Connie Ko

Connie Ko is Adjunct Professor in the Faculty of Environmental and Urban Change at York University, where she serves as GIS/Remote Sensing Technician and Research Associate. Her research focuses on advancing LiDAR data processing techniques and developing AI applications for 3D object detection in environmental contexts.

Education credentials:

• PhD in Earth and Space Science & Engineering (York University, 2014)
• MSc in Geography (York University, 2004)
• Bachelor in Environmental Science (York University, 2001)

Research specializes in:

• AI-driven LiDAR analysis for environmental mapping
• 3D object detection methodologies
• Tree genus classification using geometric features
• Large-scale dataset creation for machine learning

Publications demonstrate consistent focus on LiDAR applications (80% of works), particularly in forestry and hydrological contexts. Recent shift toward AI integration evident since 2018. Authored foundational datasets like YUTO Tree5000 and Yuto Semantic to support geospatial AI development.

Teaches GIS/Remote Sensing techniques and mentors students in spatial analysis. Transformed GIS computer lab into collaborative learning hub supporting interdisciplinary environmental research.