Dr. YAN Ran (Angel, [鄢然])'s Homepage
Ran Yan
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Dr. Ran Yan [鄢然]

Email: ran.yan(at)ntu(dot)edu(dot)sg or angel-ran(dot)yan(at)connect(dot)polyu(dot)hk

Hello! I am currently an assistant professor at the School of Civil and Environmental Engineering (CEE) at Nanyang Technological University (NTU), Singapore, since March 2023. Before joining NTU, I was a research assistant professor at the Department of Logistics and Maritime Studies at The Hong Kong Polytechnic University from May 2022 to March 2023. I am also the PI of MARINA Lab hosted by CEE, NTU.
My research interest includes data analytics in maritime studies, big data in maritime transport, green-shipping management, maritime risk management, and port and shipping optimization. If you are interested in pursuing a PhD degree or working as a post-doc/research assistant with me, please contact me via email. I have published more than 30 SCI/SSCI indexed research papers in top-tier transportation maritime, and energy journals, such as Transportation Research Part B/C/D/E, IEEE Transactions on Intelligent Vehicles, Computers and Operations Research, Computers & Industrial Engineering, Applied Energy, Journal of Cleaner Production, Maritime Policy & Management, Transport Policy, Advanced Engineering Informatics, Ocean & coastal management, and Ocean Engineering.
I serve as an Editorial Board Member of Cleaner Logistics and Supply Chain, guest editors of a number of special issues and referees for a number of transportation and maritime journals.
I also have certain experience in supervising PhD and master students and research assistants. I am currently the chief supervisor of one PhD student and one research fellow, and the co-supervisor of two PhD students and a number of CSC visiting students.

Google Scholar  /  ResearchGate  /  Academic Profile in NTU  /  LinkedIn of MARINA Lab

Academic Positions

  • Assistant Professor, March 2023 - present, School of Civil and Environmental Engineering, Nanyang Technological University (Singapore)
  • Research Assistant Professor, May 2022 - March 2023, Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University (Hong Kong, China)

News

  • I am always looking for self-motivated PhD students with full scholarship/partial scholarship in maritime transport management and data analytics/artificial intelligence in maritime transportation for January or August intake.
  • I am looking for multiple research fellows in maritime studies with flexible start time.
  • Please visit Openings for more details.

  • The electronic version of our new book Machine Learning and Data Analytics in Maritime Studies: Models, Algorithms, and Applications with Prof. Shuaian Wang are aviable at The IET Digital Library.
  • The printed version will be available in March 2023 and can be bought from The IET Shop.
  • Education

    • Doctor of Philosophy (PhD), 2022, Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University
    • Master of Philosophy (MPhil), 2020, Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University
    • Bachelor of Science (BSc) in Computer Science, 2018, Faculty of Internet of Things, Hohai University

    Grants

    • COSCO Shipping Technology Co., Ltd Industrial Fund (PI): Ship Fuel Consumption Estimation Based on Shipping Big Data and Artificial Intelligence: Models and Applications [SGD 56,316, May 2024 to April 2025]
    • NTU-Imperial Collaboration Fund 2023/24 (PI): Transport and logistics of tomorrow: Towards a smarter, greener, and more resilient future [SGD 11,000, March 2023 to July 2025]
    • MOE AcRF Tier 1 Seed Fund (PI): Prediction of vessel arrival and turnaround time at port by artificial intelligence: Models and applications [SGD 100,000, December 2023 to December 2026]
    • MOE AcRF Tier 1 (PI): Optimization of ship sailing speed profile based on dynamic meteorological data: Model, algorithm, and application [SGD 90,000, November 2023 to October 2025]
    • NTU Start-up Grant (PI): Maximizing weighted inspection benefits in port state control based on prescriptive analytics: Models, methods, and applications [SGD 175,000, April 2023 to March 2026]
    • PolyU Start-up Fund for RAPs (PI): Improving port state control efficiency by transfer learning approaches [HKD 250,000, July 2022 to March 2023]

    Research and Selected Publications

    I'm interested in developing and applying innovative and efficient data analytics models to improve the efficiency of port and shipping activities. My main research topics include port inspection by port state control, green shipping management, and general port and shipping management.

    Book

    • Machine Learning and Data Analytics in Maritime Studies: Models, Algorithms and Applications, with Prof. Shuaian Wang, published by the Institution of Engineering and Technology (IET) Publisher in March 2023. Electronic version available from The IET Shop. Printed version can be brought from The IET sites.

    Note#: Research student or research assistant assisting in supervising/supervising.

    Topic 1: Port state control

    1. Yan R., Liu Y., Wang S., 2024. A data-driven optimization approach to improving maritime transport efficiency. Transportation Research Part B: Methodological 180, 102887..

    2. Tian X.#, Yan R.*, Liu Y., Wang S., 2023. A smart predict-then-optimize method for targeted and cost-effective maritime transportation. Transportation Research Part B: Methodological, 172, 32–52. (ESI top 1% highly cited paper.)

    3. Yan R., Wang S., Cao J., Sun D., 2021. Shipping domain knowledge informed prediction and optimization in port state control. Transportation Research Part B: Methodological 149, 52-78.

    4. Yan R., Wang S., Fagerholt K., 2020. A semi-"smart predict then optimize" (semi-SPO) method for efficient ship inspection. Transportation Research Part B: Methodological 142, 100-125.

    5. Wang S., Yan R., Qu X., 2019. Development of a non-parametric classifier: Effective identiffication, algorithm, and applications in port state control for maritime transportation. Transportation Research Part B: Methodological 128, 129-157.

    6. Yan R., Wu S., Jin Y., Cao J., Wang S., 2022. Efficient and explainable ship selection planning in port state control. Transportation Research Part C: Emerging Technologies 145, 103924.

    7. Yan R., Wang S., Zhen L., 2023. An extended smart “predict, and optimize” (SPO) framework based on similar sets for ship inspection planning. Transportation Research Part E: Logistics and Transportation Review 173, 103109.

    8. Yang Y.#, Yan R., Wang S., 2024. Prescriptive analytics models for vessel inspection planning in maritime transportation. Computers & Industrial Engineering, 110012.

    9. Yan R., Wang S., Zhen L., 2024. Classification and regression in non-linear prescriptive analytics: Development of hybrid models. Computers and Operations Research, 106517.

    10. Tian X., Yan R.*, Laporte G., Wang S., 2023. Prescriptive analytics for a maritime routing problem. Ocean and Coastal Management 242, 106695.

    11. Yan R., Wang S., Fagerholt K., 2021. Coordinated approaches for ship inspection planning. Maritime Policy & Management, DOI: 10.1080/03088839.2021.1903599.

    12. Yan R., Wang S., Peng C., 2021. Ship selection in port state control: Status and perspectives. Maritime Policy & Management, DOI: 10.1080/03088839.2021.1889067.

    13. Yan R., Mo H.#, Guo X., Yang Y., Wang S., 2021. Is port state control influenced by COVID-19? Evidence from inspection data. Transport Policy 123, 82-103.

    14. Yan R., Wang S., Peng C., 2021. An artificial intelligence model considering data imbalance for ship selection in port state control based on detention probabilities. Journal of Computational Science 48, 101257.

    15. Yan R., Wang S., 2022. Ship detention prediction using anomaly detection in port state control: Model and explanation. Electronic Research Archive. 30(10), 3679-3691.

    16. Hou Z.#, Yan R.*, Wang S., 2022. On the K-Means clustering model for performance enhancement of port state control. Journal of Marine Science and Engineering 10(11), 1608.

    17. Yang Y.#, Yan R.*, Wang H., 2022. Pairwise-comparison based semi-SPO method for ship inspection planning in maritime transportation. Journal of Marine Science and Engineering, 10(11), 1696.

    18. Yan R., Yang Y.#, Du Y., 2022. Stochastic optimization model for ship inspection planning under uncertainty in maritime transportation. Electronic Research Archive 31(1), 103-122.

    19. Yan R., Zhuge D., Wang S., 2021. Development of two highly-efficient and innovative inspection schemes for PSC inspection. Asia-Pacific Journal of Operational Research 38(3), 2040022.

    20. Yan R., Wang S., 2019. Ship inspection by port state control—review of current research. Smart Transportation Systems 2019 233-241, Springer, Singapore. (Best Student Research Paper Award of KES STS 2019)

    21. Yan R., Wang S., 2019. Evaluation of the influence of stricter sulphur limits within emission control area on port state control inspection. Hong Kong Society for Transportation Studies International Conference Proceedings 2019.

    Topic 2: Green shipping management

    1. Yan R., Yang D., Wang T., Mo H.#, Wang S., 2024. Ship energy efficiency management integrating domain knowledge. Applied Energy 368, 123132.

    2. Luo X.#, Yan R.*, Wang S., 2023. Comparison of deterministic and ensemble weather forecasts on ship sailing speed optimization. Transportation Research Part D: Transport and Environment 121, 103801.

    3. Wang H.#, Yan R.*, Wang S., Zhen L., 2023. Innovative approaches to addressing the tradeoff between interpretability and accuracy in ship fuel consumption prediction. Transportation Research Part C: Emerging Technologies 157, 104361.

    4. Luo X.#, Yan R.*, Wang S., 2023. After five years’ application of the EU MRV mechanism: Review and prospectives. Journal of Cleaner Production, 140006.

    5. Wang H.#, Yan R.*, Au H., Wang S., Jin Y., 2023. Federated learning for green shipping optimization and management. Advanced Engineering Informatics 56, 101994.

    6. Yan R., Mo H.#, Wang S., Yang D., 2023. Analysis and prediction of ship energy efficiency based on the MRV system. Maritime Policy & Management 50(1), 117-139.

    7. Tian X.#, Yan R.*, Qi J., Zhuge D., Wang S., 2022. A bi-level programming model for China's marine domestic emission control area design. Sustainability 14(6), 3562.

    8. Yan R., Wang S., Psaraftis H., 2021. Data analytics for fuel consumption management in maritime transportation: Status and perspectives. Transportation Research Part E: Logistics and Transportation Review 155, 102489.

    9. Wang S., Zhen L., Psaraftis H., Yan R., 2021. Implications of the EU's inclusion of maritime transport in Emissions Trading System for shipping companies. Engineering 7(5), 554-557.

    10. Yan R., Du Y., Wang S., 2020. Development of a two-stage ship fuel consumption prediction and reduction model for a dry bulk ship. Transportation Research Part E: Logistics and Transportation Review 138, 101930.

    11. Zhen L., Hu Z., Yan R., Wang S., 2020. Route and speed optimization for liner ships under emission control policies. Transportation Research Part C: Emerging Technologies 110, 330-345.

    12. Zhen L., Zhuge D., Murong L., Yan R., Wang S., 2019. Operation management of green ports and shipping networks: Overview and research opportunities. Frontiers of Engineering Management 6(2), 1-11.

    Topic 3: Vessel arrival time and turnaround time to port prediction and optimization

    1. Chu Z.#, Yan R.*, Wang S., 2024. Vessel turnaround time prediction: A machine learning approach. Ocean and Coastal Management, accepted and in press.

    2. Chu Z.#, Yan R.*, Wang S., 2023. Evaluation and prediction of the punctuality of vessel arrival: A case study of Hong Kong port. Maritime Policy & Management, accepted and in press.

    Topic 4: General port and shipping management

    1. Teng, S.^,Yan R.^, Zhang X., Li Y., Wang X., Wang Y., Tian Y., Yu H., Li L., Chen L., Wang FY., 2024. Sora for hierarchical parallel motion planner: A safe end-to-end method against OOD events. IEEE Transactions on Intelligent Vehicles, accepted and in press. (^: co-first authors)

    2. Yan R., Tian X.#, Wu S., Wang S., 2023. Development of computer vision informed container crane operator alarm methods. Transportmetrica A: Transport Science, DOI: 10.1080/23249935.2022.2145862.

    3. Chen X., Yan R.*, Wu S., Liu Z., Mo H.#, Wang S., 2021. A fleet deployment model to minimize the covering time of maritime rescue missions. Maritime Policy & Management, DOI: 10.1080/03088839.2021.2017042.

    4. Yan R., Mo H.#, Yang D., Wang S., 2021. Development of denoising and compression algorithms for AIS-based vessel trajectories. Ocean Engineering 7(5), 554-557.

    5. Yan R.*, Yi W., Wang S., 2022. Predicting maximum work duration for construction workers for sustainability in human resources. Sustainability 14(17), 11096.

    6. Guo Y.#, Yan R.*, Wu Y., Wang S., 2022. Ports opening for seafarer change during the COVID-19: Models and applications. Sustainability 14, 2908.

    7. Liu, Z., Chen, W., Liu, C., Yan R., Zhang, M., 2024. A data mining-then-predict method for proactive maritime traffic management by machine learning. Engineering Applications of Artificial Intelligence 135, 108696.

    8. Xu, Y., Peng, P., Claramunt, C., Lu, F., Yan R., 2024. Cascading Failure Modelling in Global Container Shipping Network Using Mass Vessel Trajectory Data. Engineering Applications of Artificial Intelligence 135, 110231.

    9. Shen X., Chen J., Yan R., 2024. A spatial–temporal model for network-wide flight delay prediction based on federated learning. Applied Soft Computing 154 111380.

    10. Zhang X., Xiao Z., Fu X., Wei X., Liu T., Yan R., Qin Z., Zhang J., 2024. A Viewpoint adaptation ensemble contrastive learning framework for vessel type recognition with limited data. Expert Systems With Applications 122191.

    11. Shen X., Chen J., Zhu S., Yan R., 2024. A decentralized federated learning-based spatial-temporal model for freight traffic speed forecasting. Expert Systems With Applications 122302.

    12. Wang X., Liu Z., Yan R., Wang H., Zhang M., 2022. Quantitative analysis of the impact of COVID-19 on ship visiting behaviors to ports- A framework and a case study. Ocean and Coastal Management 230, 106377.

    13. Guo Y., Yan R.*, Wang S., 2021. Maximization of container slot booking profits for carriers in the liner shipping industry. Journal of Shipping and Trade 6(1), 1-10.

    14. Yan R., Wang S., Yang Y., 2021. Structured teaching of logistics modeling: Stimulating the mental capability of quantitative skills. Hong Kong Society for Transportation Studies International Conference Proceedings 2021.

    15. Guo Y.#, Yan R., Wu Y., Wang S., 2021. Modeling seafarer change at seaports in COVID-19. Proceedings of the KES International Symposium on Smart Transportation Systems 2021 (KES-STS-21). Virtual conference. June 2021.

    16. Wang S., Yan R.*, Wu L., Yang D., 2019. Optimal re-allocation of mooring areas for yachts. Maritime Business Review 4(1), 94-105.

    17. Yan R., Wang S., 2019. Study of data-driven methods for vessel anomaly detection based on AIS data. Smart Transportation Systems 2019 29-37, Springer, Singapore.

    Topic 5: Methodology and review

    1. Song Y., Wu Y., Guo Y., Yan R., etc. 2024. Reinforcement Learning-assisted Evolutionary Algorithm: A Survey and Research Opportunities. Swarm and Evolutionary Computation, 101517.

    2. Wang S., Yan R.*, 2023. Fundamental challenge and solution methods in prescriptive analytics for freight transportation. Transportation Research Part E: Logistics and Transportation Review, 102966.

    3. Tian X.#, Yan R.*, Wang H., Liu Y., Zhen L., 2023. Fundamental challenge and solution methods in prescriptive analytics for freight transportation. Electronic Research Archive 30(10), 3586-3594.

    4. Yan R., Wang S., 2022. Integrating prediction with optimization: Models and applications in transportation management. Multimodal Transportation, 100018.

    5. Yang Y.#, Yan R.*, Wang S., 2022. Integrating shipping domain knowledge into computer vision models for maritime transportation. Journal of Marine Science and Engineering 10(12), 1885.

    6. Wang S., Yan R.*, 2022. A global method from predictive to prescriptive analytics considering prediction error for "Predict, then optimize" with an example of low-carbon logistics. Cleaner Logistics and Supply Chain, 100062.

    7. Wang S., Tian X.#, Yan R., Liu Y., 2022. A deficiency of prescriptive analytics in urban transportation—no perfect predicted value or predicted distribution exists. Electronic Research Archive 30(10), 3586-3594.

    8. Yan R., Wang S., 2022. “Predict, then optimize” with quantile regression: A global method from predictive to prescriptive analytics and applications to multimodal transportation. Multimodal Transportation, 100035.

    9. Yan R., Wang S., Zhen L., Laporte G., 2021. Emerging approaches applied to maritime transport research: Past and future. Communications in Transportation Research, 100011.

    Research Team (MARINA Lab)

    Current PhD students
    Mr. JIANG Shuo, 2023 - present, PhD thesis title: Big Data and Artificial Intelligence for Ship Arrival to Port Prediction
    • Shuo enrolled in the PhD programme in the School of Civil and Environmental Engineering of Nanyang Technological University, Singapore in 2023 August intake
    • He obtained his bachelor's degree from Sun Yat-Sen University in 2022 and master's degree from the University of Hong Kong in 2023
    Ms. LUO Xi, 2022 - present, PhD thesis title: Data-Driven Optimization in Ship Fuel Consumption Management
    • Xi enrolled in the PhD programme in the Department of Logistics and Maritime Studies of the Hong Kong Polytechnic University in September 2022 (chief supervisor: Prof. Shuaian (Hans) Wang in PolyU)
    • She obtained her bachelor's degree from China University of Geosciences in 2018 and master's degree from Wuhan University in 2021
    • Her research has been published in Transportation Research Part D, Journal of Cleaner Production, and Electronic Research Archive
    Mr. CHU Zhong, 2021 - present, PhD thesis title: Machine Learning in Port Operations
    • Zhong enrolled in the MPhil and PhD integrated programme in the Department of Logistics and Maritime Studies of the Hong Kong Polytechnic University in September 2021 (chief supervisor: Prof. Shuaian (Hans) Wang in PolyU)
    • He obtained his bachelor's degree from Xi’an Jiaotong-Liverpool University in 2020 and master's degree from Imperial College London in 2021
    • His research has been published in Maritime Policy & Management
    Ms. HONG Le, 2023 - 2024, visiting PhD student sponserod by CSC 2023
    • Le is currenly enrolled in joint training program at the Zhejiang University-Westlake University under the supervision of Prof. CUI Weicheng.
    • Le obtained her bachelor's degree from Chongqing University in 2020.
    Mr. ZHOU Housheng, 2023 - 2024, visiting PhD student sponserod by CSC 2023
    • Housheng is currenly enrolled in the integrated MS-PhD programme at the Beijing Jiaotong University under the supervision of Prof. YANG Lixin.
    • Housheng obtained his bachelor's degree from Lanzhou Jiaotong University in 2019.
    Ms. DUN Meng, 2024 - 2025, visiting PhD student sponserod by CSC 2023
    • Meng is currently enrolled in the Nanjing University of Aeronautics and Astronautics under the supervision of Prof. DANG Yaoguo.
    • Meng obtained her bachelor’s degree from Lvliang University in 2018 and master’s degree from Hebei University of Engineering in 2021.
    Ms. ZHANG Nini, 2024 - 2025, visiting PhD student sponserod by CSC 2023
    • Nini is currently enrolled in the Bachelor's-to-PhD program at Southeast University under the supervision of Prof. XU Sudong.
    • Nini obtained her bachelor's degree from Southeast University in 2019.
    Mr. TENG Siyu, 2024-2025, visiting PhDsStudent sponsored by CSC 2023
    • Siyu is currently enrolled in Hong Kong Baptist University under the supervision of Prof. CHEN Long.
    • Siyu obtained his bachelor's degree from Northeast Petroleum University in 2018 and master's degree from Jilin University in 2021.
    Mr. ZHAO Liang, 2024-2025, visiting PhD student sponsored by CSC 2023
    • Liang is currently a PhD candidate in College of Civil Engineering and Architecture in Zhejiang University under supervision of Prof. BAI Yong and co-supervisor Prof. PAIK J.K.
    • Liang obtained his bachelor degree in Central South University in 2020.
    Mr. ZHANG Mingye, 2024-2025, visiting PhD student sponserod by CSC 2023
    • Mingye is currently enroled in the School of Transportation of Southeast University under the supervision of Prof YANG Min.
    • Mingye obtained his bachelor's degree from Jilin University in 2017 and master's degree from Jilin University in 2021.
    Current MEng (master by research) students
    Ms. ZHANG Wanying, expected enrollment date: January 2024, MEng thesis title: pending
    • Wanying is expected to enroll in the MEng programme in the School of Civil and Environmental Engineering of Nanyang Technological University, Singapore in 2024 January intake
    • She obtained her bachelor's degree from Singapore Management University in 2020 and has several years' working experience in the shipping industry of Singapore
    Research Fellows (post-doc researchers)
    • Dr. WANG Ruihan, enrollment time: August 2023
    • Mr. LIU Lei, enrollment time: January 2024
    Visiting Scholar (CSC)
    • Mr. GONG Fuzhong (Feb 2024 to July 2024), Deputy Director, Senior Investigator, Port State Control Officer, and ISM Auditor at Yantian Maritime Safety Administration, Shenzhen, China
    • Dr. XU Lang (Feb 2024 to Feb 2025), Associate Professor, Shanghai Maritime University, Shanghai, China
    Undergraduates supervision under the Undergraduate Research Experience on Campus (URECA) project
    • Project: Ship risk prediction in port state control inspection. Student: Pearlyn Neo Won Tong
    • Project: Emerging technologies in the maritime industry: Status and perspective. Student: Deng Hanyue
    • Project: Green shipping strategies in maritime transport. Student: Anson Douglas Hakim
    • Project: Ship inspection planning for port state control: From a prescriptive analytics perspective. Student: Jain Ishika
    Undergraduates supervision under the Final Year Project
    • Project: Artificial intelligence in logistics and supply chain management: Methods, practices, and opportunities. Student: Neo Kiat Peng Daren

    Teaching

    • Lecturer of MT2004: Mathematics II for Maritime Studies offered by CEE NTU to year two BSc Maritime Studies students (Semester 2, 2023/2024).
    • Lecturer of MT2005: Port Economics offered by CEE NTU to year two BSc Maritime Studies students (Semester 2, 2023/2024).
    • Lecturer of MT1001: Mathematics I for Maritime Studies offered by CEE NTU to year one BSc Maritime Studies students (Semester 1, 2023/2024).
    • Lecturer of MT4001: Shipping Logistics offered by CEE NTU to year four BSc Maritime Studies students (Semester 1, 2023/2024).
    • Lecturer of LGT5171: Contemporary Issues in Operations Management offered by Faculty of Business to MSc students in Business Management (core course), The HK PolyU (Semester 1, 2022/23, 34 MSc students), course evaluation by students: 4.3/5 (over department and faculty mean).
    • Teaching assistant of LGT5171: Contemporary Issues in Operations Management offered by Faculty of Business, The HK PolyU (Semester 1, 2019/20, 42 MSc students), course evaluation by students: 4.7/5
    • Teaching assistant of LGT5171: Contemporary Issues in Operations Management offered by Faculty of Business, The HK PolyU (Semester 1, 2019/20, 41 MSc students), course evaluation by students: 4.4/5
    • Assisting in supervising several research assistants: Mr. MO Haoyu (from The Hong Kong University of Science and Technology), Mr. TIAN Xuecheng (From Wuhan University), Ms. WANG Shuyuan (from Pennsylvania State University), Ms. YU Mengqi (from Jiangxi Normal University), Mr. HOU Zeyu (from The Hong Kong University of Science and Technology), Ms. LUO Xi (From Wuhan University), Ms. YANG Ying (from Tsinghua University), Mr. LU Zhihao (from Shanghai Maritime University), Mr. CHEN Haoyang (from TU Delft).

    Openings

    As a new faculty in the School of Civil and Environmental Engineering (CEE) at Nanyang Technological University (NTU), recruitments of PhD students, post-docs, research associates, and research assistants are on-going.

    PhD Positions

    Fully funded PhD positions and some partially/self-financed PhD positions in Maritime Studies are available for January and August intake under the supervision of Dr. Yan in the School of CEE at NTU, Singapore. If you are interested, please send an email to Dr. Yan (ran.yan@ntu.edu.sg) including your CV, transcript, GPA ranking statement, 1-page research statement with subject "PhD application+your name". Shortlisted candidates will be contacted and interviewed.
    Potential requirements:
    • Meet the PhD admission requirements of NTU and CEE https://www.ntu.edu.sg/education/graduate-programme/cee-phd-programme-(by-research)#additionaiInformation;
    • Hold a bachelor’s or master’s degree (which is highly preferred) from a good university with decent GPA in related subjects such as engineering (e.g., computer engineering, electronics engineering, industrial engineering, marine engineering, transport engineering), science (e.g., computer science, mathematics, operations research, electronics), and business (e.g., economics, management science);
    • Strong programming skills, such as Python, C++, Java, Julia, or other competent languages;
    • Having research experience in maritime transport, logistics management, machine learning, deep learning, and optimization with research publications in reputable peer-reviewed journals or conferences would be a plus;
    • Proficient in written and spoken English.

    Postdoctoral researcher positions

    Postdoctoral researchers in Maritime Studies are available with flexible start time in the School of CEE at NTU, Singapore. If you are interested, please send an email to Dr. Yan (ran.yan@ntu.edu.sg) including your CV, cover letter, 1-3 pages research proposal, and a list of two or three referees with subject "Post-doc application+your name". Shortlisted candidates will be contacted and interviewed.
    Potential requirements:
    • Must hold a PhD degree in transport engineering, maritime transport and management, computer science, or a related field from a good university;
    • Excellent programming skills, such as Python, C++, Java, Julia, or other competent languages;
    • A good record of publications in reputable peer-reviewed journals or conferences in maritime transport, logistics management, machine learning, deep learning, and optimization;
    • Proficient in written and spoken English;
    • Experience in proposal writing and funding application is a plus.

    Representative Projects

  • Artificial intelligence (AI) for Port State Control (PSC) at the Port of Hong Kong and the Port of Shanghai
  • Project Page | Project Description | User Manual

    Project Page

  • AI for Ship Arrival Time to Port Analysis and Prediction
  • Professional services

  • Member of MSc Business Management Programme Committee (offered by Faculty of Business, The HK PolyU) in 2022/23
  • Editorial Board Member of Cleaner Logistics and Supply Chain, December 2022-present
  • Editorial Assistant of Cleaner Logistics and Supply Chain, March 2022-November 2022
  • Guest editor of special issue Smarter and greener maritime and shipping logistics in Transportation Research Part E: Logistics and Transportation Review, March 2024
  • Guest editor of special issue Managing Transportation Hubs: Challenges and Best Practices in Maritime Policy & Management, March 2024
  • Guest editor of special issue Digitalisation and Artificial Intelligence in Maritime Transport: Operations, Management, and Policy in Maritime Policy & Management, March 2024
  • Guest editor of special issue Maritime Logistics and Green Shipping in Journal of Marine Science and Engineering, November 2023
  • Guest editor of special issue Learning based Solution Techniques for Optimization in Logistics and Transportation Systems in Transportation Research Part E: Logistics and Transportation Review, June 2023
  • Guest editor of special issue Innovative Mathematical Methods for Transportation Research in Electronic Research Archive, February 2023
  • Guest editor of special issue Operations for Sustainable Shipping and Port Management in Journal of Marine Science and Engineering, February 2023
  • Guest editor of special issue Opportunities and Challenges of Marine Industry in the Post Epidemic Era in Frontiers in Marine Science, February 2023
  • Guest editor of special issue Data Analytics in Maritime Research in Journal of Marine Science and Engineering, November 2022
  • Guest editor of special issue Innovative Methods for Multimodal Transport System Operation, Management, and Analysis in Sustainability, June 2022
  • Guest editor of special issue Intelligence in Urban Transportation in Electronic Research Archive, June 2022
  • Guest editor of special issue Big Data and Artificial Intelligence in Maritime Transport Research in Maritime Transport Research, January 2022
  • Guest editor of special issue Cleaner Maritime and Air Cargo Logistics and Supply Chain in Cleaner Logistics and Supply Chain, July 2021
  • Editorial board member of special issue Transport+Big Data+Machine Learning of Journal of Transportation Engineering and Information, 2021
  • Session organizer of the 28th Annual Conference of the International Association of Maritime Economists (IAME), Hong Kong, 2020
  • Student helper of the 24th International Conference of Hong Kong Society for Transportation Studies (HKSTS), Hong Kong, 2019
  • Referees of Transportation Science,Transportation Research Part E, Applied Energy Computer-Aided Civil and Infrastructure Engineering, IISE Transactions, Marine Pollution Bulletin ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, Journal of Air Transport Management, Travel Behaviour and Society, Ocean Engineering, Applied Ocean Research, Maritime Policy & Management, Expert Systems With Applications, IET Intelligent Transport Systems, Naval Research Logistics, Operational Research, Journal of Marine Science and Engineering, International Journal of Shipping and Transport Logistics, Transportation Research Record, Electronic Research Archive, GeoInformatica, Communications in Transportation Research, Cleaner Logistics and Supply Chain, Maritime Transport Research, Journal of Shipping and Trade, IAME conference proceedings, IEEE ITS conference proceedings.
  • Talks

  • 12/2023: The 9th International Symposium on Transport Network Resilience (INSTR2023), Hong Kong, China(Session Chair)
  • 12/2023: The 27th International Conference of Hong Kong Society for Transportation Studies (HKSTS 2023), Hong Kong, China
  • 12/2023: School of Management, Shenzhen Univresity, Shenzhen, China
  • 09/2023: The International Association of Maritime Economists (IAME, 2023), Los Angeles, the USA
  • 07/2023: School of Economics & Management, Shanghai Maritime University, Shanghai, China
  • 07/2023: The 7th Maritime Silk Road Port International Cooperation Forum, Ningbo, China
  • 09/2022: Campus visit (including delivering a research seminar and a mock lecture) invited by the School of Civil and Environmental Engineering of the Nanyang Technological University (NTU), Singapore
  • 05/2022: The 11th International Forum on Shipping, Ports, and Airports (IFSPA 2022), Hong Kong, China
  • 12/2021: The 25th International Conference of Hong Kong Society for Transportation Studies (HKSTS 2021), Hong Kong, China
  • 06/2021: The World Transport Convention (WTC, 2021), Xi'an, China
  • 11/2020: The World Transport Convention Chengdu Forum (WTC, 2020), Chengdu, China
  • 06/2020: The International Association of Maritime Economists (IAME, 2020), Hong Kong, China
  • 12/2019: The 24th International Conference of Hong Kong Society for Transportation Studies (HKSTS 2019), Hong Kong, China
  • 12/2019: The 3rd International Symposium on Multimodal Transportation (ISMT 2019), Singapore
  • 06/2019: The KES International Symposium on Smart Transportation Systems 2019 (KES-STS-19), Malta
  • 04/2019: The LMS Research Postgraduate Student Symposium, Hong Kong, China
  • Awards

  • 2023, Elsevier 2022 Early Career Researcher Paper Award for journal Cleaner Logistics and Supply Chain
  • 2022, Excellent Outstanding Reviewer of Cleaner Logistics and Supply Chain
  • 09/2018-03/2022, Studentship of The Hong Kong Polytechnic University for Postgraduate Students
  • 2022, Nominated by Faculty of Business (the only nominee) for the competition of the PolyU PhD Thesis Award
  • 2021, Excellent Paper Award of WTC 2021 (first author). Paper title: Vessel fuel consumption prediction considering shipping domain knowledge. Xi'an, China
  • 2019, Best Student Paper Award for the 2nd KES International Symposium on Smart Transport Systems. Paper title: Ship inspection by port state control—review of current research. (The only student awardee in maritime transportation)
  • 2018, Outstanding student cadres of Jiangsu Province, China (1 of about 2,500 students)
  • 2018, Honorary Title of Outstanding Graduate of Hohai University (1 of 101 students)