一、Basic information
Personal profile：Dr. YUAN Jun, associate professor. His research interests include energy systems modeling, shipping energy systems, computer simulation and optimization. In the past five years, he has published more than 20 SCI papers and held the National Natural Science Foundation Youth Program.
（一）Contact information
Email：yuanj@shmtu.edu.cn
Phone：+86 21 38283865
（二）Education
2013, Ph.D. degree in Industrial and Systems Engineering from National University of Singapore.
2008,B.E. degree in Industrial Engineering and Management from Shanghai Jiao Tong University.
二、Research
（一）Research area
Energy system modeling, shipping decarbonization, computer simulation and optimization.
Project
Gaussian process based ship energy system modeling and emission reduction measures optimization, National Natural Science Foundation Youth Program（71804108），2019-2021.
Publication
[1] Yuan J, Shi X, He J. LNG market liberalization and LNG transportation: Evaluation based on fleet size and composition model [J]. Applied Energy. 2024, 358:122657.
[2] Yuan J, Gu H, Nian V, Zhu L. Influence of system boundary conditions on the life cycle cost and carbon emissions of CO2 transport [J]. International Journal of Greenhouse Gas Control. 2023, 124:103847.
[3] Yuan J, Ng SH. An integrated method for simultaneous calibration and parameter selection in computer models [J]. ACM Transactions on Modeling and Computer Simulation (TOMACS). 2020, 30(1):1-23.
[4] Yuan J, Wang H, Ng SH, Nian V. Ship emission mitigation strategies choice under uncertainty [J]. Energies. 2020, 13(9):2213.
[5] Yuan J, Nian V, He J, Yan W. Cost-effectiveness analysis of energy efficiency measures for maritime shipping using a metamodel based approach with different data sources [J]. Energy. 2019, 189:116205.
[6] Yuan J, Nian V, Su B. Evaluation of cost-effective building retrofit strategies through soft-linking a metamodel-based Bayesian method and a life cycle cost assessment method [J]. Applied Energy. 2019, 253:113573.
三、Teaching
（一）Courses
Courses：Bayesian method and application；Renewable energy and shipping energy transition.