Dr. Tarek Taha

Robotics Lab Lead @ Dubai Future Lab

About Me

Dr Tarek Taha currently leads the Robotics Lab at Dubai Future Foundation. He has more than 15 years of experience in the fields of robotics, autonomous systems and artificial intelligence while working for both, industry and academia.

He obtained his PhD in Robotics and Mechatronics from the Centre of Excellence for Autonomous Systems (CAS), University of Technology Sydney, Australia. He worked in Sydney, Australia in the advanced R&D sector, before joining Khalifa University. He then founded and led the Autonomous Aerial Lab at Algorythma in Abu Dhabi before moving to the Robotics Lab at the Dubai Future Labs where he is currently leading the robotics lab. He led productive R&D teams to produce novel research outcomes and develop effective engineering solutions and products for deployment in real-world applications. Moreover, he supervised/co-supervised various research projects and activities focusing on robot autonomy, perception, navigation, connected autonomous vehicles and artificial intelligence.

Dr Tarek has more than 30 peer-reviewed papers in topics related to autonomous aerial systems; autonomous exploration, navigation and mapping; machine vision; human-robot interaction; assistive robotics and reinforcement learning.

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Experience

2024 2020

Lead - Robotics Lab

Robotics Lab - Dubai Future Foundation

2020 2018

Senior Technical Lead

Algorythma - Autonomous Aerial Lab

2020 2018

Mentor and Technical Consultant

Krypto Labs

2018 2013

Senior Researcher / Postdoctoral Research Fellow

Center for Autonomous Robotics Systems, Khalifa University

2013 2010

Senior Mechatronics Engineer

Memjet Technology, Australia

2010 2008

Intelligent Systems Engineer

Silverbrook Research

Education & Training

Professional Certificate 2023

Chief Technology Officer

MIT Professional Education

Ph.D. 2010

Ph.D. in Robotics and Mechatronics

University of Technology Sydney

Graduate Certificate 2010

Research Commecialization

Australian Technology Network

M.Eng 2003

Computer Control

University of Technology Sydney

B.S. 2002

Computer Engineering

Eastern Mediterranean University

Research Activities

Coverage path planning focuses on mobilizing a robotic platform in a particular environment in order to achieve adequate coverage as needed by the intended application. For instance, domestic robotic vacuum cleaners attempt to achieve full coverage by moving the robot around the house in order to completely clean it. Similarly, a painting robot utilizes a coverage algorithm in order to completely paint the surface. Many of the new applications, however, focus on either 3D reconstruction or inspection of a large structure, building, or area (e.g., bridges, wind turbines, planes, power plants etc.).