongyi Ye

  • Heterogeneous Graph Structure Learning for Graph Neural Networks

    Jianan Zhao;Xiao Wang;Chuan Shi;Binbin Hu

  • HinDroid: An Intelligent Android Malware Detection System Based on Structured Heterogeneous Information Network

    Shifu Hou;Yanfang Ye;Yangqiu Song;Melih Abdulhayoglu

  • An intelligent PE-malware detection system based on association mining

    Yanfang Ye;Dingding Wang;Tao Li;Dongyi Ye

  • Deep4MalDroid: A Deep Learning Framework for Android Malware Detection Based on Linux Kernel System Call Graphs

    Shifu Hou;Aaron Saas;Lifei Chen;Yanfang Ye

  • Malicious sequential pattern mining for automatic malware detection

    Yujie Fan;Yanfang Ye;Lifei Chen

  • CIMDS: Adapting Postprocessing Techniques of Associative Classification for Malware Detection

    Yanfang Ye;Tao Li;Qingshan Jiang;Youyu Wang

  • Knowledge-aware Coupled Graph Neural Network for Social Recommendation

    Chao Huang;Huance Xu;Yong Xu;Peng Dai

  • Graph Representation Learning: Foundations, Methods, Applications and Systems

    Wei Jin;Yao Ma;Yiqi Wang;Xiaorui Liu

  • Automatic malware categorization using cluster ensemble

    Yanfang Ye;Tao Li;Yong Chen;Qingshan Jiang

  • Automatic Detection of Helmet Uses for Construction Safety

    Abu H. M. Rubaiyat;Tanjin T. Toma;Masoumeh Kalantari-Khandani;Syed A. Rahman

  • SBMDS: an interpretable string based malware detection system using SVM ensemble with bagging

    Yanfang Ye;Lifei Chen;Dingding Wang;Tao Li

  • Combining file content and file relations for cloud based malware detection

    Yanfang Ye;Tao Li;Shenghuo Zhu;Weiwei Zhuang

  • DeepAM: a heterogeneous deep learning framework for intelligent malware detection

    Yanfang Ye;Lingwei Chen;Shifu Hou;William Hardy

  • Hyperbolic Graph Attention Network

    Yiding Zhang;Xiao Wang;Chuan Shi;Xunqiang Jiang

  • Network Schema Preserving Heterogeneous Information Network Embedding.

    Jianan Zhao;Xiao Wang;Chuan Shi;Zekuan Liu

  • Heterogeneous Graph Attention Network.

    Xiao Wang;Houye Ji;Chuan Shi;Bai Wang

Frequent Co-Authors

Chuan Shi
Chuan Shi Beijing University of Posts and Telecommunications
Tao Li
Tao Li Florida International University
xin li
xin li Louisiana State University
Shouhuai Xu
Shouhuai Xu University of Colorado Colorado Springs
Philip S. Yu
Philip S. Yu University of Illinois at Chicago
Kenneth A. Loparo
Kenneth A. Loparo Case Western Reserve University
Chang-Tien Lu
Chang-Tien Lu Virginia Tech
Yangqiu Song
Yangqiu Song Hong Kong University of Science and Technology
Zhao Qin
Zhao Qin Syracuse University
Pan Li
Pan Li Case Western Reserve University

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