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I am a Ph.D. candidate in the Department of Cognitive Science at UC San Diego, mentored by Dr. Doug Nitz. I am currently receiving training in developmental psychology in the Mind and Development Lab. I am affiliated with the Contextual Robotics Institute in the Computer Science and Engineering Department. I have a master's degree in Human-Computer Interaction and a bachelor's degree in Digital Art.

 

My research passionately delves into how emerging technologies—such as social robots, AR/VR, and telerepresentation—shape early social-cognitive development. I'm deeply fascinated by the social perception of robots, with a particular focus on their perceived mental states. 

Understanding parental attitudes toward children's robots

My ongoing projects explore the following questions using experimental designs: (preprints coming soon!)

  1. How do robot movements affect human perception and attitudes toward the robot?

  2. How do children reason about the visual perspectives of others?

  3. How do technologies affect children's judgment about reality?

Previous projects and peer-reviewed articles

Understanding parental attitudes toward children's robots

With the increasing prevalence of AI-powered robots, we explored how parents perceive using robots as storytellers through design fiction. Our findings indicate: (1) parents generally held positive but mixed attitudes toward children’s storytelling robots, seeing them as superior to screen-based technologies for story time; (2) some parents felt ambivalent due to the robots' potential adaptability and emotional expression, potentially impacting their adoption; and (3) the context of use, perceived agency, and perceived intelligence of these robots influenced parental acceptance.

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Designing a musical robot for low-income children's piano practicing

With children in low-income backgrounds often facing greater academic challenges compared to their peers in higher financial brackets, implementing musical training, like learning the piano, can help bridge this gap. We designed an affordable robot, named Itchy, Scratchy, for children to practice piano outside the classroom. Our prototype evaluation revealed that Itchy, Scratchy could serve as an economical, effective, and engaging musical instrument. We propose that robots for low-income children's piano practice may significantly narrow the disparity in musical education achievement among individuals from various socioeconomic backgrounds.

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Exploring user types and design opportunities of virtual reality pet games 

This project investigated the perceptions, motivations, and expectations of individuals engaging in pet-related games. Specifically, we explored how their emotional connection with real pets influences expectations for virtual animals in virtual reality (VR). Based on the findings from an online survey and an in-lab study, differences in perception, motivation, and expectations in virtual reality pet games were observed between players with and without real pets. In addition, we identified three user types that capture preferences and gameplay styles in VR pet games. These user types can inform the design of VR pet games.

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Investigating self-directed learning in Minecraft classrooms

Minecraft, an online multiplayer sandbox video game, is often utilized as a teaching tool for subjects ranging from digital literature to computer science. To comprehend the adoption of Minecraft in classrooms, we conducted interviews with teachers and students who had used Minecraft in an educational setting. The analysis revealed three key ways in which Minecraft enables and motivates students to work towards their own learning goals: the ability to customize context, engage in immersive stories, and assume roles in the virtual world. Drawing from these themes, we propose a set of design recommendations for online informal learning spaces.

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Teaching assistantship since 2019

  • Research methods: COGS 119 Programming for Experimental Research (MATLAB and Psychtoolbox) · COGS 118A Supervised Machine Learning Algorithms · COGS 118B. Intro. to Machine Learning · COGS 108 Data Science in Practice · COGS 18 Intro. to Python · COGS 14B Intro. to Statistical Analysis · COGS 14A Intro. to Research Methods · COGS 13 Field Methods: Studying Cognition in the Wild

  • UX design: COGS 187A Usability and Information Architecture · COGS 102C Cognitive Design · DSGN 100 Prototyping

  • Cognitive science/ Psychology: COGS 111 Beauty and the Brain· COGS 107A Neuroanatomy and Physiology · PSYC 104 Social Psychology · COSG 100 Cyborgs Now and in the Future · COGS 10 Cognitive Consequences of Technology

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