Hongyi Zhu, Ph.D.

Assistant Professor, Information Systems and Cyber Security

Hongyi Zhu Headshot

Contact

Bio

Google Scholar Page

Dr. Hongyi Zhu is an Assistant Professor in the Department of Information Systems and Cyber Security at the Alvarez College of Business. He received his Ph.D. in Management Information Systems from the University of Arizona (UA).

Dr. Zhu’s research focuses on developing artificial intelligence-based analytics for mobile and mental health, cybersecurity, and business intelligence. He has expertise in deep learning, network analysis, and data/text mining. He has multidisciplinary research interests and has published in various prestigious journals, conferences, and workshops, including MIS Quarterly, Journal of Management Information Systems, IEEE Transactions on Knowledge and Data Engineering, ACM Transactions on Privacy and Security, ACM Transactions on Management Information Systems, Journal of Biomedical Informatics, and others. He is a member of the IEEE, ACM, AIS, and INFORMS.

Teaching

  • Computer Networking and Telecommunication Systems

Research Interests

  • Mobile health and mental health analytics, smart home, IoT
  • Cyber threat intelligence, vulnerability (propagation) assessment
  • Knowledge mapping, technology outcomes assessment, network science
  • Data analytics and business analytics

Degrees

  • Ph.D. University of Arizona
  • BBM. Tsinghua University

Publications

  • “Creating Proactive Cyber Threat Intelligence with Hacker Exploit Labels: A Deep Transfer Learning Approach,” with B. Ampel, S. Samtani, and H. Chen, Forthcoming at MIS Quarterly (MISQ).
  • “Additive Feature Attribution Explainable Methods to Craft Adversarial Attacks for Text Classification and Text Regression,” with Y. Chai, R. Liang, S. Samtani, M. Wang, Y. Liu, & Y. Jiang, IEEE Transactions on Knowledge and Data Engineering (TKDE), Vol. 35, No. 12, 2023, pp. 12400-12414.
  • “Deep Learning for Information Systems Research,“ with S. Samtani, B. Padmanabhan, Y. Chai, H. Chen, & J. F. Nunamaker, Journal of Management Information Systems (JMIS), Vol. 40, No. 1, 2023, pp. 271-301.
  • “A Deep Learning Approach for Recognizing Activity of Daily Living (ADL) for Senior Care: Exploiting Interaction Dependency and Temporal Patterns,” with S. Samtani, R. Brown, & H. Chen, MIS Quarterly (MISQ), Vol. 45, No. 2, 2021, pp. 859-896.
  • “Proactively Identifying Emerging Hacker Threats: A Diachronic Graph Embedding Framework (D-GEF),” with S. Samtani & H. Chen, ACM Transactions on Privacy and Security (TOPS), Vol. 23, No. 4, 2020, pp. 1-33.
  • “Human Identification for Activities of Daily Living: A Deep Transfer Learning Approach,” with S. Samtani, H. Chen, & J. F. Nunamaker, Journal of Management Information Systems (JMIS), Vol. 37, No. 2, 2020, pp. 457–483.
  • “Comparing Nanotechnology Landscapes in US and China: A Patent Analysis Perspective,” with L. Wu, H. Chen, & M. Roco, Journal of Nanoparticle Research (JNR), Vol. 21, No. 8, 2019, pp. 180.
  • “Fear Appeals and Information Security Behaviors: An Empirical Study on Mechanical Turk,” with S. Samtani & S. Yu, AIS Transactions on Replication Research (TRR), Vol. 5, No. 5, 2019, pp. 1-22.
  • “Emoticon Analysis for Chinese Social Media and E-commerce: The AZEmo System,” with S. Yu, S. Jiang, Y. Zhang, C. Xing, & H. Chen, ACM Transactions on Management Information Systems (TMIS), Vol. 9, No. 4, 2019, pp. 16.
  • “A Sequence-to-Sequence Model-Based Deep Learning Approach for Recognizing Activity of Daily Living for Senior Care,” with H. Chen & R. Brown, Journal of Biomedical Informatics (JBI), Vol. 84, 2018, pp. 148-158.