Interview with Professor Yi-Qin Gao

Our conversation ranged from the role of computational physics in understanding complex life and materials systems, to the impact of artificial intelligence (AI) on biophysics, to his personal scientific journey and advice for young researchers.This conversation with Professor Gao was profoundly inspiring to me.His ability to connect rigorous physical principles with the complexity of living systems, his vision of AI as both a scientific partner and a catalyst for cross-scale understanding, and his thoughtful reflections on mentorship and scientific growth all left a deep impression.I found his metaphors-the low-dimensional flow of life, the bamboo forest of modern education, the deep-andwide foundation required to plant a tree-which capture not only the intellectual landscape of modern science but also the human dimension of curiosity, resilience, and humility.Speaking with him reminded me why we pursue science in the first place: to explore the unknown with an open mind, to bridge disciplines in meaningful ways, and to inspire the next generation to explore further than we ever could.What follows is an edited transcript of that interview, incorporating both human and AI translation and editing, originally conducted in Mandarin.Editor-in-Chief: Professor Gao, thank you for speaking with us.To begin, from your perspective, what advantages does computational physics offer over traditional experimental methods in studying complex life and materials systems?Yi-Qin Gao: Thank you, Xiaosong.I am very happy to have this opportunity.This question really goes beyond "computational physics."From the broader viewpoint of physics, chemical physics, or physical chemistry, we are always asking: when we study complex living systems, or more generally, complex chemical systems, what can computation do that experiments alone cannot?These systems are intrinsically multi-scale in both space and time.They involve many