Research Interests
- Multiphysics
modeling of soft matters –
Smart hydrogel in
bioMEMS & Biological cell in microscale field
- Machine learning based prediction – Physics-informed and data-driven analysis for correlation among 3D printing process parameters, microstructures and mechanical properties of additively manufactured part
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Development
of highly efficient numerical computational methodology
– Meshless & Multiscale algorithms
- Simulation
of sustainable energy –
Building energy efficiency & Fuel cell system
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Dynamics
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High-speed rotating shell & Composite materials structure
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More Information
- Industrial Collaborators: CAAS, Rolls-Royce, Makino, Emerson, Lloyd's Register, ABB, SUN Microsystems (Oracle), Sony, Philips, GE, DSO, JTC, A*STAR-ARTC
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One of the top 10 most-cited papers among work published in the journal between 1 January and 31 December 2023, Citation data from Clarivate Analytics, sent by John Wiley & Sons, on 19 March 2025. Zhixin Zhan (RF), Xiaofan He, Dingcheng Tang, Linwei Dang, Ao Li, Qianyu Xia, Filippo Berto and Hua Li (Corresponding author), Recent developments and future trends in fatigue life assessment of additively manufactured metals with particular emphasis on machine learning modelling, Fatigue & Fracture of Engineering Materials & Structures, Vol. 46, pp.44254464, 2023 (Invited Review Paper).
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