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Affective Intelligence and Robotics Laboratory (AFAR)
Welcome to the Cambridge Affective Intelligence and Robotics (AFAR) Lab’s website!
The AFAR Lab’s research interests are in the areas of affective computing and social signal processing that lie at the crossroad of multiple disciplines including, computer vision, signal processing, machine learning, multimodal interaction and human-robot interaction.
• Autonomous, socio-emotionally intelligent systems and social robots
• Long-term, adaptive and personalized interactions ( Virtual Reality / Human-Computer & Human-Robot Interaction )
The AFAR Lab’s research approaches toward this vision include:
• Iterative design and data gathering
• Learning from experienced humans (e.g., coaches)
• face-to-face studies to gather multimodal interaction data (e.g., MHHRI Dataset)
• Simulated data and crowdsourced labels to achieve Sim2Real (e.g., MANNERS DB)
• Machine learning (Traditional ML techniques, Deep learning, Continual learning, Federated learning, Graph representations, Generative AI, Bias analysis, mitigation and fairness)
Some of the practical areas that the AFAR Lab’s research approaches are put for use include:
- Facial / bodily / nonverbal / multimodal artificial reaction generation
- Personality computing
- Depression analysis
- Assessment of affect in work-like settings
- Affective explainable human-AI interactions
- Adaptive virtual reality gaming for cognitive training
- Learning socially appropriate robo-waiter behaviours and robot actions
- Automatic analysis of robot facilitated taste-liking
- Robotic wellbeing coaching in the workplace
- Robotic coaches for practicing mindfulness
- Robotised mental wellbeing assessment in children
- Automatic inference of engagement in human-machine interactions
Projects
For more detail on the AFAR Lab’s most recent projects, see:
- Adaptive Robotic Emotional Intelligence For Well-being
- Continual Learning for Affective Computing and Robotics
- Robotised Assessment of Children's Mental Wellbeing
- Affective Intelligence for Humanoid Service Robotics
- User Research for Robotic Mental Well-Being Coaches
- Adaptive Robotic Coaches for Wellbeing
- Deep Learning for Facial AU, Depression and Personality Analysis
- Bias Analysis and Achieving Fairness for Affective Computing
- WorkingAge
Publications
Leader
Hatice Gunes
Leader of Affective Intelligence & Robotics LabMy current research vision is to embrace the challenges present in the area of health and empower the lives of people through creating socio-emotionally intelligent technology. This vision is currently supported by three new projects funded by prestigious and competitive grants via the WorkingAge Project funded by the EU H2020 Programme (2019–2021), the EPSRC Fellowship Programme (2019–2024) and the Turing Fellowship Programme (2019-2021).
Current Members (November 2023)
Guy Laban
Postdoctoral Research Associate - https://www.guylaban.com/Postdoctoral researcher working on the EPSRC ARoEQ Project
Micol Spitale
Postdoctoral Research Associate - https://micolspitale.com/Postdoctoral researcher working on the EPSRC ARoEQ Project
Jiaee Chong
PhD studentPhD student funded by the Alan Turing Institute
Minja Axelsson
CPGS Student - https://www.minjaaxelsson.com/I am a PhD student (2020 – ) working in the Affective Intelligence and Robotics Lab, under the supervision of Dr Hatice Gunes. My research focuses on creating robots for human wellbeing. I work together with experts from different disciplines (such as psychology and computing), as well as prospective users of such robots. My research interests include Human-Robot Interaction, Social Robotics, Affective Computing, Artificial Intelligence, Design Research, Participatory Design, and User Experience. I am funded by the Osk. Huttunen foundation and the EPSRC.
Nida Itrat Abbasi
CPGS studentI am a first year PhD student at the Computer Laboratory, University of Cambridge. I completed my masters in Biomedical Engineering from the National University of Singapore. My research interests include human-robot interaction, cognitive computing and artificial intelligence.
Ying Feng
Visiting PhD Student - https://yingfeng23.github.io/I am a diligent and determined third-year Digital Marketing Ph.D. student, studying for my doctoral degree at Institute for Digital Technologies, at Loughborough University, London campus. Currently I am a visiting PhD student at the AFAR lab, Department of Computer Science and Technology, University of Cambridge.
Weiling Du
MPhil student
Can Ekkazan
Intern
Garima Kankariya
Intern
Aditya Choudhary
InternPast Members
Alex Raymond
PhD StudentPhD student funded by the Royal Commission for the Exhibition 1851 Industrial Fellowship
Euodia Dodd
M.Phil studentMPhil student funded by DeepMind Cambridge Scholarship, University of Cambridge, Oct 2021 - Jun 2022
Abbas Khan
Research Assistant - https://kabbas570.github.io/Department of Archaeology, University of Cambridge. ML for analysing expressions in sculptures
Chaudhary Muhammad Aqdus Ilyas
Postdoc Research AssociatePostdoctoral researcher working on the WorkingAge Project
Indu P Bodala
Post-doctoral Research FellowI am a Postdoctoral Research Associate at the Department of Computer Science and Technology, University of Cambridge. I received her Ph.D. from NUS Graduate School of Integrative Sciences and Engineering at the National University of Singapore where I studied human attention and trust during human interactions with autonomous agents. My research interests include human-robot interaction, affective computing, machine learning and cognitive neuroscience.
Luke Geurdan
M.Phil studentI am an MPhil student in the Affective Intelligence and Robotics Lab, where I am focusing my MPhil thesis on combining continual learning and federated learning for personalized, privacy-preserving human-robot interaction. Previously, I graduated from the University of Missouri with degrees in computer science and psychology.
Millie McQuillin
M.Phil studentMy name is Millie and I am an MPhil student in the AFAR group. In my work I am most interested in using computer vision and machine learning techniques to improve existing methods social robotics and pro-social computing. I am a previous recipient of the Google Women Techmakers Scholarship, and am able to study at Cambridge thanks to the support of DeepMind. When I'm not working I can usually be found at the ice rink or reading a good book!
Samuil Stoychev
M.Phil studentHi! My name is Samuil. I have recently graduated from UCL with BSc Computer Science. I am currently studying towards an MPhil Advanced Computer Science here at Cambridge where I am researching resource efficiency in continual learning
Harsh Shah
Intern
Cheng Luo
InternContact
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