Dr Oya Celiktutan is a Reader in the Department of Engineering at King’s College London, where she leads the Social AI & Robotics Laboratory. She is also Interim Co-Director of the Centre for Robotics within the Faculty of Natural, Mathematical & Engineering Sciences. In September 2026, she was awarded the Guy's and St Thomas' NHS Foundation Trust/ Royal Academy of Engineering Senior Research Fellowship in CO-STAR: CO-designing Socially inTelligent Assistive Robots for future healthcare.

She received her BSc degree in Electronics Engineering from Uludag University and her MSc and PhD degrees in Electrical and Electronics Engineering from Bogazici University, Turkey. During her doctoral studies, she was a visiting researcher at the National Institute of Applied Sciences of Lyon, France. After completing her PhD, she moved to the United Kingdom, where she worked as a postdoctoral researcher at Queen Mary University of London, the University of Cambridge, and Imperial College London. In 2018, she joined King’s College London.

Dr Celiktutan’s research focuses on multimodal machine learning for developing autonomous agents, including robots and virtual agents, that can interact seamlessly with humans. Her research addresses challenges in multimodal perception, understanding and forecasting human behaviour, and advancing the navigation, manipulation, and social awareness capabilities of autonomous agents.

Her research has been supported by EPSRC, the Royal Society, EU Horizon programmes, and the Royal Academy of Engineering, as well as through industrial collaborations. Her team’s research has received several awards and distinctions, including the Best Paper Award at IEEE RO-MAN 2022, the NVIDIA CCS Best Student Paper Award Runner-Up at IEEE FG 2021, and the First-Place Award and Honourable Mention Award at the ICCV UDIVA Challenge 2021.

As part of CO-STAR, Dr Celiktutan’s research focuses on developing socially intelligent assistive robots that can support patients and clinicians across healthcare environments. Her work aims to advance the safe and responsible adoption of robotics in healthcare by ensuring that technologies are co-designed and evaluated around the needs of patients, clinicians, and other end users.

Research Interests

• Multimodal Machine Learning
• Human-Robot Interaction
• Human Behaviour Analysis and Synthesis
• Generative Models
• Continual Learning
• Reinforcement Learning

More Information

• Research Profile
• Personal Website