Dr Oya Celiktutan

Lecturer (Assistant Professor)

I am a Lecturer (Assistant Professor) in the Centre for Robotics Research (CoRe) Group within the Department of Informatics, King's College London, United Kingdom. Before this, I spent several years as a postdoctoral researcher in the Personal Robotics Lab, Department of Electrical and Electonic Engineering, Imperial College London (2017-2018); Graphics and Interaction Research Group (Rainbow), Computer Laboratory, University of Cambridge (2016-2017); and Multimedia and Vision Research Group, School of Electrical Engineering and Computer Science, Queen Mary University of London (2013-2015). I obtained my PhD degree in Electrical and Electronic Engineering from Bogazici University, Turkey, in collaboration with National Institute of Applied Sciences of Lyon, France, in 2013. Broadly speaking, my research focuses on computer vision and pattern recognition within a context of applied work in the areas of human behaviour understanding, human-computer interaction, and human-robot interaction.


User Modelling

Intelligent virtual agents · mental state recognition · eye movement analysis

Robotic Teleoperation

Imitating human movements · personality perception

Multiparty Interaction

Personality and engagement recognition · multimodal data fusion

Personality/Emotion Recognition

Nonverbal behaviour analysis · group emotion recognition

Human Activity Recognition

Hyper-graph matching · Hidden Markov Models · HARL dataset

Face Analysis

Face landmarking · Bosphrous 2D/3D face dataset

Camera Source Identification

Image forensics features · sequential feature selection


2019-2020 (Role: PI, £25K)

Wiring the Smart City

King's Together Multi & Interdisciplinary Research Award

An exciting multidisciplinary project that is on a mission to build a 5G connected smart platform for public safety and health in large urban areas such as London. The team is distributed across three King’s faculties, namely, NMS, IoPPN, SSPP, and five research centres including CTR, CoRe, CTI, CUSP, and SLaM. More info will follow - stay tuned!

2017-2018 (Role: Post-doc)

Personal Assistant for Healthy Lifestyle (PAL)

Horizon 2020

PAL project aimed to develop (mobile) health applications for the purpose of assisting diabetic children through a social robot and its mobile virtual avatar. My role involved developing vision-based methods for estimating user’s mental states to enable system personalisation mechanisms

2014-2017 (Role: Post-doc)

Being There


This project was a unique collaboration between researchers and artists to enable people to access to public spaces through cutting-edge robotic telepresence systems. My role involved developing (multimodal) methods to automatically model nonverbal cues during human-robot interaction.

2013-2014 (Role: Post-doc)



MAPTRAITS aimed at developing natural, human-like virtual agents that can not only sense their users, but also adapt their own personalities to their users' personalities. My role involved devising a real-time personality prediction system.


Random Variables and Stochastic Processes

This is a first semester (autumn) module for students doing MSc in Engineering, Data Science, Mobile & Personal Communication and Telecommunications & Internet Technology. The aim of this module is to introduce the fundamentals of probability theory and develop the tools needed to understand more advanced topics such as random sequences, continuous and discrete-time random processes, and filtering. For more information, please click here .

Machine Learning for Affect Analysis

This has been a series of lectures I delivered as part of Affective Computing module, in the Department of Computer Science and Technology, University of Cambridge (Nov. 2016 and Oct. 2017). The aim of this lecture is to introduce unsupervised and supervised machine learning techniques that are widely used in the area of affective computing and develop the skills needed to identify suitable algorithm according to the specificities of the tasks in this area.


Color Panel