Welcome, I am Jiakang
Hi, I am Jiakang Chen. I have a background in theoretical physics and machine learning, and I work at the intersection of physics and AI.
My current research at University College London develops physics-informed neural networks for complex-time saddle-point equations in strong-field physics. I am particularly interested in physics-informed machine learning, AI for scientific discovery, and physics-inspired computing.
My recent paper, “Physics-informed neural networks for solving saddle-point equations in strong-field physics with tailored fields,” has been accepted for publication in Physical Review Research. I also presented this work as a poster at Atto-FEL 2026.