Dr Jamie A Ward

Jamie's interests include wearable computing, social neuroscience, and theatre. He is particularly interested in how wearable computing can help to capture and model human activity.

Staff details

Dr Jamie A Ward






j.ward (@gold.ac.uk)





Jamie is a lecturer in Machine Learning at Goldsmiths. His background encompasses wearable computing, social neuroscience, and theatre. His work is broadly concerned with how we can best use wearable sensing and machine learning as tools to help us capture, model, and understand real-world human activity and behaviour. As part of this effort, he draws on methods from theatre and performance as a way of obtaining close-to-real world data, developing the idea of using theatre as a laboratory.

He obtained his PhD from the Swiss Federal Institute of Technology (ETH), Zürich, Switzerland in 2006, and a joint degree in Computer Science and Electrical Engineering from the University of Edinburgh in 2000. Prior to joining Goldsmiths, Jamie was a post-doctoral researcher at University College London’s Institute of Cognitive Neuroscience, and at Lancaster University, where he was a Marie Curie Fellow.

Between academic positions he worked variously as a technology consultant, an analogue circuit designer, and as an actor in television, film, and theatre. 

Publications and research outputs


Falk, Patrick; Cañigueral, Roser; Ward, Jamie A and Hamilton, Antonia F de C. 2023. Head Nodding and Hand Coordination Across Dyads in Different Conversational Contexts. Journal of Nonverbal Behaviour, ISSN 0191-5886

Sun, Yanke; Greaves, Dwaynica A; Orgs, Guido; de C. Hamilton, Antonia F; Day, Sally and Ward, Jamie A. 2023. Using Wearable Sensors to Measure Interpersonal Synchrony in Actors and Audience Members During a Live Theatre Performance. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 7(1), 27. ISSN 2474-9567

Chen, Kanyu; Han, Jiawen; Baldauf, Holger; Wang, Ziyue; Chen, Dunya; Kato, Akira; Ward, Jamie A and Kunze, Kai. 2023. Affective Umbrella – A Wearable System to Visualize Heart and Electrodermal Activity, towards Emotion Regulation through Somaesthetic Appreciation. Proceedings 4th Augmented Humans International Conference 2023, Glasgow, UK (AHs2023), pp. 231-242.

Conference or Workshop Item

Hynds, Danny; Chernyshov, George; Zheng, Dingding; Uyama, Aoi; Li, Juling; Matsumoto, Kozue; Pogorzhelskiy, Michael; Kunze, Kai; Ward, Jamie A and Minamizawa, Kouta. 2024. 'Innermost Echoes: Integrating Real-Time Physiology into Live Music Performances'. In: Eighteenth International Conference on Tangible, Embedded, and Embodied Interaction (TEI ’24). Cork, Ireland 11–14 February 2024.

Eghtebas, Chloe; Liebald, Alexander; Pospelova, Maria; Manjunath, Ashika; Geheeb, Julian; Puspitasari, Norma; Ward, Jamie A and Klinker, Gudrun. 2023. 'An Experimental Video Conference Platform to Bridge the Gap Between Digital and In-Person Communication'. In: Adjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing & the 2023 ACM International Symposium on Wearable Computing (UbiComp/ISWC ’23 Adjunct). Cancun, Quintana Roo, Mexico 8-12 October 2023.

Henneberg, Maximilian; Eghtebas, Chloe; De Candido, Oliver; Kunze, Kai and Ward, Jamie A. 2023. 'Detecting an Offset-Adjusted Similarity Score Based on Duchenne Smiles'. In: CHI EA ’23: ACM CHI Conference on Human Factors in Computing Systems. Hamburg, Germany 23–28 April 2023.

Research Interests

Wearable computing, on-body sensing, activity recognition, social neuroscience, pattern analysis, and machine learning.