Arash Tavakoli is a PhD student working with Dr Petar Kormushev at Imperial College London. He received a MS in Computer Science from the University of Southern California (USC) in 2016. He completed his MEng in Electrical Engineering with First Class Honours and Dean's List Recognition at the University College London (UCL) in 2014.
During 2012-2013, he attended the Georgia Institute of Technology as a Visiting Student. In 2013, he joined the Georgia Robotics and Intelligent Systems (GRITS) lab—part of the Institute for Robotics and Intelligent Machines (IRIM) at Georgia Tech—as an Undergraduate Research Assistant, where he conducted research in the area of networked and hybrid control systems with applications to the control and coordination of mobile robots.
From 2014 to 2016, he was a Research Assistant at the Automatic Coordination of Teams (ACT) lab—part of the Robotics and Autonomous Systems Center (RASC) at USC—where his research focused on creating human-inspired coordination algorithms for distributed control of teams of robots.
Arash’s primary research interests revolve around the application of machine learning, in particular reinforcement learning and deep learning, to complex control challenges and robotics.
Tavakoli A, Ayanian N, Multirobot coordination by multiplayer games, IEEE International Conference on Robotics and Automation (ICRA), Fielded Multi-Robot Systems Operating on Land, Sea, and Air Workshop
Hoenig W, Tavakoli A, Ayanian N, Seamless Robot Simulation Integration for Education: A Case Study, IEEE International Conference on Simulation, Modeling, and Programming for Autonomous Robots (SIMPAR), Workshop on the Role of Simulation in Robot Programming
Tavakoli A, Nalbandian H, Ayanian N, Multiplayer Games for Learning Multirobot Coordination Algorithms, arXiv preprint
Tavakoli A, Nalbandian H, Ayanian N, Crowdsourced Coordination Through Online Games, The Eleventh ACM/IEEE International Conference on Human Robot Interaction