This virtual seminar series invites presentations related to one of 3 themes:
Challenges facing psychological science – including replication crisis, limited generalizability, fragmentation, and other foundational concerns.
Innovative approaches to addressing these challenges – covering existing and potential solutions, whether methodological, conceptual, or institutional.
Empirical work employing these innovative approaches – featuring research that puts the approaches outlined in Theme 2 into practice.
This event is organized by Liqiang Huang (see his motivation) on behalf of the Department of Psychology at The Chinese University of Hong Kong, with the help of the following co-organizers (in alphabetical order):
Time: 9:00 am (Hong Kong time, UTC+8), Saturday, October 17, 2026
Zoom: https://cuhk.zoom.us/j/95239400686
Title: Cognitive Mechanisms of Discovery
Abstract: To understand and navigate our world, both individuals and scientific communities create simplifying representations, such as concepts and theories. How do we construct useful representations from our experiences, and how do we use these representations to guide our learning? In this talk, I discuss empirical research on the mechanisms of human concept learning, highlighting the ease with which we adopt new, even arbitrary, conceptualizations. I illustrate how these acquired concepts shape the way we perceive and explore the world. For example, I show that our perception of objects becomes biased by our conceptual needs and our knowledge about these objects. I suggest that similar mechanisms are at play when scientific conceptualizations, such as the DSM in psychopathology and the periodic table in chemistry, guide scientific exploration. Then, I discuss the double-edged nature of theory-guided discovery: although conceptualizations can efficiently steer us towards new experiences that further refine our knowledge, they can also lead our exploration astray. I present a computational model of scientific discovery in which agents conduct experiments, build theories, and share results to advance collective understanding of the world. The model reveals that when new experiments are guided by existing theoretical frameworks, scientific communities risk missing important aspects of the world not yet captured by their theories. I conclude by reviewing our current and future research that integrates cognitive psychology, machine learning, and philosophy of science to enhance our understanding of how theories and observations can inform each other to support—rather than hinder—human learning and scientific progress.Time: 9:00 pm (Hong Kong time, UTC+8), Saturday, October 31, 2026
Zoom: https://cuhk.zoom.us/j/91237375512
Title: Integrative Social Science
Abstract: The dominant paradigm in experimental social and behavioral science treats experiments as tests of theory, assuming that theories generalize beyond the specific conditions of any single study. Under this view, scientific knowledge advances one experiment at a time, and integration across findings is left to the publication process. In this talk, I will argue that such integration often happens inefficiently, or not at all. I outline an alternative approach that inverts the usual sequence of reasoning, starting first with the question of generalization (“over what domains or situations do we want claims to hold?”), then conducting the relevant experiments and analysis, and only then interpreting the results in terms of existing (or new) theory. I illustrate this approach with examples from ongoing work on collaboration and cooperation.Time: 9:00 pm (Hong Kong time, UTC+8), Saturday, November 14, 2026
Zoom: https://cuhk.zoom.us/j/92717837375
Title: To be confirmed
Abstract: To be confirmedTime: 10:00pm (Hong Kong time, UTC+8), Saturday, December 5, 2026
Zoom: https://cuhk.zoom.us/j/99593360722
Title: To be confirmed
Abstract: To be confirmed