Wissam Bejjani

Wissam Bejjani

Research Engineer (Applied Reinforcement Learning) @ InstaDeep

About Wissam Bejjani

Wissam Bejjani is a Research Engineer specializing in applied reinforcement learning, currently employed at InstaDeep Ltd since 2022. He holds a Bachelor's degree in Mechanical Engineering, a Master's degree in Mechatronics, Robotics, and Automation Engineering, and a PhD in Robotics from the University of Leeds.

Current Role at InstaDeep

Wissam Bejjani serves as a Research Engineer specializing in applied reinforcement learning at InstaDeep Ltd. He has been in this role since 2022, contributing to the development of advanced machine learning algorithms and their applications in various domains. His expertise in reinforcement learning supports the company's mission to enhance AI capabilities.

Education and Academic Background

Wissam Bejjani holds a Bachelor's degree in Mechanical Engineering from Notre Dame University - Louaize (NDU), which he completed from 2008 to 2013. He furthered his education by obtaining a Master’s Degree in Mechatronics, Robotics, and Automation Engineering from TU Dortmund University between 2013 and 2015. He then pursued a Doctor of Philosophy (PhD) in robotics at the University of Leeds from 2017 to 2021.

Previous Research Experience

Prior to his current position, Wissam Bejjani gained valuable research experience in various institutions. He worked as a Research Scientist at EPFL (École polytechnique fédérale de Lausanne) for six months in 2016. Additionally, he served as a Visiting Researcher at DLR in Oberpfaffenhofen, Germany, from 2015 to 2016. He also held a position as a Research Assistant at the American University of Beirut for seven months in 2013.

PhD Research at University of Leeds

During his time at the University of Leeds, Wissam Bejjani focused on R&D Management and Innovation as a PhD student in Machine Learning and Robotics from 2017 to 2021. His research contributed to advancements in the field of robotics, particularly in the integration of machine learning techniques.

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