About Me

I’m Hongjie Jiang, a Ph.D. student in Applied Mathematics at Brown University. I received my B.S. in Mathematics from Peking University, graduating from the Applied Mathematics Honors Program.

During my undergraduate studies, I had the opportunity to work with Prof. Bin Dong, Prof. Liwei Wang, and Prof. Di Luo. These experiences shaped my interests in mathematical modeling, scientific computing, and machine learning.

My research interests lie broadly in scientific machine learning and AI for science, with a particular focus on machine learning methods for partial differential equations and scientific computing, including neural operators and physics-informed approaches. I am especially interested in developing accurate, efficient, and interpretable methods for scientific modeling, simulation, and inverse problems.

I enjoy combining mathematical rigor with computational tools and am particularly interested in bridging mathematical analysis, numerical computation, and modern machine learning. I am always open to discussions and collaborations. If you share similar interests or have ideas to exchange, please feel free to reach out.

You can find my CV for more details about my background and experience. For those interested in my personal interests and reflections outside academia, please visit this page.