当前位置: X-MOL首页全球导师 国内导师 › 蒯曙光

个人简介

蒯曙光博士主要从事虚拟现实系统感知觉和人机交互研究,擅长使用数学和工程建模方法研究人类交互行为。曾以第一或通讯作者在Nature Neuroscience, Nature Human Behavior, Current Biology, Plos Biology, Journal of Neuroscience, Psychological Science国际心理学与神经科学杂志发表多篇的学术论文,蒯曙光博士先后主持了多个研究项目。研究工作受到国家自然科学基金优秀青年基金的资助等多个国家项目资助。 教育经历 2004.9-2009.7中国科学院神经科学研究所,博士 (期间随导师到北京师范大学认知神经科学与学习国家重点实验室学习) 2000.9-2004.6华东师范大学心理学学士(主修),计算机科学第二专业(辅修) 工作经历 2015.5-今 先后担任华东师范大学心理和认知科学学院,研究员,教授,视觉认知和虚拟现实应用实验室负责人,博士生导师 2012.9-2015.5 飞利浦研究院研究人员 2009.9-2012.8 英国伯明翰大学博士后,期间受玛丽居里学者计划基金资助

研究领域

基于虚拟现实社会交互研究 了解社会交互对于人类的社会活动至关重要。先前的研究发现具有社会意义的信息在建立社会互动中起着重要作用,但是对传统研究中却鲜有对这些线索的定量分析。为此我们使用了虚拟现实技术来创建社交环境,并通过心理物理学的方式突破了传统研究的限制,测量了人类的社交感知,这使得被试在社会交互中可以成为直接参与的互动者,而不仅仅是观察者。基于这些VR测量,我们提出了社交互动场模型(SIFM),SIFM可以帮助我们了解人类是如何在社会交互中产生这些规律性的智能行为并能帮助我们预测人类社交互动状态。 人类行走行为研究 在复杂的自然环境中绕开障碍物到达目标地点对于生物是一种基础能力。就人类而言,我们能够在日常生活中,例如在人流攒动的派对或商场,毫不费力地绕行静止和运动的人群。同时,作为社会动物,人类的行走行为受到了大量社会信息的影响。人类在行走过程中会避免与他人产生不必要的社会交互强度。我们通过虚拟现实技术构建复杂的社会情境,并记录被试的行走轨迹,探究人类行走路径规划和路径执行的规律。对人类行走行为规律的掌握对大型群体活动的安全预案制定、城市道路规划以及服务型机器人的设计有着重要的指导意义

近期论文

查看导师新发文章 (温馨提示:请注意重名现象,建议点开原文通过作者单位确认)

Deng, C.L., Sun, L., Zhou, C., & Kuai S.G. (2023). Dual-Gain Mode of Head-Gaze Interaction Improves the Efficiency of Object Positioning in a 3D Virtual Environment. International Journal of Human–Computer Interaction[PDF] Zhou, C., Miao, M. C., Chen, X. R., Hu, Y. F., Chang, Q., Yan, M. Y. & Kuai, S. G. (2022). Human-behaviour-based social locomotion model improves the humanization of social robots. Nature Machine Intelligence[PDF] 邓成龙, 耿鹏, & 蒯曙光. (2022). 三维虚拟空间中转头选中远离和靠近运动目标的操作特性差异. 心理学报[PDF] Han, M., Wang, X. M., & Kuai, S. G. (2022). Social rather than physical crowding reduces the required interpersonal distance in virtual environments. PsyCh Journal.[PDF] 邓成龙,赵铭,蒯曙光. (2022). 身体偏转对虚拟现实头控交互操作的影响. 人类工效学[PDF] Deng, C. L., Tian, C. Y., & Kuai, S. G. (2022). A combination of eye-gaze and head-gaze interactions improves efficiency and user experience in an object positioning task in virtual environments. Applied Ergonomics, 103, 103785.[PDF] 邓成龙,蒯曙光. (2021). 虚拟现实空间中角度量参数包含深度对放置任务操作时间的影响. 人类工效学[PDF] Tan, H., Peng, S. L., Zhu, C. P., You, Z., Miao, M. C., & Kuai, S. G. (2021). A long-lasting negative effect of COVID-19 pandemic on public sentiment: a full-year tracking of online public sentiment in mainland China. Journal of Medical Internet Rese[PDF] 沈靖,杨晓晴,王振宇,凌若蓝,蒯曙光. (2021). 虚拟现实技术在欺骗研究中的应用. 应用心理学[PDF] Kuai, S. G., Liang, Q., He, Y. Y., & Wu, H. N. (2020). Higher anxiety rating does not mean poor speech performance: dissociation of the neural mechanisms of anticipation and delivery of public speaking. Brain Imaging and Behavior, 1-10.[PDF] Kuai, S. G., Shan, Z. K. D., Chen, J., Xu, Z. X., Li, J. M., Field, D. T., & Li, L. (2020). Integration of motion and form cues for the perception of self-motion in the human brain. Journal of Neuroscience, 40(5), 1120-1132.[PDF] Zhao, Y., Kuai, S., Zanto, T. P., & Ku, Y. (2020). Neural Correlates Underlying the Precision of Visual Working Memory. Neuroscience, 425, 301-311.[PDF] Wu, H. N., Wang, X. M., Yu, L. K., Yuan, T., & Kuai, S. G. (2019). Rendering a virtual light source to seem like a realistic light source in an electronic display: A critical band of luminance gradients for the perception of self-luminosity. Displays[PDF] Deng, C. L., Geng, P., Hu, Y. F., & Kuai, S. G. (2019). Beyond Fitts’s Law: A Three-Phase Model Predicts Movement Time to Position an Object in an Immersive 3D Virtual Environment. Human factors, 61(6), 879-894.[PDF] Zhou, C., Han, M., Liang, Q., Hu, Y. F., & Kuai, S. G. (2019). A social interaction field model accurately identifies static and dynamic social groupings. Nature human behaviour, 3(8), 847-855.[PDF] Xu, Z. X., Chen, Y., & Kuai, S. G. (2018). The human visual system estimates angle features in an internal reference frame: A computational and psychophysical study. Journal of vision, 18(13), 10-10.[PDF] Safdar, M., Luo, M. R., Mughal, M. F., Kuai, S., Yang, Y., Fu, L., & Zhu, X. (2018). A neural response-based model to predict discomfort glare from luminance image. Lighting Research & Technology, 50(3), 416-428.[PDF] 李明英,吴惠宁,蒯曙光,张畅芯. (2017). 虚拟现实技术在执行功能评估中的应用. 心理科学进展[PDF] Kuai, S. G., Li, W., Yu, C., & Kourtzi, Z. (2017). Contour integration over time: psychophysical and fMRI evidence. Cerebral Cortex, 27(5), 3042-3051.[PDF] Christian, J., Goldstone, A., Kuai, S. G., Chin, W., Abrams, D., & Kourtzi, Z. (2015). Socio-cognitive profiles for visual learning in young and older adults. Frontiers in aging neuroscience, 7, 105.[PDF] Kuai, S. G., Levi, D., & Kourtzi, Z. (2013). Learning optimizes decision templates in the human visual cortex. Current Biology, 23(18), 1799-1804.[PDF] Kuai, S. G., & Kourtzi, Z. (2013). Learning to see, but not discriminate, visual forms is impaired in aging. Psychological science, 24(4), 412-422.[PDF] Zhang, J. Y., Kuai, S. G., Xiao, L. Q., Klein, S. A., Levi, D. M., & Yu, C. (2008). Stimulus coding rules for perceptual learning. PLoS biology, 6(8), e197.[PDF] Levi, D. M., Yu, C., Kuai, S. G., & Rislove, E. (2007). Global contour processing in amblyopia. Vision Research, 47(4), 512-524.[PDF] Kuai, S. G., Zhang, J. Y., Klein, S. A., Levi, D. M., & Yu, C. (2005). The essential role of stimulus temporal patterning in enabling perceptual learning. Nature Neuroscience, 8(11), 1497-1499.[PDF]

推荐链接
down
wechat
bug