ICIIL 2024 Keynote Speakers 

Fellow, IEEE
Prof. Bo Ai, Beijing Jiaotong University, China

Bo Ai (Fellow, IEEE) received the M.S. and Ph.D. degrees from Xidian University, Xi’an, China, in 2002 and 2004, respectively.,He received the Honor of Excellent Post-Doctoral Research Fellow from Tsinghua University, Beijing, China, in 2007. He was a Visiting Professor with the Electrical Engineering Department, Stanford University, Stanford, CA, USA, in 2015. He is currently a Full Professor with Beijing Jiaotong University, Beijing, where he is the Dean of the School of Electronic and Information Engineering. He is one of the directors for Beijing “Urban Rail Operation Control System” International Science and Technology Cooperation Base, and a Backbone Member of the Innovative Engineering based jointly granted by the Chinese Ministry of Education and the State Administration of Foreign Experts Affairs. He has authored or coauthored eight books and authored over 300 academic research articles in his research area. He holds 26 invention patents. He is the research team leader of 26 national projects. He has won some important scientific research prizes. Five papers have been the ESI highly cited paper. He has been notified by the Council of Canadian Academies. His research interests include the research and applications of channel measurement and channel modeling and dedicated mobile communications for rail traffic systems.,Dr. Ai is a fellow of the Institution of Engineering and Technology (IET). He received the Distinguished Youth Foundation and Excellent Youth Foundation from the National Natural Science Foundation of China, the Qiushi Outstanding Youth Award by the Hong Kong Qiushi Foundation, the New Century Talents by the Chinese Ministry of Education, the Zhan Tianyou Railway Science and Technology Award by the Chinese Ministry of Railways, and the Science and Technology New Star by the Beijing Municipal Science and Technology Commission. He has been listed as one of the Top 1% authors in his field all over the world, based on the Scopus database. He has also been feature interviewed by the Electronics Letters (IET). He is the IEEE VTS Beijing Chapter Vice Chair and the IEEE BTS Xi’an Chapter Chair. He was a co-chair or a session/track chair of many international conferences. He is an Associate Editor of the IEEE Antennas and Wireless Propagation Letters and IEEE Transactions on Consumer Electronics, and an Editorial Committee Member of the Wireless Personal Communications journal. He is the Lead Guest Editor of Special Issues on IEEE Transactions on Vehicular Technology, IEEE Antennas and Propagations Letters, and the International Journal on Antennas and Propagations. He is an IEEE VTS Distinguished Lecturer.

Speech Title: MIMO Channel Measurement and Modeling

Abstract: The future of wireless communication is set to be more diverse and dynamic, with a wider range of scenarios and services. The emergence of satellite internet, smart railways, maritime communications, and unmanned aerial vehicles has expanded the communication demands. The wireless channel is the medium through which communication occurs and is one of the fundamental factors determining wireless communication capacity and system performance. Consequently, the evolution of wireless communication technologies also presents new challenges and demands for channel modeling. This report, based on our team's research achievements in the field of wireless channel measurement and modeling, highlights the latest advancements and findings in three typical scenarios: massive MIMO, high-speed mobility, and millimeter-wave integrated communication and sensing. The report covers specific content such as channel measurement methods, analysis of measured results, channel modeling, and simulation methods. Finally, the report offers a perspective on the research prospects and development directions for channel modeling in future wireless systems.

Prof. Zongzhi Li, Illinois Institute of Technology, USA

Zongzhi Li received BE from Chang’an University, Xi’an, China; MSCE and Ph.D. (December 2003) in transportation and infrastructure systems engineering, as well as MSIE in operations research (May 2002) from Purdue University, USA. After completing the Ph.D. study, he joined Traffic Operations and Safety Laboratory (TOPS Lab) at the University of Wisconsin-Madison, USA as a Postdoctoral researcher until August 2004 after accepting a tenure-track assistant professor position at Illinois Institute of Technology (IIT), USA. Currently, he holds full professor rank with tenure and serves as the Director of Sustainable Transportation and Infrastructure Research (STAIR) Center, and Transportation Engineering Laboratory at IIT. He has served as the Principal Investigator (PI) for over US$4.26 million of research studies on multimodal travel demand and transportation system performance modeling, asset management, and network economics funded by U.S. Federal and state agencies and the private sector. He has supervised nearly 80 M.S. and Ph.D. students; published 4 books, including Transportation Asset Management: Methodology and Applications (ISBN: 978-148-221-052-1) as the world’s first graduate-level textbook in the area; and Megacity Mobility: Integrated Urban Transportation Development and Management (ISBN: 978-036-736-358-1), 3 book chapters, and nearly 80 referred papers; developed 3 software packages; and holds 7 U.S. patents. He is a member of the editorial board of the American Society of Civil Engineers (ASCE) Journal of Infrastructure Systems, an associate editor of the Elsevier Journal of Traffic and Transportation Engineering, and a handling editor of the TRB/Sage Journal of Transportation Research Record. Dr. Li was a recipient of numerous awards, including ASCE Arthur M. Wellington Prize (2011), IIT Sigma Xi Award for Research Excellence (2011), Charley V. Wootan Award given by the U.S. Council of University Transportation Centers (2000), and International Road Federation Fellowship Award (1998).

Speech Title: Temporal Instability and Unobserved Heterogeneity in Means and Variances of Random Parameters across Single-Vehicle Crash Severity Factors

Abstract: This study introduces a random parameter multinomial logit model with heterogeneity in means and variances across single-vehicle crash severity factors. Crash severities are classified property damage only (PDO), non-incapacitating injury or possible injury (NPI), and incapacitating injury or fatal (ICF) designations. Factors considered include personnel, vehicle, roadway, traffic, and crash-specific characteristics. Data from Illinois state-maintained highways (2018-2021) are used for model estimation and validation. Model estimation begins by evaluating the temporal instability of factors over the four-year period, then applying the data to both the proposed and traditional models for comparisons. Chi-square tests reveal temporal instability at a 5% significance level, leading to separate model estimation using the annual dataset. Results shows that the proposed models contain normally distributed random parameters with heterogeneity in means and variances of some crash severity factors. Better data fits are observed for the proposed model over the traditional model. Providing adequate nighttime lighting increases PDO crash potential, benefiting safety. This effect is higher for young drivers, passing maneuvers, and animal-related causes but is lower for crashes involving passenger cars, SUVs/minivans, medians, and airbag ejections. Cautious driving on wet roads increases PDO and decreases NPI crash potential, especially in distraction-related incidents. Safety improvements, indicated by increased PDO potential or shifts from severe ICF to less severe NPI crashes, are seen in male occupants and young drivers, attentive and cautious drivers in harsh weather, vehicles with superior features, and lower speeds. Roadways with wider cross-sections and effective control measures also contribute to safety benefits.

Prof. Xiaowen Fu, The Hong Kong Polytechnic University, China

Professor Xiaowen Fu is the Head of Department and Professor in Engineering Management at the Department of Industrial and Systems Engineering, the Hong Kong Polytechnic University. His main research areas include engineering management, data analytics, transport and logistics, which cover issues such as competition policy and government regulation, efficiency benchmarking, operation management, transport demand modelling and industrial organization. He has been the principal investigator of more than 20 research grants, the guest editor of 7 journal special issues, and the author of more than 110 journal articles. He is the Editor-in-Chief of the journal Case Studies on Transport Policy, associate editor of the book series “Advances in Airlines Economics”. Prof. Fu has provided advisory and economic modeling services to many organizations such as the Boeing Commercial Aircraft, New Zealand Commerce Commission, Australian Competition and Consumer Commission, Government of British Columbia in Canada, Australian Competition Tribunal, Hong Kong Civil Aviation Department, Hong Kong Transport and Housing Bureau, Greater Bay Airlines, Japan Rail (East), and OECD. He is the director of the Behavior and Knowledge Engineering Research Center, founding chair of the Maritime Economy and Policy stream of the World Transport Convention, member of the Technical and Statistical Task Team on the Productive Capacities Index under the United Nations Conference on Trade and Development (UNCTAD), and an honorary professor of the University of Sydney Business School.

Speech Title: High-speed Rail’s Dynamic Impacts on Regional Industrial Structure Upgrading and Its Mechanisms

Abstract: High-speed rail (HSR) is a costly transportation infrastructure, and its investment can be better justified when it leads to long-term regional economic development. However, there is a lack of empirical investigations that quantify HSR's dynamic economic benefits, particularly considering the lagging and fading effects, as well as the changing effects resulting from the continuous expansion of the HSR network. This study represents one of the initial attempts to quantify the dynamic impacts of HSR on the upgrading of regional industrial structures. It distinguishes the sources of these impacts by considering the lagging/fading effects for individual cities and the staggered expansion of the HSR network that includes a more diverse range of cities. Using data from 278 Chinese cities over a span of 19 years, we employed a staggered synthetic control method (staggered SCM) for our empirical investigations. The results of our study indicate that HSR generally facilitates the upgrading of a city's industrial structure, although its dynamic impacts on "industrial structure servitization" and "industrial labor productivity" vary across cities. The effects of HSR on industrial structure servitization tend to fade quickly, while the impacts on improving industrial labor productivity are more persistent. Furthermore, our analysis of heterogeneity suggests that there is significant regional diversity in the effects of HSR on industrial servitization. This effect is more enduring in core cities, while the labor productivity-improving impacts of HSR remain consistent across different cities. Mechanism analysis reveals that HSR has a stronger incentivizing effect on the tertiary industry compared to the secondary industry, thus promoting servitization rather than directly transforming the secondary industry into the tertiary industry. In contrast, a city's industrial labor productivity is enhanced by HSR through improved productivity in both the secondary and tertiary industries.