Lin Lin

Harbin Institute of Technology, Xiamen University, Waseda University

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About

Lin Lin is a versatile researcher whose work spans intelligent fault diagnostics, cultural heritage robotics, and evolutionary automation systems. Most prominently, Lin has made significant strides in machine learning-based industrial diagnostics, with a 2023 paper on Feature-level SMOTE earning 84 citations — a remarkable achievement demonstrating the work's broad influence in the engineering community. This contribution addressed a critical challenge in fault diagnosis of gas turbines: the scarcity of fault samples in real-world datasets. By augmenting fault samples within a learnable feature space, Lin's approach meaningfully advanced imbalanced learning methodologies for industrial applications. Beyond industrial diagnostics, Lin has shown a rare breadth of interdisciplinary curiosity. The HinHRob project represents a thoughtful intersection of robotics and cultural preservation, developing a performance robot capable of embodying China's thousand-year-old glove puppetry tradition — an innovative effort to safeguard intangible cultural heritage through technology. Earlier work on evolutionary techniques for automation reflects Lin's long-standing engagement with intelligent systems and optimization. Across these diverse domains, Lin demonstrates a consistent commitment to solving real-world problems through creative computational approaches, making their research portfolio both technically rigorous and culturally meaningful.