Department of Mechanical, Robotics and Energy Engineering Dongguk University-Seoul 30, Pildong-ro 1-gil, Jung-gu, Seoul, Korea, 04620

Dr. Xianglin Huang is a Research Professor at Dongguk University and a Postdoctoral Researcher at the InnoCORE PRISM-AI Center, Korea Advanced Institute of Science and Technology (KAIST). He received his Ph.D. in Mechanical Engineering from the University of Manchester (2024), an M.Eng. from Harbin Institute of Technology (2017), and a B.Eng. from the Civil Aviation University of China (2014).

During his Ph.D., he focused on modeling the mechanical behavior of engineering materials, including validation of constitutive equations and the development of data-driven approaches to describe material response under complex loading conditions. His earlier research included solid mechanics, composite materials, and multiscale modeling of advanced structures.

Currently, his work explores the use of artificial intelligence for prognostics and health management (PHM) of energy systems, with emphasis on data-driven approaches for condition monitoring, reliability improvement, and life prediction.

2025.10 - currently Postdoctoral Researcher InnoCORE PRISM-AI Center, KAIST, South Korea
2025.05 - 2025.08 Research Associate (Part-time) Zhejiang University
2019.07 - 2024.12 Ph.D. in Mechanical Engineering University of Manchester
2015.09 - 2017.07 M.Eng Harbin Institute of Technology
2010.09 - 2014.07 B.Eng Civil Aviation University of China

2023 - 2025 : Failure mechanisms of batteries under complex loading
2023 - 2025 : Machine learning-based methods for battery health assessment under complex loading
2023 - 2025 : Multiscale modeling of advanced composites under complex loading
2022 - 2025 : Constitutive modeling and performance prediction of engineering materials under complex loading
2015 - 2017 : Structural response of lightweight sandwich structures under complex loading

2019 - 2023 : Graduate Teaching Assistant, University of Manchester

Prognostics and health management (PHM);
Artificial intelligence (AI);
Neuromorphic sensing;
Solid mechanics;
Constitutive modeling.

UK Henry Lester Trust Grant (2022)
UK Henry Lester Trust Grant (2021)