Xianglin Huang

Name:  Xianglin Huang

Department of Mechanical, Robotics and Energy Engineering

Dongguk University-Seoul

30, Pildong-ro 1-gil, Jung-gu, Seoul, Korea, 04620

E-mail: xianglin.huang5@gmail.com

Biographical Information

• 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.

Academic Experience

• 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 

Research Experience

• 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

Teaching Experience

• 2019 - 2023 : Graduate Teaching Assistant, University of Manchester

Research Interests  

• Prognostics and health management (PHM)

• Artificial intelligence (AI) 

• Neuromorphic sensing

• Solid mechanics

• Constitutive modeling

Honors and Awards  

• UK Henry Lester Trust Grant (2022)

• UK Henry Lester Trust Grant (2021)

PUBLICATIONS-INTERNATIONAL JOURNAL/ COMMUNICATED INTERNATIONAL JOURNALS

1. X. Huang, Q.M. Li, Determination of dynamic flow stress equation based on discrete experimental data: Part 2... International Journal of Impact Engineering, 206 (2025) 105432.
   https://doi.org/10.1016/j.ijimpeng.2025.105432

2. X. Huang, Q.M. Li, Determination of dynamic flow stress equation based on discrete experimental data: Part 1... International Journal of Impact Engineering, 206 (2025) 105403.
   https://doi.org/10.1016/j.ijimpeng.2025.105403

3. H. Wei, X. Huang, et al., Multiscale modeling for the behavior of 3D angle-interlock woven composites. International Journal of Mechanical Sciences, 276 (2024) 109382.
   https://doi.org/10.1016/j.ijmecsci.2024.109382

4. X. Huang, Q.M. Li, The legitimacy of decoupled dynamic flow stress equations... International Journal of Impact Engineering, 173 (2023) 104453.
   https://doi.org/10.1016/j.ijimpeng.2022.104453