Lei Guan | Machine Learning | Research Excellence Award

Mr. Lei Guan | Machine Learning | Research Excellence Award

Director | China Academy of Safety Science and Technology | China

Lei Guan is a Director and Professor at the Risk Monitoring and Early Warning Center, China Academy of Safety Science and Technology, with expertise in risk monitoring, early warning systems, artificial intelligence, and industrial safety engineering. He holds a Bachelor’s degree in Materials Science and Master’s and Doctoral degrees in Mechanical Engineering with specialization in precision instruments and safety-related systems. He has led major national and ministerial research programs, directed key laboratories and professional committees, supervised graduate researchers, and provided technical leadership for large-scale industrial and governmental safety initiatives. His research focuses on intelligent work safety systems, industrial internet applications, digital twins, data-driven risk modeling, and emergency management, with sustained contributions through peer-reviewed publications, patents, and standards development. His scholarly impact is reflected in 18 citations, an h-index of 3, and 13 published articles.

Citation Metrics (Google Scholar)

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Featured Publications

Numerical simulation of the double pits stress concentration in a curved casing inner surface
W. Yan, L. Guan, Y. Xu, J.G. Deng – Advances in Mechanical Engineering, 9(1) (3 citations)

Safety monitoring and management system for fluid catalytic cracking (FCC) process
L. Fang, Z. Wu, L. Wei, R. Kang, L. Guan – International Conference on Information and Automation (3 citations)

Study on SVM-based Flame Recognition and Fire Warning for Cotton and Linen Warehouses
X. Zhao, S. Hao, L. Guan, Y. Wang, Q. Zhao, D. Lv – IEEE Conference on Advances in Electrical Engineering (2 citations)

Industrial Internet of Things (IIoT) Identity Resolution Techniques: A Review
C. Dai, H. Li, L. Guan, M. Chi – IEEE BigDataSecurity (1 citation)

Ms. Xiaohua Li | Machine Learning | Excellence in Research Award

Ms. Xiaohua Li | Machine Learning | Excellence in Research Award

Associate Professor | Shanghai Electric Power University | China

Dr. Li Xiaohua, a distinguished Professor at Sichuan University and leading expert in materials science and structural engineering, is renowned for advancing high-performance composite materials and sustainable structural systems. She holds advanced degrees in materials engineering with specialization in composite behavior and structural performance, complemented by extensive experience in academic leadership, project supervision, and collaborative research initiatives. Her professional portfolio includes directing major institutional projects, mentoring interdisciplinary teams, and contributing to engineering innovations that strengthen the reliability and resilience of modern structures. Dr. Li’s research focuses on composite structures, fire-resistant materials, mechanical behavior, and performance optimization, supported by 297 citations, 34 scholarly documents, and an h-index of 11, reflecting her growing global impact. She has authored influential publications, contributed to high-level research panels, and advanced knowledge dissemination through editorial responsibilities and membership in professional engineering societies. Recognized for excellence in research, innovation, and service, she also holds relevant professional certifications that underscore her commitment to scientific rigor and continued advancement in the engineering sciences.

Profile: Scopus

Featured Publications

Li Xiaohua*, Probabilistic forecasting of coal consumption for power plants under deep peak shaving conditions using Informer with DDPM-based uncertainty modeling. Int. J. Electr. Power Energy Syst., 2025.

Li Xiaohua*, Electromagnetic vibration characteristics of permanent magnet synchronous motors with segmented grain-oriented electrical steel teeth–yoke.

Li Xiaohua, Research on core loss prediction of low-frequency transformer based on Grey Wolf optimisation algorithm optimised Back Propagation neural network. IET Electr. Power Appl., 2025.

 



 

Zhang-Peng Tian | Data-Driven Decision Analysis | Best Researcher Award

Zhang-Peng Tian | Data-Driven Decision Analysis | Best Researcher Award

Associate professor | China University of Mining and Technology | China

Zhang-peng Tian, Ph.D., is an Associate Professor and Head of the Master’s Program in Management Science and Engineering at the School of Economics and Management, China University of Mining and Technology. He earned his Ph.D. and M.E. in Management Science and Engineering from Central South University and a B.E. in Electronic Commerce from Tianjin Chengjian University. Dr. Tian has extensive experience in teaching undergraduate and postgraduate courses, leading national research projects, and contributing as a principal investigator on multiple grants focused on decision-making theory, social network analysis, and data-driven consensus models. His research specializes in data-driven decision analysis, preference learning, and multi-criteria group decision-making, with over 40 publications in top international and Chinese journals, including IEEE Transactions on Fuzzy Systems, Information Fusion, and Applied Soft Computing. He is a council member of national academic associations, serves as a reviewer for leading journals such as Tourism Management, Decision Support Systems, and IEEE Transactions, and regularly participates in prestigious conferences. Dr. Tian has received numerous honors, including recognition for his excellent doctoral dissertation, national and provincial scholarships, and selection into Jiangsu Province’s Double Innovation Doctor program. His academic contributions reflect a commitment to advancing decision science and fostering innovation in information management and engineering applications, making him a distinguished candidate for the Best Researcher Award.

Profile: ORCID

Featured Publications

Tian Zhang-peng*, Xu Fu-xin, Ma Wei-min, Analysis of coalition stability based on graph model under power asymmetry. Syst. Eng. Theory Pract., 2024, 44(7), 2309-2324.

Tian Zhang-peng, Xu Fu-xin, Nie Ru-xin*, Wang Xiao-kang, Wang Jian-qiang, An adaptive consensus model for multi-criteria sorting under linguistic distribution group decision making considering decision-makers' attitudes. Inf. Fusion, 2024, 108, 102406.

Yang Yu, Tian Zhang-peng, Lin Jun*, Strategic outsourcing in reverse logistics: Neutrosophic integrated approach with a hierarchical and interactive quality function deployment. Appl. Soft Comput., 2024, 152, 111256.

Ma Wei-min, Gong Kai-xin*, Tian Zhang-peng, Heterogeneous large-scale group decision making with subgroup leaders: An application to the green supplier selection. J. Oper. Res. Soc., 2023, 74(6): 1570-1586.

Tian Zhang-peng, Liang He-ming, Nie Ru-xin*, Wang Xiao-kang, Wang Jian-qiang, Data-driven multi-criteria decision support method for electric vehicle selection. Comput. Ind. Eng., 2023, 177: 109061.

Tian Zhang-peng, Xu Fu-xin, Nie Ru-xin*, Wang Xiao-kang, Wang Jian-qiang, Linguistic single-valued neutrosophic multi-criteria group decision making based on personalized individual semantics and consensus. Informatica, 2023, 34(2): 387-413.

Tian Zhang-peng, Liang He-ming, Nie Ru-xin*, Wang Jian-qiang, An integrated multi-granular distributed linguistic decision support framework for low-carbon tourism attraction evaluation. Curr. Issues Tourism, 2023, 26(6): 977-1002.

Nie Ru-xin, Chin Kwai Sang, Tian Zhang-peng*, Wang Jian-qiang, Zhang Hong-yu, Exploring dynamic effects on classifying service quality attributes under the impacts of COVID-19 with evidence from online reviews. Int. J. Contemp. Hosp. Manage., 2023, 35(1): 159-185.

Wang Xiao-kang, Hou Wen-hui, Zhang Hong-yu, Wang Jian-qiang, Goh Mark, Tian Zhang-peng, Shen Kai-wen, KDE-OCSVM model using Kullback-Leibler divergence to detect anomalies in medical claims. Expert Syst. Appl., 2022, 200: 117056.