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Research

Research Themes

1. The Construction of Context We are all embedded in specific contexts—defined by where we live, who we interact with, and what we possess. We believe these contexts are not passive backgrounds but active forces that construct our social reality. Concepts like “success,” “genius,” or “community” are not static natural kinds; they are dynamic structures woven from continuous interactions. By applying structuralist principles, we identify the implicit binary oppositions that shape how individuals and society operate while seeking the critical middle points that define the true spectrum of how they work.

2. Recovering Continuity via Representation Learning When we force the world into boxes, we lose the signal. Our lab develops Representation Learning methods to bridge the gap between discrete data and continuous reality. We use advanced embedding techniques to capture the subtle, continuous nuances that traditional categories miss. This approach allows us to reverse-engineer social constructions, bringing the “grey areas” and “gradients” of human behavior back into focus.

3. Universal Patterns in Complex Systems We search for the invariants—the ubiquitous patterns that manifest across science, technology, and social systems. Whether in the evolution of knowledge networks or the dynamics of social polarization, we use Network Science to trace the fundamental structures that underpin these diverse domains. Our goal is to find the mathematical and structural commonalities that transcend disciplinary boundaries.