Biography

Amin Alizadeh Naeini is a Schmidt Scholar and postdoctoral researcher at the Toronto Robotics and AI Laboratory (TRAIL), University of Toronto, under the supervision of Prof. Steven L. Waslander. His current project, Robust All-Weather Lane Perception and Behavior Prediction for Autonomous Driving, focuses on developing safer autonomous driving systems for adverse conditions, with special attention to Canadian winter environments.

Before joining TRAIL, he was a VISTA Scholar and postdoctoral fellow at ElderLab, York University, where he worked on explainable deep learning for monocular depth estimation and the geospatial alignment of UAV imagery with orthophotos. He received his Ph.D. in Earth and Space Sciences from York University in 2024, where he conducted research in the ASUM Lab on deep learning for monocular depth estimation, ground completion, and LiDAR-based terrain modeling. He also holds a Ph.D. in Photogrammetry from the University of Tehran, focused on computer vision, hyperspectral image analysis, pattern recognition, and optimization.

His research connects computer vision, remote sensing, deep learning, and autonomous systems. At TRAIL, he works on all-weather lane perception, behavior prediction, sensor uncertainty, and simulation-supported data generation to support robust autonomous driving in complex real-world environments.