Pai Yun Suen

Pai Yun Suen

Research Fellow

Dr. Yun Suen Pai is currently a Research Fellow at the Empathic Computing Laboratory (ECL), University of Auckland, directed by Prof. Mark Billinghurst. He received his Masters degree in Engineering Science on 2015 at the University of Malaya, Malaysia. He then completed his PhD from the Keio University Graduate School of Media Design, Yokohama, Japan in 2018 (Supervised by Prof. Kai Kunze), before continuing to be a researcher there for an additional 6 months.

His research interests includes the effects of augmented, virtual and mixed reality towards human perception, behavior, and physiological state. He has collaborated with several companies, including AirBus Malaysia, Fujitsu Design, NTT Media Intelligence Laboratory, Ignition Point, CSIRO and Google in several research areas, including haptics in AR, vision augmentation, VR navigation, and the use of machine learning for novel input and interactions.

Publications:
Gupta, K., Hajika, R., Pai, Y. S., Duenser, A., Lochner, M., & Billinghurst, M. (2020, March). Measuring Human Trust in a Virtual Assistant using Physiological Sensing in Virtual Reality. To appear in 2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR) IEEE.

Hajika, R., Gupta, K., Sasikumar, P., & Pai, Y. S. (2019, November). HyperDrum: Interactive Synchronous Drumming in Virtual Reality using Everyday Objects. In SIGGRAPH Asia 2019 XR (pp. 15-16). ACM.

Gupta, K., Hajika, R., Pai, Y. S., Duenser, A., Lochner, M., & Billinghurst, M. (2019, November). In AI We Trust: Investigating the Relationship between Biosignals, Trust and Cognitive Load in VR. In 25th ACM Symposium on Virtual Reality Software and Technology (p. 33). ACM.​

Publications

  • Measuring Human Trust in a Virtual Assistant using Physiological Sensing in Virtual Reality
    Kunal Gupta, Ryo Hajika, Yun Suen Pai, Andreas Duenser, Martin Lochner, Mark Billinghurst

    K. Gupta, R. Hajika, Y. S. Pai, A. Duenser, M. Lochner and M. Billinghurst, "Measuring Human Trust in a Virtual Assistant using Physiological Sensing in Virtual Reality," 2020 IEEE Conference on Virtual Reality and 3D User Interfaces (VR), Atlanta, GA, USA, 2020, pp. 756-765, doi: 10.1109/VR46266.2020.1581313729558.

    @inproceedings{gupta2020measuring,
    title={Measuring Human Trust in a Virtual Assistant using Physiological Sensing in Virtual Reality},
    author={Gupta, Kunal and Hajika, Ryo and Pai, Yun Suen and Duenser, Andreas and Lochner, Martin and Billinghurst, Mark},
    booktitle={2020 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)},
    pages={756--765},
    year={2020},
    organization={IEEE}
    }
    With the advancement of Artificial Intelligence technology to make smart devices, understanding how humans develop trust in virtual agents is emerging as a critical research field. Through our research, we report on a novel methodology to investigate user’s trust in auditory assistance in a Virtual Reality (VR) based search task, under both high and low cognitive load and under varying levels of agent accuracy. We collected physiological sensor data such as electroencephalography (EEG), galvanic skin response (GSR), and heart-rate variability (HRV), subjective data through questionnaire such as System Trust Scale (STS), Subjective Mental Effort Questionnaire (SMEQ) and NASA-TLX. We also collected a behavioral measure of trust (congruency of users’ head motion in response to valid/ invalid verbal advice from the agent). Our results indicate that our custom VR environment enables researchers to measure and understand human trust in virtual agents using the matrices, and both cognitive load and agent accuracy play an important role in trust formation. We discuss the implications of the research and directions for future work.