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

Published on by Electrical Engineering

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.

Kang Liu | Structural Engineering | Best Researcher Award

Published on by Electrical Engineering

Kang Liu | Structural Engineering | Best Researcher Award

Associate Professor | Shandong Agricultural University | China

Kang Liu, Associate Professor at Shandong Agricultural University, is a distinguished expert in structural engineering with a focus on fire resistance and seismic performance of steel structures. He earned his Ph.D. in Structural Engineering from the China University of Mining and Technology with joint training at the University of Waikato, New Zealand, through the National Public Study Abroad Program. Dr. Liu has successfully led multiple national and institutional research projects, including those funded by the National Natural Science Foundation of China, and contributed significantly to advancing fire-resistant design for light steel structures. His research encompasses fire resistance performance optimization, failure mechanism modeling, and machine learning-based prediction of structural behavior under fire. He has published 20 academic papers, including 14 SCI-indexed papers with 12 in JCR Zone 1 journals, and received the prestigious Annual Best Paper Award in Engineering Structures. Dr. Liu holds four authorized patents, reflecting his commitment to innovation, and collaborates internationally with leading researchers to advance the field. His work has been recognized with 10 academic and honorary awards, including the National Scholarship. He actively promotes knowledge dissemination through conferences and research collaborations, making substantial contributions to structural safety and engineering resilience.

Profile: ORCID

Featured Publications

Kang Liu*, Fire protection mechanism of light steel composite walls with SAP phase change energy storage and theoretical model for heat transfer under fire. Eng. Struct., Accepted.

Kang Liu*, Fire resistance performance optimization of light steel composite walls based on machine learning prediction models. Thin-Walled Struct., 2024, 5(2), 101456.

Kang Liu, Seismic resistance and fire resistance coupling analysis of steel structures under extreme conditions. J. Build. Eng., 2024, 6(1), 112034.

Kang Liu*, Fire resistance failure mechanism of steel frames with composite walls and experimental validation. Constr. Build. Mater., 2023, 4(3), 214589.

Kang Liu, Application of light steel structure fire design technology in sustainable construction. J. Constr. Steel Res., 2023, 8(2), 103945.