I am currently a Postdoctoral Research Fellow at the National University of Singapore (NUS) Centre for Trusted Internet and Community (CTIC). My research focuses on understanding how consumers perceive trust in digital environments and how these perceptions shape their behaviors.
Before joining CTIC, I developed a deep interest in leveraging machine learning to explore psychological phenomena. This led me to pursue a Ph.D. in Data Science at the Institute of Data Science, NUS in 2020. Under the mentorship of Assistant Professor Kokil Jaidka and Professor Mike Cheung, my doctoral research examined cognitive-affective constructs—such as appraisals and emotions—expressed in first-person autobiographical text and how these are perceived by other readers (third-person) in the context of consumer behavior. Grounded in psychological theories, I developed computational models of these constructs using methods from Natural Language Processing (NLP) and machine learning.
In addition to applied work, I have contributed to theoretical advancements in psychology. Collaborating with Assistant Professor Desmond Ong (my ex-advisor)— formerly at NUS and now at UT-Austin— we explored the theoretical foundations of emotions and published a meta-analysis on the relationships between cognitive appraisals and emotions in Psychological Bulletin.
My academic journey began at NUS, where I earned both my Bachelor’s and Master’s degrees in Social Science (Psychology) through the Concurrent Degree Programme (CDP). During this time, I worked under the guidance of Associate Professor Ryan Hong, investigating cognitive vulnerabilities that contribute to anxiety.
Ongoing research
- Developing computational models of language to uncover insights into affect, cognition, and behavior, grounded in psychological theory.
- Improving social-cognitive (e.g. Theory-of-Mind) and analogical reasoning in Large Language Models (LLMs)
- Investigating value alignment in LLMs through model steering techniques.
My works are primarily published in CS conferences with a computational social science track (EMNLP, ACL, ICWSM, AAAI). Broadly, I am passionate about two intersecting areas: using computational methods to better understand psychological phenomena expressed in text, and applying psychological principles to improve the design and capabilities of Artificial Intelligence (AI).
If you are interested in collaborating—whether it’s studying psychological constructs in language, applying psychology to advance machine learning, or engaging in theory-driven psychological research—please feel free to reach out to me at gerardyeo4 [at] gmail.com.