David Meger

David Meger is an Assistant Professor in the School of Computer Science at McGill University. His research focuses on Computer Vision, Machine Learning, and Robotics. He has contributed to various projects, including the development of robotic systems for environmental monitoring and autonomous navigation. His work has been published in several conferences and journals, with notable contributions in areas such as 3D object recognition, visual search, and sensor network localization. Meger's research interests also include the application of robotics in disaster management and intelligent decision systems.

David Meger is an Associate Professor at McGill University specializing in Robotics, Machine Learning, and Computer Vision. His research focuses on advancing deep reinforcement learning, particularly in addressing function approximation errors and improving off-policy learning methods. He explores applications of these techniques in robotics, including visual search, 3D object reconstruction, and multimodal manipulation policies. His work also involves integrating sensory data from vision and touch to enhance robotic perception and navigation. Meger's research emphasizes the development of robust and efficient algorithms for complex environments, with a focus on real-world applications such as underwater navigation and spatial-semantic modeling.