Robotics

About the event

Calling all alumni who graduated within the last 10 years! Interested in a career in Robotics? Thinking about your next career move within the field? If so, Alumni Insights: Careers in Robotics is the event for you.

Alumni Insights events are designed to inform and inspire, providing a unique opportunity to hear from alumni who are experts in their field.

Alumni will talk about their career in the field of Robotics, what attracted them to the sector and challenges and opportunities they have met along the way. The panel will also share their thoughts on how the sector is evolving and opportunities and suggestions for career progression. After the panel discussion there will be a Q&A.

About the speakers

The panel will be chaired by Dr Edward Johns, Director of the Robot Learning Lab at Imperial College London. 

Dr Johns is also a Lecturer and Royal Academy of Engineering Research Fellow. His work lies at the intersection of robotics, computer vision, and machine learning, and he and his team are currently studying visually-guided robot manipulation.

He received a BA and MEng in Electrical and Information Engineering from Cambridge University, and a PhD in visual place recognition from Imperial. He then spent a year as a postdoc at UCL, before returning to Imperial College as a founding member of the Dyson Robotics Lab along with Andrew Davison, where he led the robot manipulation team. In 2017, he was awarded a Royal Academy of Engineering Research Fellowship for his project “Empowering Next-Generation Robots with Dexterous Manipulation: Deep Learning via Simulation”, and then in 2018 he was appointed as a Lecturer and founded the Robot Learning Lab.

Panellists 

Dr Feryal Behbahani (MSc Computing 2011, PhD 2016) – Research Scientist, DeepMind

James Walker (BSc Physics 2012, MSc 2014) – Software Engineer, Automata

Orfeo Nicolai (MSc Innovation Design Engineering 2018) – Head of Software, Karakuri

Please note that this event is open to alumni and students of Imperial College London only.

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