91原创

Biography

Juntao Huang is an assistant professor in the Department of Mathematical Sciences at the 91原创. He received his Ph.D. in applied mathematics in 2018 and dual bachelor's degrees in mathematics and engineering mechanics in 2013, all from Tsinghua University, China. He served as a faculty member at Texas Tech University from 2022 to 2025 and a visiting assistant professor at Michigan State University from 2018 to 2022.

Huang's research聽interests lie at the intersection of scientific computing, applied mathematics and data-driven modeling. His work focuses on the design, analysis and implementation of numerical methods for partial differential equations (PDEs), particularly hyperbolic systems and kinetic equations. A central theme of his research is the development of moment modeling frameworks, including moment-enhanced shallow water equations and machine-learning moment closures for radiative transfer and related multiscale systems. By integrating rigorous mathematical analysis with modern machine learning techniques, Huang seeks to build computational models that are both physically consistent and computationally efficient.

Beyond traditional PDE modeling, Huang is also engaged in multiscale modeling of soft matter systems. His recent work explores the mechanics of architected networks, combining discrete modeling and high performance computing to understand the structure-property relationships of advanced materials. Through these efforts, he aims to bridge mathematical theory, computational algorithms and real-world applications ranging from fluid dynamics to materials science.

Looking ahead, Huang is enthusiastic about fostering collaborations across mathematics, engineering and data science. He is passionate about mentoring students and contributing to a vibrant research community, while pushing the boundaries of scientific machine learning and multiscale modeling to address challenging problems with broad societal impact.