Lun Che

INTI International University — Malaysia

Materials Science · Physical Sciences

5h-index127citations18works4.72yr avg
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Research Topics

Hydrogen embrittlement and corrosion behaviors in metals(5), Microstructure and Mechanical Properties of Steels(3), Additive Manufacturing Materials and Processes(3), Machine Learning in Materials Science(3), Metal Alloys Wear and Properties(3)

Publications17 total

Applications of Machine Learning in High-Entropy Alloys: Phase Prediction, Performance Optimization, and Compositional Space Exploration
Metals·2025· 1 citedOpen Access
Accelerating Bayesian inference of structural damage detection based on physics-guided CNN and zero-shot transfer learning
Structural Health Monitoring·2025
The necessity of multimodal feedback for learning effective pedagogical policies with reinforcement learning
Scientific Reports·2025Open Access
Development of an Age-sensitive SET* Index and predictive thermal sensation model for shopping malls in severe cold regions
Building and Environment·2025
Multi-Modality Sheep Face Recognition Based on Deep Learning
Animals·2025· 2 citedOpen Access
Interior luminous environment for the elderly: Recommended values of lighting parameters and comfort discriminant model
Building and Environment·2025· 5 cited
Machine Learning-Assisted Design of Strength-Ductility Synergy in Co-Cr-Ni-Al-Ti Medium-Entropy Alloys: Integration of Ultralarge Heterostructures and High-Density Precipitates
SSRN Electronic Journal·2025Open Access
Clear:Consistent Language Extraction and Retrieval Framework for Scientific Literature on Alloys
SSRN Electronic Journal·2025Open Access
An automatic segmentation and quantification method for austenite and ferrite phases in duplex stainless steel based on deep learning
Journal of Materials Chemistry A·2024· 4 cited
A Cycle Ride to HDR: Semantics Aware Self-Supervised Framework for Unpaired LDR-to-HDR Image Reconstruction
arXiv (Cornell University)·2024Open Access
The influence of annealing temperature on the microstructure and mechanical properties of Fe-0.52 C-11Mn-5.14Al-1Cr lightweight steel
Materials Today Communications·2024· 7 citedOpen Access
Deep alloys: Metal materials empowered by deep learning
Materials Science in Semiconductor Processing·2024· 18 cited
Machine learning guided BCC or FCC phase prediction in high entropy alloys
Journal of Materials Research and Technology·2024· 28 citedOpen Access
Composition design and optimization of Fe–C–Mn–Al steel based on machine learning
Physical Chemistry Chemical Physics·2024· 5 cited
The Influence of Annealing Temperature on the Microstructure and Mechanical Properties of Fe-0.52c-11mn-5.14al-1cr Lightweight Steel
SSRN Electronic Journal·2024· 1 citedOpen Access
Deep learning in alloy material microstructures: Application and prospects
Materials Today Communications·2023· 21 cited
An Automatic Captioning System for Telemedicine
2006· 31 cited

Frequent Co-authors

Meiling Ge(6), Tianyu Si(6), Feng Zhao(6), Kaiyuan Zheng(5), Kaiyuan Zheng(5), Zhongping He(4), Zhongping He(4), Xiaotian Xu(4), Yanlin He(4), Hong Cheng(3), Xiaotian Xu(3), Hong Cheng(3), Lijuan Wang(2), Hua Fu(2), Wentao Wu(2), Zhijiang Chen(2), Mingxiao Ma(2), Xiaomeng Si(2), Jiang An(2), Chen Du(2)