Events

HCIIL BBL Speaker Series: Prompting Rich and Low-Burden Self-Tracking Through Multimodal Data Input

Event Start Date: Thursday, October 7, 2021 - 12:30 pm

Event End Date: Thursday, October 7, 2021 - 1:30 pm

Location: HBK2119 and on Zoom

Add to Calendar Thursday, October 7, 2021 12:30 pm Thursday, October 7, 2021 1:30 pm America/New York HCIIL BBL Speaker Series: Prompting Rich and Low-Burden Self-Tracking Through Multimodal Data Input

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Speaker: Yuhan Luo, PhD Candidate, College of Information Studies, University of Maryland Yuhan Luo

Abstract: Multimodal systems seek to support effective human-computer interaction leveraging people’s natural capabilities. While screen-based touch, keyboard, and mouse input have been the mainstream, we see the growing popularity of speech input. Inspired by speech’s fast, flexible, and expressive nature, I examine how speech input complements traditional touch input on smartphones in supporting self-tracking practices.

Bio: Yuhan Luo is a Ph.D. Candidate in Information Studies at University of Maryland College Park. Her research focuses on Human-Computer Interaction (HCI), Health Informatics, Personal Informatics, and Ubiquitous Computing. Yuhan is passionate about bringing positivity to individuals’ everyday health and well-being through supporting them to better capture and manage their personal health data. Toward this goal, she has designed and evaluated multimodal self-tracking systems such as mobile apps and Alexa skills. Before joining the Ph.D. program at UMD, Yuhan received her master’s degree in Information Science and Technology at Pennsylvania State University and her bachelor’s degree in Computer Science at Southeast University in China. More information can be found on her website: https://www.terpconnect.umd.edu/~yuhanluo/.

HBK2119 and on Zoom

HCIL Logo

Speaker: Yuhan Luo, PhD Candidate, College of Information Studies, University of Maryland Yuhan Luo

Abstract: Multimodal systems seek to support effective human-computer interaction leveraging people’s natural capabilities. While screen-based touch, keyboard, and mouse input have been the mainstream, we see the growing popularity of speech input. Inspired by speech’s fast, flexible, and expressive nature, I examine how speech input complements traditional touch input on smartphones in supporting self-tracking practices.

Bio: Yuhan Luo is a Ph.D. Candidate in Information Studies at University of Maryland College Park. Her research focuses on Human-Computer Interaction (HCI), Health Informatics, Personal Informatics, and Ubiquitous Computing. Yuhan is passionate about bringing positivity to individuals’ everyday health and well-being through supporting them to better capture and manage their personal health data. Toward this goal, she has designed and evaluated multimodal self-tracking systems such as mobile apps and Alexa skills. Before joining the Ph.D. program at UMD, Yuhan received her master’s degree in Information Science and Technology at Pennsylvania State University and her bachelor’s degree in Computer Science at Southeast University in China. More information can be found on her website: https://www.terpconnect.umd.edu/~yuhanluo/.

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