Shawn (Shuolin) Li

I develop physics-grounded, uncertainty-quantified models that integrate turbulence theory with generative machine learning to predict how Earth’s surface and climate extremes evolve under intensifying human pressures. Turbulence serves as the unifying framework of my research: it governs particle transport, shapes landscape morphodynamics, and modulates boundary-layer dynamics that influence the onset, intensity, and persistence of heat waves.

My research sits at the intersection of:

• Turbulence and hydrodynamics
• Heat transfer and data-center cooling
• Sediment transport and geomorphology
• Generative machine learning for probability distributions