Wellcome, I am Jiakang

Hi👋, I am Jiakang. I have a background in theoretical physics and machine learning, and I’m currently exploring new computing paradigms at the intersection of physics and AI.

My MSci project on supergravity revealed to me the deep beauty of physics and the universe. Later, during my MSc in Machine Learning, I developed a neural network–based solver for partial differential equations (PDEs), which deepened my interest in physics-informed AI methods. These experiences showed me how powerful AI can be as a tool for advancing physics research — and how, in turn, physics can inspire new approaches in AI.

My research interests include physics-informed machine learning, AI for physics research, and physics-inspired computing.