Expertise
Dr Falah is an expert in reinforced deep learning, advanced control, optimisation and prediction, and their application to autonomous systems. He has led and contributed to several research activities funded by the UK and European governments as well as industry (EPSRC, Innovate UK, H2020, KTP). He and his research team contributed to the development of i) novel cloud-assisted distributed control systems for highly automated driving functionalities, ii) advanced AI-enabled control and prediction algorithms for autonomous robot systems and iii) perception-based decision-making systems using deep reinforcement learning.
Dr Fallah is the Director of the Connected Autonomous Vehicles Lab (CAV-Lab) at the University of Surrey, where he leads a team of academic scholars, researchers, and RAS experts whose research has contributed to the state-of-the-art research in the areas of CAVs and autonomous systems here in the UK and also globally through collaborative projects delivered in partnership with international companies. CAV-Lab provides a unique laboratory to design, develop and test the next generation of robotics and autonomous systems used for remote assembly and manufacture, highly automated transportation systems, and missions in hazardous environments including space. CAV-Lab also provides expertise in distributed control systems, AI and machine learning, and predictive optimisation techniques. Due to the heavy reliance on simulation technologies for robotics testing, the lab is particularly strong in the development of digital twins using Unity.
Prior to joining the University of Surrey, he was part of a cross-disciplinary team in Green Intelligent Transportation Systems research (University of Waterloo, Canada) in collaboration with General Motors of the USA. He also previously collaborated with Canadian Space Agency in the development of power system management and optimization tools for space missions.