My research investigates how lexical and semantic knowledge is represented, accessed, and reorganized, and how these processes relate to broader aspects of cognition. I examine these questions across languages and cultures by combining behavioral experiments with computational and network-based methods.
Psycholinguistics asks how language is represented, understood, and produced in the mind. My interests span the field broadly, including comprehension, production, learning, memory, and the cognitive processes that make everyday language use possible.
Most people in the world use more than one language. My research explores how these languages coexist and interact, and how proficiency, immersion, language use, and individual differences shape multilingual experience over time.
How are words and concepts represented, and how do their meanings become available? I study semantic similarity, concreteness, lexical associations, and translation equivalents to understand how meaning is organized within and across languages.
Using more than one language requires constant selection and adaptation. My research examines how speakers manage competing languages, switch between them, and adjust control in response to proficiency, context, task demands, and incoming information.
Words and concepts form richly connected systems rather than isolated entries. Using network science, I examine how the structure of these systems supports efficient processing and changes across individuals, languages, learning histories, and linguistic environments.
Language, cognition, and emotion continually shape one another and are central to human experience. My research explores this interplay, asking how language influences thought and feeling, and how emotional and cognitive processes, in turn, shape language.
AI is changing the conditions under which teaching and learning take place. Careful research is needed to understand how these tools should be designed, when they improve learning, whom they benefit, and where their limitations lie.
AI offers new ways to investigate meaning, reasoning, creativity, and knowledge. Comparing human and artificial systems can reveal shared patterns, important differences, and new insights into both the possibilities of machines and the nature of human cognition.
Language and culture develop in close interaction, shaping how people understand meaning, emotion, and experience. My research examines this relationship across communities, while separating cultural influences from linguistic differences and individual variation.
EVOLVE: Examining Valence-mOduLated Variation of Emotion Concepts Across Cultures
Do speakers of different languages carve up the emotional world in the same way? This project asks whether how pleasant or unpleasant a feeling is changes how consistently its concept travels across cultures.
Translations: Psycholinguistic, Social Semiotic, Neuroanatomical, Health Technological and Psychological Perspectives on ‘Voice Hearing’
Hearing a voice that nobody else can hear gets described very differently depending on who is asking. This CityUHK–Exeter collaboration puts psycholinguistics, social semiotics, neuroanatomy, health technology and psychology to work on the same experience, to see what each perspective can and cannot capture.
MODERA: Moderation and Optimization of Discussions with Enhanced Reasoning AI
Running a good group discussion is one of the hardest things to do in a large class. This project builds and tests an AI moderator that keeps a discussion on track and pushes students to reason further, and asks when that support genuinely helps them learn.
My research uses a combination of behavioral and computational methods.
I design behavioral experiments to investigate lexical-semantic processing, language production, and their relationships with broader cognitive processes.
I use graph-theoretic methods to analyze semantic networks derived from behavioral and linguistic data and to examine how their organization varies across individuals, languages, and experiences.
I use computational and distributional semantic models to quantify relationships between concepts, characterize patterns in linguistic data, and generate predictions about human behavior.
Data, stimuli, materials, and analysis code from my studies are available on the Open Science Framework, enabling others to reproduce or extend the work. Each paper links to its project page, while all publicly available resources are collected in my OSF profile.