Fay Zhong Faculty Profile

Fay  Zhong

Associate Professor

Department of Computer Science

Extended Reality, Data Engineering, Machine Learning, STEM Education

  • Ph.D., The University of Texas at Dallas
Fall Semester 2022
Course #SecCourse TitleDaysFromToLocationCampus
CS 30103Data Structures & AlgorithmsTTH1:15PM2:30PMWEB-SYNCHOnline Campus
CS 30107Data Structures & AlgorithmsTTH2:45PM4:00PMWEB-SYNCHOnline Campus
CS 61101Theory of ComputationTH9:30AM10:45AMMB-2079Hayward Campus
CS 61103Theory of ComputationTH11:00AM12:15PMMB-2079Hayward Campus
CS 69201Capstone ExaminationsF3:00PM4:30PMSC-S302Hayward Campus

Selected Recent Publications:

JOURNAL PAPERS

  • X. Gao, Y. Yang, G. Chen, X. Lu, J. Zhong. Global Optimization for Multi-Channel Wireless Data Broadcast with AH-Tree Indexing Scheme. IEEE Transactions on Computers (TC). Vol. 65, Issue 7, 2016.
  • D. Kim, J. Zhong, M. Lee, D. Li, Y. Li, A.O. Tokuta. Efficient respondents selection for biased survey using homophily-high social relation graph. Discrete Mathematics, Algorithms and Applications (DMAA), Vol. 8, No. 04, Dec 2016.
  • Z. Mundher, and J. Zhong. Provide a Global Tracking Feature for Person-Following Robot based on the Kinect Sensor. Journal of Automation and Control Engineering, 2014.
  • J. Zhong, W. Wu, X. Gao, Y. Shi, and X. Yue. Evaluation and Comparison of Various Indexing Schemes in Single-Channel Broadcast Communication Environment, Knowledge and Information Systems: An International Journal (KAIS), 2014.

CONFERENCE PAPERS

  • S. Clark, E. Kamalinejad, C. Magpantay, S. Sahota, J. Zhong, Y. Hu. A Review of CNN on Medical Imaging to Diagnose COVID-19 Infections. The 34th International Conference on Computer Applications in Industry and Engineering (CAINE'21), October 11th-13th, 2021.
  • R. Eskandar, J. Zhong, Y. Hu. Diagnosing COVID-19 Using Convolutional Neural Networks and Deep Learning Approaches. The 7th International Conference on Health Informatics & Medical Systems (HIMS'21), Las Vegas, NV, United States, July 26-29, 2021.
  • A. Chidumije, F. Gowher, E. Kamalinejad, J. Mercado, J. Soni, J. Zhong. A Survey of CNN and Facial Recognition Methods in the Age of COVID-19. The 5th International Conference on Information System and Data Mining (ICISDM'21), Silicon Valley, California, United States, May 27th-29th, 2021.
  • A. Kim, E. Kamalinejad, K. Madal-Hellmuth, J. Zhong. Deep Learning Based Face Recognition Application with Augmented Reality Devices, the Future of Information and Communications Conference (FICC'20), San Francisco, California, March 5th-6th, 2020.
  • D. Haley, E. Kamalinejad, J. Zhong. IsoClustering: A Generalized Framework for Local Data Clustering, the 18th IEEE International Conference on Machine Learning and Applications (ICMLA'19), Boca Raton, Florida, December 16th-19th, 2019.
  • J. Zhong. Actively Engage Students with Diverse Background Using a More Personalized Approach, The 48th IEEE Frontiers in Education Conference (FIE'18) Fostering Innovation Through Diversity, San Jose, California, October 3rd-6th, 2018.
  • J. Zhong. Designing Adaptive Learning Objects for Enhanced Student Engagement in Data Structures and Algorithms, Proceedings of the 49th ACM Technical Symposium on Computer Science Education (SIGCSE'18), pp. 1089-1089, Baltimore, Maryland, February 21st-24th, 2018.
  • S. Yu, F. Xia, K. Zhang, Z. Ning, J. Zhong and C. Liu. Team Recognition in Big Scholarly Data: Exploring Collaboration Intensity, The 3rd IEEE International Conference on Big Data Intelligence and Computing (DataCom'17), Orlando, Florida, USA, November 6th-10th, 2017. [Best Paper Award]

  • “Collaborative Research: A Technology Pathway Program in Data Technology and Applications,” National Science Foundation, NSF-DUE-1626612, 10/1/2016-9/30/2020.
  • “Collaborative proposal: Faculty and Undergraduate Research Student Teams (FURST),” National Science Foundation, NSF-DMS-1620500, 1/1/2017-12/31/2020.