Hi, I’m Liwei Hu (胡立伟).

I’m an applied mathematician working on inverse problems and scientific computing. I develop computational methods that integrate physical models, data, and prior information for interpretable and reliable inference, with current applications to Earth systems. A central theme of my research is the incorporation of physically meaningful and problem-specific structure into inverse formulations. I am also extending this perspective toward uncertainty quantification in inverse problems governed by complex physical systems.

I’m currently in the final year of my PhD in Applied Mathematics at the University of Bologna, Italy, where I previously earned my B.S. and M.S. in Mathematics.

In my doctoral research, I use landslide thickness estimation as a first major Earth-system testbed for developing structure-aware inverse methods. Specifically, I develop regularization frameworks that incorporate kinematic and geological structure to infer landslide thickness and subsurface geometry from indirect surface deformation measurements. This work combines mathematical regularization design with physically interpretable constraints and validation on real-world data. It has also led to interdisciplinary collaborations and research visits to UC Berkeley and Case Western Reserve University, where I engaged with complementary geoscientific and computational perspectives.

My long-term research goal is to develop mathematically rigorous and computationally scalable inverse methods that exploit and preserve physically meaningful structure, while quantifying uncertainty in data, models, and inferred parameters. I aim to use challenging Earth-system problems and real-world data to drive methodological advances in scientific inference.