I am a Ph.D. candidate in the Department of Cognitive Science at UC San Diego.
I am interested in how humans, including children, construct the meaning of symbolic representations, and how these insights may contribute to the advancement of socially aligned and trustworthy robotics and AI.
Research
-
How do humans utilize their own actions to acquire and refine symbolic meaning?
-
How do they reason about the behaviors of both human and nonhuman agents (e.g., robots)?
-
How can insights from human symbolic meaning construction inform the development of socially aligned and trustworthy robotics and AI?
To investigate these questions, I employ an interdisciplinary approach, integrating insights from embodied cognition and human development:
-
Behavioral experiments
-
Computational modeling
-
Mixed-methods
-
EEG
Action
Human/Robot
Meaning
Social/Cognitive
Using actions for symbolic learning
My PhD dissertation projects investigate how children engage with symbolic representations—through physical exploration, testing, or interaction—to clarify the meaning, authenticity, or referential status of these representations. I led a group of 20+ excellent undergraduate research assistants within the Mind and Development Lab.
Children's learning about others' visual perspectives
Three pre-registered experiments were conducted, with data collected over Zoom from 4- to 6-year-old children recruited through Children Helping Science (Lookit). Manuscript in preparation.
💵 This work is funded by the UCSD Sanford Institute for Empathy and Compassion.
🏆 This work received the UCSD Interdisciplinary Research Award.
Children's judgment of the reality status of objects
Two pre-registered experiments were conducted with data collected from 3- to 7-year-old children at a local science museum and preschools. Manuscript in preparation.
💵 This work is funded by the UCSD Senate Research Grant program.
Understanding the actions of artificial agents
In addition to my dissertation projects, I investigate how people interpret the actions of artificial agents to inform the design of robots that foster trust and social-cognitive alignment in real-world environments. I have a particular interest in utilizing computational models and EEG to gain insights into human cognition.
How do people reason about the behavior of robots during malfunctions?
EEG study.
💵 This work is funded by the UCSD Yankelovich Research Center.
How do robot movements shape human social attributions?
Two pre-registered online experiments. Manuscript in preparation.
🏆 SMPC’22 Student Research Award finalist.
What are parents’ beliefs about children's robots in the home?
Study 1. Frontiers in Robotics and AI (2021). [pdf]
Study 2: A longitudinal study with robot intervention in natural home environments, employing a mixed-methods approach (pre-posttest, daily logs, surveys, and interviews).
🏆 ICSR’24 Best Short Paper Award
How do humans perceive virtual agents in VR games?
Studied how real pet bonds shape expectations for VR animals. An online survey and lab study revealed differences in perception, motivation, and expectations between pet owners and non-owners, identifying three user types to guide the design of VR pet games.
How do humans perceive virtual agents in MMORPGs?
Carried out a thorough review of existing literature on flow theory, interactive drama, and emotion theories, and created a theoretical model that explains how emotions are triggered in massive multiplayer online role-playing games (MMORPGs).
🏆 Best Undergraduate Graduation Thesis
Teaching
-
As the Instructor of Record, I developed and launched a new Human–Robot Interaction course for the Psychology Department.
-
This course (PSYC 193L Human-robot interaction) explores human-robot interaction through the lenses of psychology and cognitive science, covering research on perception, social cognition, and the psychological effects of social robots, as well as the ethical considerations of robot design. Students will also develop the skills to write a research paper integrating course discussions and psychological research methods that match the guidelines offered on the B.S. Research Paper site.
-
-
As a teaching assistant, I have supported instruction in 17 courses：
Research methods and programming:
COGS 119 Programming for Experimental Research
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
COGS 9 Intro. to Data Science
Cognition and design:
COGS 187A Usability and Information Architecture
COGS 111 Beauty and the Brain
COGS 107A Neuroanatomy and Physiology
PSYC 104 Social Psychology
COGS 102C Cognitive Design
COSG 100 Cyborgs Now and in the Future
DSGN 100 Prototyping
COGS 10 Cognitive Consequences of Technology