Dr. Kun-Ying Li | Sustainable Engineering | Best Researcher Award

Dr. Kun-Ying Li | National Chin-Yi University of Technology | Taiwan

Dr. Kun-Ying Li is an accomplished researcher in sustainable engineering and intelligent manufacturing, focusing on low-carbon technologies and energy-efficient machine tools. His research encompasses ISO14064-1:2018 greenhouse gas inventory, industrial energy-saving methods, intelligent thermal error analysis, cooling optimization, multi-objective optimization, and precision machinery design. His work emphasizes the integration of reliability engineering, applied mathematics, smart manufacturing systems, and computer-assisted engineering within the framework of Industry 4.0. He has contributed to several industry-academic collaboration projects aimed at optimizing cooling systems for multi-axis machine tools and implementing carbon inventory strategies in manufacturing transformation programs. These projects have involved partnerships with precision machinery and metal manufacturing companies, supported by national funding agencies. His expertise extends to developing innovative approaches for reducing energy consumption, enhancing process reliability, and improving the performance of advanced machine tools. Through a combination of technical insight and practical application, his research supports the transition toward intelligent, sustainable, and high-efficiency production systems that align with global goals for carbon reduction and green industry innovation. He has 220 citations by 151 documents, 29 published documents, and an h-index of 9, reflecting his consistent research contributions and growing academic influence in the fields of precision engineering and green manufacturing.

Profiles: Scopus | Google Scholar | ORCID

Featured Publications

Liu, Y. C., Li, K. Y., & Tsai, Y. C. (2021). Spindle thermal error prediction based on LSTM deep learning for a CNC machine tool. Applied Sciences, 11(12), 5444.
Li, K. Y., Luo, W. J., & Wei, S. J. (2020). Machining accuracy enhancement of a machine tool by a cooling channel design for a built-in spindle. Applied Sciences, 10(11), 3991.
Hsieh, M. C., Maurya, S. N., Luo, W. J., Li, K. Y., Hao, L., & Bhuyar, P. (2022). Coolant volume prediction for spindle cooler with adaptive neuro-fuzzy inference system control method. Sensors & Materials, 34, 28.
Li, K. Y., Luo, W. J., Hong, X. H., Wei, S. J., & Tsai, P. H. (2020). Enhancement of machining accuracy utilizing varied cooling oil volume for machine tool spindle. IEEE Access, 8, 28988–29003.
Li, K. Y., Maurya, S. N., Lee, Y. H., Luo, W. J., Chen, C. N., & Wellid, I. (2023). Thermal deformation and economic analysis of a multi-object cooling system for spindles with varied coolant volume control. The International Journal of Advanced Manufacturing Technology, 126(3), 1807–1821.
Maurya, S. N., Li, K. Y., Luo, W. J., & Kao, S. Y. (2022). Effect of coolant temperature on the thermal compensation of a machine tool. Machines, 10(12), 1201.

Mr. Mohammad Alibabaei Shahraki | Structural Engineering | Best Researcher Award

Mr. Mohammad Alibabaei Shahraki | Technical and Vocational University | Iran

Mr. Mohammad Alibabaei Shahraki is a distinguished lecturer and researcher at the Technical and Vocational University in Tehran, Iran, specializing in civil engineering with a focus on earthquake engineering, structural dynamics, and structural design. Recognized for his exceptional academic achievements, he was the top student for 12 consecutive semesters and secured a single-digit rank in the national university entrance examination. His research excellence has been acknowledged with the title of Best Researcher in Chaharmahal and Bakhtiari Province, alongside the invention of two notable research innovations. Prof. Shahraki has made significant contributions to the field of structural control and seismic performance enhancement, including pioneering studies on multiple tuned mass dampers, elastoplastic-tuned mass damper-inerters, and the effectiveness of viscous dampers in steel frame structures, with his work published in prominent journals such as Soil Dynamics and Earthquake Engineering and Structures, and presented at international conferences on civil engineering, architecture, and urban planning. With a perfect GPA of 4.00 from Shahrekord University for his Master’s in Civil Engineering, he combines academic rigor with practical expertise, delivering high-quality teaching and research. His scholarly impact includes 60 citations across 44 documents, 4 published works, and an h-index of 2, reflecting his growing influence in earthquake-resistant structural design. Fluent in English, Prof. Shahraki actively engages with global research communities and maintains an ORCID profile to showcase his contributions.

Featured Publications

Shahraki, M. A., Kamgar, R., & Heidarzadeh, H. (2023). Damage-based design of multiple tuned mass dampers to improve the seismic performance of steel frame structures. Soil Dynamics and Earthquake Engineering, 173, 108062.

Shahraki, M. A., Kamgar, R., & Heidarzadeh, H. (2023). Assessing the seismic behavior of structures controlled with a novel elastoplastic-tuned mass damper inerter considering the effects of soil-structure interactions. Structures, 57, 105265.

Shahraki, M. A., & Chaleshtori, H. S. A. (2025). Comparative analysis of novel non-linear tuned mass damper inerter and traditional tuned mass dampers in steel shear frame structures. International Journal of Structural Stability and Dynamics.

Shahraki, M. A. (2025). Response mitigations of adjacent structure with MPTMD under real and stochastic excitations. Discover Geoscience, 3(47), 1-20.

Alibabaei Shahraki, M. (2025). Cloud drift optimization algorithm as a nature-inspired metaheuristic. Discover Computing, 28(1), 1-28.