Zhida Li

Zhida Li

Title
Assistant Professor
Department
Computer Science
Campus
Vancouver
Area(s) of Expertise
Communication Networks, Cybersecurity, Machine Learning, Intrusion Detection Systems
Education Credentials
Ph.D.
Joined New York Tech
2023

Zhida Li received his B.E. and M.Eng.Sc. in electrical engineering and microelectronic design, respectively, from the University College Cork, Ireland. He received his Ph.D. in engineering science from Simon Fraser University (SFU), Canada.

He is an assistant professor in the Department of Computer Science at New York Institute of Technology-Vancouver, in British Columbia, Canada. From 2011 to 2014, he was a research assistant at Tyndall National Institute, Ireland. He was a postdoctoral fellow at SFU from June to December in 2022. His research interests include machine learning systems for detecting network anomalies, brain-computer interfaces, and blockchain.

Li serves as secretary (2022-present) of the Membership Development Committee, IEEE Canada. He is chair (2023–present) of the IEEE Circuits and Systems Society joint chapter of the Vancouver/Victoria sections. He served as a Technical Program Committee (TPC) member of the IEEE International Conference on High Performance Computing and Communications (HPCC) in 2020 and a session chair at IEEE International Conference on Cyber, Physical, and Social Computing (CPSCom) in 2020. He served as a publicity chair and a TPC member of the CPSCom 2022 and a TPC member of the International Conference on E-Business and Internet (ICEBI) 2023. He is a TPC member of the International Conference on Intelligent Sensing and Industrial Automation (ISIA) 2023 and a member of the IEEE.

Selected Publications

Book Chapters
  1. Q. Ding, Z. Li, S. Haeri, and Lj. Trajković, "Application of machine learning techniques to detecting anomalies in communication networks: datasets and feature selection algorithms," in Cyber Threat Intelligence, A. Dehghantanha, M. Conti, T. Dargahi, Eds., Berlin: Springer, pp. 47–70, 2018.
  2. Z. Li, Q. Ding, S. Haeri, and Lj. Trajković, "Application of machine learning techniques to detecting anomalies in communication networks: classification algorithms," in Cyber Threat Intelligence, A. Dehghantanha, M. Conti, T. Dargahi, Eds., Berlin: Springer, pp. 71–92, 2018.
Refereed Journals
  1. Z. Li, A. L. G. Rios, and Lj. Trajković, "Machine learning for detecting the WestRock ransomware attack using BGP routing records," IEEE Commun. Mag. vol. 61, no. 3, pp. 20–26, Mar. 2023. (IF: 9.03)
  2. Z. Li, A. L. G. Rios, and Lj. Trajković, "Machine learning for detecting anomalies and intrusions in communication networks," IEEE Journal on Selected Areas in Communications (JSAC), vol. 39, no. 7, pp. 2254–2264, July 2021. (IF: 13.081)
  3. M. P. Kennedy, Z. Li, and Z. Huang, "Programmable analog frequency divider based on p-switching," Nonlinear Theory and Its Applications, IEICE, vol. 4, no. 4, pp. 389–399, Oct. 2013.
Publications in Refereed Conference Proceedings
  1. T. Sharma, K. Patni, Z. Li, and Lj. Trajković, "Deep Echo State Networks for Detecting Internet Worm and Ransomware Attacks," in Proc. IEEE Int. Symp. Circuits Syst., Monterey, USA, May 2023.
  2. Z. Li, A. L. G. Rios, and Lj. Trajković, "Classifying denial of service attacks using fast machine learning algorithms," in Proc. IEEE Int. Conf. Syst., Man, Cybern., Melbourne, Australia, Oct. 2021, pp. 1221–1226.
  3. Z. Li, A. L. G. Rios, and Lj. Trajković, "Detecting Internet worms, ransomware, and blackouts using recurrent neural networks," in Proc. IEEE Int. Conf. Syst., Man, Cybern., Toronto, Canada, Oct. 2020, pp. 2165–2172.
  4. A. L. G. Rios, Z. Li, K. Bekshentayeva, and Lj. Trajković, "Detection of denial of service attacks in communication networks," in Proc. IEEE Int. Symp. Circuits Syst., Sevilla, Spain, Oct. 2020.
  5. Z. Li, A. L. G. Rios, G. Xu, and Lj. Trajković, "Machine learning techniques for classifying network anomalies and intrusions," in Proc. IEEE Int. Symp. Circuits Syst., Sapporo, Japan, May 2019, pp. 1–5.
  6. A. L. G. Rios, Z. Li, G. Xu, A. Diaz Alonso, and Lj. Trajković, "Detecting network anomalies and intrusions in communication networks," in Proc. 23rd IEEE Int. Conf. Intell. Eng. Syst., Hungary, Apr. 2019, pp. 29–34.
  7. Z. Li, P. Batta, and Lj. Trajković, "Comparison of machine learning algorithms for detection of network intrusions," in Proc. IEEE Int. Conf. Syst., Man, Cybern., Miyazaki, Japan, Oct. 2018, pp. 4248–4253.
  8. P. Batta, M. Singh, Z. Li, Q. Ding, and Lj. Trajković, "Evaluation of support vector machine kernels for detecting network anomalies," in Proc. IEEE Int. Symp. Circuits Syst., Florence, Italy, May 2018, pp. 1–4.
  9. H. B. Yedder, Q. Ding, U. Zakia, Z. Li, S. Haeri, and Lj. Trajković, "Comparison of virtualization algorithms and topologies for data center networks," in Proc. 26th Int. Conf. Comput. Commun. Netw., 2nd Workshop Netw. Security. Analytics Autom., Vancouver, Canada, Aug. 2017.
  10. Q. Ding, Z. Li, P. Batta, and Lj. Trajković, "Detecting BGP anomalies using machine learning techniques," in Proc. IEEE Int. Conf. Syst., Man, Cybern., Budapest, Hungary, Oct. 2016, pp. 3352–3355.
  11. S. Haeri, Q. Ding, Z. Li, and Lj. Trajković, "Global resource capacity algorithm with path splitting for virtual network embedding," in Proc. IEEE Int. Symp. Circuits Syst., Montreal, Canada, May 2016, pp. 666-669.
  12. M. P. Kennedy, H. Mo, Z. Li, G. Hu, P. Scognamiglio, E. Napoli, "The noise and spur delusion in fractional-N frequency synthesizer design," in Proc. IEEE Int. Symp. Circuits Syst., Lisbon, Portugal, May 2015.
  13. Z. Li, H. Mo, and M. P. Kennedy, "Comparative spur performance of a fractional-N frequency synthesizer with a nested MASH-SQ3 divider controller in the presence of memoryless piecewise-linear and polynomial nonlinearities," in _Proc. 25th IET Irish Signals Syst. Conf., Limerick, Ireland, June 2014, pp. 374–379.
  14. M. P. Kennedy, Z. Li, and H. Mo, "How to eliminate integer boundary spurs in fractional-N frequency synthesizers", in Proc. 17th RIA/URSI Research Colloquium Commun. Radio Sci. into the 21st Century, Dublin, Ireland, May 2014, pp. 1–4.
  15. Z. Li and M.P. Kennedy, "The switched injection-locked oscillator (SILO) concept," in Proc. Int. Symp. Nonlinear Theory and Its Applications (NOLTA), Palma, Mallorca, October 2012, pp. 868–871.

Professional Honors and Awards

  • IEEE Outstanding Leadership Award (Dec. 2022): Publicity Chair of the 2022 IEEE International Conference on Digital Twin as a part of the 2022 IEEE Smart World Congress

Courses Taught at New York Tech

  • CSCI 651: Algorithm Concepts
  • CSCI 690: Computer Networks
  • INCS 615: Advanced Network and Internet Security
  • INCS 870: Project I

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