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Nikolay Atanasov
Also published under:Nikolay A. Atanasov
Affiliation
Contextual Robotics Institute, University of California San Diego, La Jolla, CA, USA
Topic
Control Input,Neural Network,Simultaneous Localization And Mapping,Quadratic Programming,Robot State,Control Synthesis,Nonlinear Systems,Optimization Problem,Point Cloud,Safety Constraints,Semantic Information,Stability Constraints,Swarm Robotics,Activation Maps,Asymptotically Stable,Conditional Value At Risk,Continuously Differentiable Function,Depth Camera,Learning Models,Locally Lipschitz,Model Uncertainty,Nominal Model,Path Planning,Robot Operating System,Robot Trajectory,Safe Set,Safety Control,Second-order Cone Programming,Semantic Segmentation,Signed Distance Function,Wasserstein Distance,Accuracy Of Model,Angular Velocity,Artificial Neural Network,Camera Pose,Center Of Mass,Closed-loop System,Control Barrier,Control Design,Cost Function,Deep Learning,Deep Reinforcement Learning,Depth Images,Distributed Algorithm,Dynamic Model,Dynamical,Feasible Set,Free Space,Graph Neural Networks,Inner Nodes,
Biography
Nikolay Atanasov (Member, IEEE) received the B.S. degree in electrical engineering from Trinity College, Hartford, CT, USA, in 2008 and the M.S. and Ph.D. degrees in electrical and systems engineering from the University of Pennsylvania, Philadelphia, PA, USA, in 2012 and 2015, respectively.
He is currently an Assistant Professor of Electrical and Computer Engineering with the University of California San Diego, La Jolla, CA, USA. He works on probabilistic models that unify geometric and semantic information in simultaneous localization and mapping (SLAM) and on optimal control and reinforcement learning algorithms for minimizing uncertainty in probabilistic models. His research focuses on robotics, control theory, and machine learning with applications to active perception problems for autonomous mobile robots.
Dr. Atanasov was the recipient of the Joseph and Rosaline Wolf award for the best Ph.D. dissertation in Electrical and Systems Engineering, University of Pennsylvania in 2015, the best conference paper award at the IEEE International Conference on Robotics and Automation (ICRA) in 2017, and the NSF CAREER award in 2021.
He is currently an Assistant Professor of Electrical and Computer Engineering with the University of California San Diego, La Jolla, CA, USA. He works on probabilistic models that unify geometric and semantic information in simultaneous localization and mapping (SLAM) and on optimal control and reinforcement learning algorithms for minimizing uncertainty in probabilistic models. His research focuses on robotics, control theory, and machine learning with applications to active perception problems for autonomous mobile robots.
Dr. Atanasov was the recipient of the Joseph and Rosaline Wolf award for the best Ph.D. dissertation in Electrical and Systems Engineering, University of Pennsylvania in 2015, the best conference paper award at the IEEE International Conference on Robotics and Automation (ICRA) in 2017, and the NSF CAREER award in 2021.