Erik Billing
Senior Lecturer in Informatics
School of Informatics
Room H104
I am a researcher at the Interaction Lab here at the University of Skövde. I’m currently spending most of my time the research synergy Virtual Ergonomics, funded by the Swedish Knowledge Foundation (KK). My primary research focus lies on cognitive modelling for human robot interaction. Over the last five years I've spent a lot of time within the EU funded project DREAM, developing robots used in therapy for children with autism spectrum disorder. I have also a big heart for robot learning from demonstration and wrote my PhD thesis on the topic, titled Cognition Rehearsed – Recognition and Reproduction of Demonstrated Behavior, presented January 2012. The thesis presents novel techniques for learning from human demonstration, inspired by several cognitive and neurocomputational models of learning.
Please also refer to my profiles at Google scholar, Mendeley, and Research Gate.
Research
Publications
Projects
2020
DHM2020: Proceedings of the 6th International Digital Human Modeling Symposium, August 31 – September 2, 2020
2020. Conference paper.
https://doi.org/10.3233/ATDE200010
PLoS ONE
2020. Article.
https://doi.org/10.1371/journal.pone.0236939
Human-Robot Interaction: Evaluation Methods and Their Standardization
2020. Chapter in book. https://doi.org/10.1007/978-3-030-42307-0_9
DHM2020: Proceedings of the 6th International Digital Human Modeling Symposium, August 31 – September 2, 2020
2020. Conference paper.
https://doi.org/10.3233/ATDE200040
2019
Proceedings of the 15th SweCog Conference
2019. Conference paper.
The second workshop on social robots in therapy and care in conjunction with the 14th ACM / IEEE International Conference on Human-Robot Interaction (HRI 2019), Daegu, Korea, March 11–14 2019
2019. Conference paper, poster.
Anticipation and Anticipatory Systems: Humans Meet Artificial Intelligence, Örebro, Sweden, June 10-13, 2019
2019. Conference paper, oral presentation with abstract.
IEEE Sensors Journal
2019. Article. https://doi.org/10.1109/JSEN.2018.2877662
IEEE robotics & automation magazine
2019. Article. https://doi.org/10.1109/MRA.2019.2904121