Petr Svec
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Assistant Research Scientist 301/405-5577 TEL |
Research Interests
Development of autonomy for robotic systems including unmanned sea surface, ground, aerial vehicles, and optical tweezers: machine learning and artificial intelligence for automated synthesis of action selection policies and their representations, multi-agent and motion planning under uncertainty.
Background Information
Dr. Petr Svec is an Assistant Research Scientist in the Department of Mechanical Engineering at the University of Maryland, College Park. Prior to joining the University of Maryland, he was a Graduate Research Assistant at the Faculty of Mechanical Engineering, Brno University of Technology in the Czech Republic. During his Ph.D. study, he received one year Ph.D. fellowship to perform research at the Department of Computer Science, Faculty of Engineering, University of Bristol in the UK. Dr. Svec received a Master's degree in Computer Science from the Institute of Automation and Computer Science, Faculty of Mechanical Engineering at the Brno University of Technology in 2003. Due to his preparation for interdisciplinary research in robotics by simultaneously studying Computer Science and Mechanical Engineering at two universities, he received a Bachelor's degree in Computer Science from the Faculty of Informatics, Masaryk University in 2004 and second Master's degree in 2006 from the same institute. Dr. Svec received a Ph.D. in Mechanical Engineering (Machines and Equipment program, Design and Process Engineering branch) with a focus on robot motion planning from the Brno University of Technology in 2007. Besides his academic work, he also worked on a variety of software engineering projects in private companies in the Czech Republic and United Kingdom.
His research interests in robotics include machine learning with (co-)evolutionary and reinforcement learning techniques and artificial intelligence for automated synthesis of action selection policies and their corresponding adaptive representations, multi-agent and trajectory planning under uncertainty.
Links
Mechanical Engineering Department
Simulation-Based System Design Laboratory
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