Faculty Profiles
Nikolay A. Atanasov
Professor, Electrical and Computer Engineering
Calit2
Robotics, control theory, optimization, computer vision, machine learning, autonomous information collection, sensor-based planning, reactive navigation, unmanned aerial vehicles, active localization and mapping
Nikolay Atanasov's research focus is on controlling teams of aerial and ground robots to collect metric, semantic, and topological information in applications such as environmental monitoring, security and surveillance, localization and mapping, search and rescue. His work investigates how to perform distributed sensing and estimation of the evolution of physical processes of interest, how to plan robot motion that minimizes the estimation uncertainty, the energy expenditure, and the information exchange among the robots, and how to have the robots autonomously execute these motion plans in a safe and robust manner. In addition to system modeling, algorithm design, and theoretical analysis, his work involves experimental validation in real robot deployments.
Capsule Bio:
Nikolay Atanasov is a Professor in the Department of Electrical and Computer Engineering at the University of California San Diego, La Jolla, CA, USA. He obtained a B.S. degree in Electrical Engineering from Trinity College, Hartford, CT, USA in 2008, and M.S. and Ph.D. degrees in Electrical and Systems Engineering from University of Pennsylvania, Philadelphia, PA, USA in 2012 and 2015, respectively. Dr. Atanasov's research focuses on robotics, control theory, and machine learning with emphasis on active perception problems for autonomous mobile robots. He works on probabilistic models and inference techniques for simultaneous localization and mapping (SLAM) and on optimal control and reinforcement learning techniques for autonomous robot navigation and uncertainty minimization. Dr. Atanasov's work has been recognized by the Joseph and Rosaline Wolf award for the best Ph.D. dissertation in Electrical and Systems Engineering at the University of Pennsylvania in 2015, the Best Conference Paper Award at the IEEE International Conference on Robotics and Automation (ICRA) in 2017, the NSF CAREER Award in 2021, and the IEEE RAS Early Academic Career Award in Robotics and Automation in 2023.
Selected Publications:
