Gerard Chung
Hi! I study
About
I study how social workers use technology and AI. My research focuses on how digital social work practice can be developed and how social workers can use text to engage youths and other service users. I practiced previously as a social worker in a family service center. I hold a PhD from UNC-Chapel Hill School of Social Work and am an Assistant Professor at NUS. I lead the SWAT Lab.
Collaborate
I’m always interested in connecting with social workers, researchers, and students who share similar research interests.
For students: I’m happy to discuss ideas for Honors thesis projects. I also have Undergraduate Research Opportunities (UROP) available.
Feel free to reach out via email!
Latest Papers
- May '26 Adverse childhood experiences and the well-being of young workers: exploring the longitudinal impact on health and work-related functioning [Community, Work & Family]
- May '26 Technological Attitudes, Devices, and Skills at Work and at Home [link]
- Apr '26 More equitable preconception health: paternal life course opportunities for better pregnancy, child, and family outcomes [The Lancet]
- Mar '26 “Clicking without understanding”: A mixed-methods analysis of user agreements in digital mental health services [International Journal of Medical Informatics]
- Jun '26 What makes text-based online chat work? Communication features of effective chat helpers’ responses to chat users [Counselling and Psychotherapy Research]
Selected News
- Jul '26 Awarded a NUS Teaching Enhancement Grant ($29,500) to evaluate the AI-Vatar Role Playing Tool — a multi-school collaboration with Nursing and Medicine.
- Jun '26 Presented our paper on ritualizing the use of LLM role-playing bots for simulated learning in social work at the APISWEA International Conference on AI and Innovation for Social Work in Macau.
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Jan '26
Awarded grant to work with Nataliya Thell from LUND to research on digital social work.
Our new paper submitted "Worker Skills Associated with Outcomes in Suicidal-related Youth Chat Sessions" [preprint]