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Eduardo Feo Flushing
Also published under:Eduardo Feo-Flushing
Affiliation
Department of Computer Science, Carnegie Mellon University in Qatar, Ar-Rayyan, Qatar
Topic
Mission Planning,Task Allocation,Group Of Agents,Makespan,Mixed Integer Linear Programming,Rescue Missions,Sequential Task,Solution Approach,Task Completion,Task Scheduling,Task Workload,Wireless Networks,3D Planning,Access Points,Advanced Machine Learning,Aerial Robots,Amount Of Time,Application Programming Interface,Artificial Neural Network,Auction,Benchmark Instances,CPLEX Solver,Communication Constraints,Communication Range,Convolutional Neural Network,Convolutional Neural Network Model,Data Augmentation,Deep Convolutional Neural Network,Deep Learning,Differences In Performance,Distribution Of Tasks,Diverse Capabilities,Enhancing Communication,Euclidean Space,Exact Method,Execution Plan,Feasible Solution,Fraction Of Time,General Properties,Genetic Operators,Graph Neural Networks,Ground Plane,Heterogeneous Agents,Heterogeneous Multi-robot Teams,Heterogeneous Systems,Heterogeneous Teams,Impact Of Different Parameters,Incremental Manner,Incremental Update,Indoor Wireless,
Biography
Eduardo Feo Flushing received the first M.Sc. degree in informatics from the University of Trento, Italy, in 2010, the second M.Sc. degree in software system engineering from RWTH Aachen University, Germany, in 2010, and the Ph.D. degree from the University of Lugano, Switzerland, in 2017. He is an Assistant Teaching Professor with Carnegie Mellon University in Qatar. From 2018 to 2021, he was a Postdoctoral Associate with the Department of Computer Science, Carnegie Mellon University in Qatar. From 2011 to 2017, he was with the Dalle Molle Institute for Artificial Intelligence (IDSIA), Switzerland. He is an Erasmus Mundus Master’s Alumni. His research interests include integrating cyber-physical systems, artificial intelligence, wireless networking, and multi-robot systems to develop affordable solutions for societal challenges.