Aleksandra Faust is a Deep Learning Task and Motion Planning Technical Lead and Manager at Google Brain Robotics, specializing in reinforcement learning. Previously, Aleksandra led machine learning efforts for self-driving car planning and controls in Waymo and Google X, and was a researcher in Sandia National Laboratories, where she worked on satellites and other remote sensing applications. She earned a Ph.D. in Computer Science at the University of New Mexico (with distinction), a Master’s in Computer Science from University of Illinois at Urbana-Champaign, and a Bachelor’s in Mathematics from University of Belgrade, Serbia. Her research interests include reinforcement learning, adaptive motion planning, and machine learning for decision-making. Aleksandra won the Tom L. Popejoy Award for the best doctoral dissertation at the University of New Mexico in Engineering, Mathematics, and Sciences in the period of 2011-2014. She was also awarded with Sandia National Laboratories’ Doctoral Studies Program and New Mexico Space Grant fellowships. Her work has been featured in the ZdNet, New York Times, and PC Magazine.View the profile
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Aleksandra Faust, Staff Research Scientist at Google Brain Robotics, discusses how to use machine learning to improve robot navigation systems.
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