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Abbas Sadat

Abbas Sadat is a senior research scientist at Uber ATG Toronto working on self-driving vehicles. His research interest lies in Robotics, focusing on safe decision-making and motion planning, leveraging machine-learning. Before joining ATG, he worked as autonomous driving research engineer at Bosch Research. He obtained his computing science PhD from SFU in 2016. His PhD research was on planning and decision making for small-size UAVs.

Research Papers

End-to-end Interpretable Neural Motion Planner

W. Zeng, W. Luo, S. Suo, A. Sadat, B. Yang, S. Casas, R. Urtasun
In this paper, we propose a neural motion planner for learning to drive autonomously in complex urban scenarios that include traffic-light handling, yielding, and interactions with multiple road-users. Towards this goal, we design a holistic model that takes as input raw LIDAR data and an HD map and produces interpretable intermediate representations in the form of 3D detections and their future trajectories, as well as a cost volume defining the goodness of each position that the self-driving car can take within the planning horizon. [...] [PDF]
Conference on Computer Vision and Pattern Recognition (CVPR), 2019

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