In order to further strengthen academic exchanges in the field of transportation both domestically and internationally, and learn from cutting-edge research achievements, the Department of Transportation Engineering at South China University of Technology held the Overseas Transportation Academic Masters Forum on the afternoon of June 12, 2022. This forum specially invited Professor Wang Shuai'an from the Hong Kong Polytechnic University, Professor Dong Jingxin from the University of Newcastle in the UK, and Professor Liu Ronghui from the University of Leeds to attend and share recent research results, chaired by Professor Wen Huiying.
Professor Wang Shuai'an's report title:
Analysis of Typical Methods for Transportation System Management: The Latest Research Progress of Machine Learning Algorithms in the Transportation Field
Focusing on the rapidly developing machine learning algorithms at present, Professor Wang Shuai'an starts from the principles of machine learning and introduces in simple terms how to make approach predictions based on historical data when facing uncertain parameters, and analyzes the characteristics of different prediction methods.
Report Content of Part 1
In the report, Professor Wang cites real-life examples and statistical principles to gradually depict the important role of machine learning in solving related problems. Through Professor Wang's simple and easy to understand explanation, students have gained a more intuitive and in-depth understanding of the concepts and application scenarios of machine learning, and have also corrected some cognitive misunderstandings.
Reported by Dr. Wang Shuai'an, a professor at the School of Business at the Hong Kong Polytechnic University. Graduated from Tsinghua University with a bachelor's degree; Graduated with a master's degree from Tsinghua University and Ashen Polytechnical University in Germany; I graduated with a PhD from the National University of Singapore. After graduating with a PhD, he taught at universities in Australia, the United States, and Hong Kong SAR. The main research areas include port and shipping operation management, urban transportation network management, and transportation big data. Published over 200 papers in journals such as Transportation Research Part B, Transportation Science, and Operations Research. Ranked among the top 2% scholars in the world in terms of citation influence in the field of transportation and logistics. Served as the founding editor in chief of international journals Communications in Transportation Research, Cleaner Logistics and Supply Chain, deputy editor in chief of Transportation Research Part E, Flexible Services and Manufacturing Journal, Transportmetrics A, Transportation Research Part B, Transportation Letters, and Transportation Research Record Editorial board member of Maritime Transport Research.
Professor Dong Jingxin's report title:
Management of empty shipping containers during the epidemic period
In combination with the new challenges posed by the COVID-19 in recent years to shipping management, especially the problem of empty container turnover, Professor Dong Jingxin shared a variety of solutions to the problem, focusing on how to use mathematical planning methods to improve the management level of shipping empty containers in the context of the epidemic.
Report Content of Part II
In the report, Professor Dong quantitatively analyzed the economic losses caused by empty containers based on the current situation of shipping under the impact of the epidemic, enabling students to understand the practical significance of this issue. Subsequently, Professor Wang introduced the various methods currently used and their effectiveness, and ultimately focused on alleviating the problem through mathematical planning.
Reporter Introduction: Dr. Dong Jingxin, Professor of Operations Management and Supply Chain Management at the Business School of the University of Newcastle in the UK, Doctoral Supervisor, and Director of the Doctoral Project Center. In 2005, he obtained a doctoral degree in Systems Engineering from Beijing Jiaotong University. From 2006 to 2009, he worked as a postdoctoral researcher at the University of Plymouth School of Business in the UK. His main research areas include operations research, data science, etc. He is skilled in using game theory, stochastic integer programming, data mining in logistics, transportation, energy and other fields and operational management projects. Professor Dong has published over 50 papers in renowned journals in the field of transportation, such as Transportation Research Part B, Part E, European Journal of Operations Research, Town Planning Review, etc. Organized or participated in high-level academic seminars multiple times, and served as the organizational chairman of the UK Operations Management and Research Summit in 2020; Member of the Organizing Committee for the 2020 International Conference on Logistics and Maritime Systems; In 2016, served as the organizing chairman of the China UK Green Logistics and Supply Chain Management Research Seminar. Served as the deputy editor in chief of the renowned academic journal IET Intelligent Transportation System, editor in chief of Ocean Systems Management, and reviewer for many well-known journals in the field of transportation. Has won the Outstanding Review Contribution Award for top transportation journals such as Transportation Research Part C and Part E.
Professor Liu Ronghui's report title:
Public Transport Big Data Analysis - Modeling Framework and Application
With the increasing maturity of data collection and processing methods in the field of public transportation, Professor Liu Ronghui introduced in detail at the conference how to use data analysis methods such as machine learning to analyze the large amount of travel data generated in the public transportation field, from modeling framework to practical application, in order to significantly improve the performance of the public transportation system and improve the passenger experience.
Report Content of Part III
In this report, Professor Liu pointed out that with the help of diversified information collection methods, the public transportation dataset has become more three-dimensional and precise. He put forward his own opinions on how to use this data and what problems to solve. At the same time, he further explained the problems encountered in the research process and the future development direction of this field. Through Professor Liu's explanation, students have gained a deeper understanding of how data can help solve practical problems.
Reported by Dr. Liu Ronghui, Professor and Vice Dean of the School of Transportation at the University of Leeds, UK. The first female editorial board member of the top conference in the field of transportation, ISTTT, and the deputy editor in chief of the mainstream journals in the field of transportation, IEEE Transactions on ITS and IET ITS. She obtained a doctoral degree from the University of Cambridge, mainly engaged in research in traffic network modeling, traffic simulation, and public transportation systems. Professor Liu has published multiple papers in top transportation journals such as Transportation Science, Transportation Research Part A/B/C/E, and has led multiple projects such as the European Union Science Fund and the Newton Science Fund. The School of Transportation at the University of Leeds ranks first in Europe and fourth globally.
In this meeting, experts patiently answered the confusion raised by the attending teachers and students. This academic forum focuses on current hot topics in the field of transportation and has been successfully conducted in a harmonious and orderly discussion and strong academic atmosphere. The selfless sharing of research results by experts has built a solid bridge for academic exchanges at home and abroad.