Hi! I'm Adam Roberge, a Computer Engineering student at the University of Toronto, minoring in Artificial Intelligence, and expected to graduate in May 2027.

I'm passionate about Computer Vision, especially in Autonomous Vehicles, and Multimodal Architecture. Technology has always fascinated me, and I love learning new skills. I continuously strive to apply AI to solve real-world problems.

Stay updated with the latest insights and developments in 2D vision for autonomous vehicles and other computer vision topics on my Medium page. I regularly publish articles that delve into cutting-edge research, practical applications, and innovative solutions in the realm of computer vision and artificial intelligence.

DynamicTokenLoc ViT enables flexible token allocation in Vision Transformers and allows visualizing attention maps at any layer.

Efficient MultiLevelUNet is a specialized U-Net architecture incorporating multi-level global pooling for enhanced feature extraction and classification, developed using the NIH Chest X-Ray dataset.

Ultimate EV Mapper is a GIS project using C++ and Algorithms to find the optimal path and integrate real-time data such as weather, wind speed, wind direction, and the nearest EV charging stations.

EscapeQuest is a two-player maze game developed in C and Assembly for the Nios II processor environment, where Player 1 races to a dynamically changing checkpoint while Player 2 attempts to catch them, leveraging FPGA capabilities for a responsive experience.