Meet our faculty & staff

Frank Zhang is an associate professor in the School of Computing and an associate member of the Geography department at the University of the Fraser Valley (UFV), where he has been since 2017. He currently serves as Chair of Curriculum Development and Articulation, a member of the School Selection Advisory Committee (SAC), and the representative of the Faculty of Business and Computing to the Faculty of Science. Additionally, he holds several leadership roles, including vice-chair of the BCCAT Computing Education Committee, treasurer of the Western Canadian Computing Education Society (WCCES), co-chair of the organizing committee for the 2024 Western Canadian Conference on Computing Education (WCCCE), and a member of the 2025 organizing committee. He also holds adjunct professorships at Fujian Normal University and the China University of Geosciences (Wuhan). He also serves as a reviewer for several journals. 

More information can be found on his LinkedIn page: https://www.linkedin.com/in/kongwen-frank-zhang-257ba8111/

PhD, Earth and Space Science, Remote Sensing, York University, 2014. Dissertation Title: Exploring hyperspectral and very high spatial resolution imagery in vegetation characterization

MSc., Earth and Space Science, Remote Sensing, York University, 2008, Thesis Topic: The FIFEDOM (Frequent Image Frames Enhanced Digital Ortho-rectified Mapping) camera calibration and its applications

BASc., Geomatics Engineering with special Honours, York University, 2005, Thesis Topic: Subsurface Utility Mapping System (SUMS)

• Canadian Remote Sensing Society working group member
• IEEE member

Put student first. Education should always focus on the students' future, emphasizing both career aspirations and personal passions. Recognize and celebrate the differences and unique strengths of each individual. Teaching methods should be flexible and adaptable to meet the diverse needs of every student.

Continuously explore and evolve new teaching strategies to keep pace with technological advancements and meet the evolving needs of a new generation of students.

Leveraging advancements in machine learning and deep learning to enhance multi-platform remote sensing (e.g., satellite-borne, airborne, drone, close-range) image processing and information retrieval, enabling the development of highly robust and automated 3D modeling, monitoring, and analytic systems for environmental, economic, and social applications.

• Miao, S., Zhang, K. F., Zeng, H., Liu, J. “Improving Artificial-Intelligence-Based Individual Tree Species Classification Using Pseudo Tree Crown Derived from Unmanned Aerial Vehicle Imagery”, Remote Sensing, 202416(11), 1849, doi:10.3390/rs16111849.
• Sharma, R., Zhang, K. “Conifer Tree Classification using ConvNeXt from UAV Imagery Data”, proceedings of the 45th Canadian Symposium on Remote Sensing, Halifax, Nova Scotia, 2024.
• Shi, J., Li, H., Lin, Y., Jing, L., Zhang, K. “Individual tree crown delineation based on Deep Learning for ARD areas Using High resolution Satellite Imagery”, processings of the International Geoscience and Remote Sensing Symposium, Athens, Greece, 2024.
• Xie, Q., Li, H., Jing, L., Zhang, K. “Road Eextraction based on Deep Learning using SDGSAT-1 Nighttime Light Data”, processings of the International Geoscience and Remote Sensing Symposium, Athens, Greece, 2024.
• Wang, A., Whang, S., Sagre, E., Sachin, N., Dutra, G., Lim, Y., Hains, G., Khmelevsky, Y and Zhang, K. F.. “Short-Term Stock Price Forecasting using exogenous variables and Machine Learning Algorithms”, processing of the 3rd International Conference on Intelligent Cybernetics Technology & Applications (ICICyTA 2023), Bali, Indonesia, 2023.

Drone micro-credential development with Sea Bird Island.