Haoning XiView profile
Lecturer
Dr. Haoning Xi is a Lecturer in Business Analytics at the Newcastle Business School, University of Newcastle (UON), Australia. She previously served as a Research Fellow at the Institute of Transport and Logistics Studies (ITLS), The University of Sydney Business School. Dr. Xi received her Ph.D. in Transportation & Operations Research from the University of New South Wales (UNSW) Sydney, where she was also a co-cultured Ph.D. student at CSIRO Data 61. She holds a Master's degree from Tsinghua University and a Bachelor's from Central South University, China, and has research experience at the University of California, Berkeley and Hong Kong University of Science and Technology. Ph.D. in Transportation & Operations Research, University of New South Wales Master of Engineering, Tsinghua University, China Bachelor of Engineering, Central South University, China Research Assistant, University of California, Berkeley Visiting Researcher, Hong Kong University of Science and Technology Dr. Xi's research focuses on applying business analytics, machine learning, and operations research to mobility services and transportation systems. Her work centers on Mobility-as-a-Service (MaaS), travel behavior analysis, data-driven optimization, and sustainable transportation. She investigates how to leverage millions of smart card data from various transport modes to uncover user travel patterns and preferences, enabling intelligent decision-making for transport authorities. Her research also explores predictive analysis using AI and ML algorithms to forecast travel patterns, service disruptions, and resource allocation strategies. A significant portion of her work examines personalized mobility services and how to integrate transportation with non-mobility offerings to create comprehensive subscription models. Dr. Xi has published over 23 SCI/SSCI indexed papers, including 9 ABDC A* journal articles (8 as first/corresponding author) in top journals like European Journal of Operational Research and Transportation Research series. Her publications reveal a strong emphasis on mathematical modeling of transportation systems, with increasing focus on AI/ML applications in recent years. The articles demonstrate progression from traditional transportation modeling toward more sophisticated data-driven approaches integrating machine learning with operational research techniques, particularly in the context of Mobility-as-a-Service ecosystems and pandemic-related travel behavior changes. Rising Stars Women in Engineering, Asian Deans' Forum (2024) Best Research Silver Award, International Symposium on Sustainable Development of Urban Transport Systems (2024) Best Paper Award, International Workshop on Computational Transportation Science (2024) Global Talent Independent Scheme, Australian Government (2021) University Postgraduate Award, UNSW (2021) CSIRO Data 61 Top-up Ph.D. Scholarship (2020) Dr. Xi currently supervises 5 PhD students across various topics including digital transformation's impact on ESG, digital sustainability measurement, data analytics for hospitality management, social media sentiment analysis, and organizational capabilities in regulated environments. She has secured over $463,500 in research funding from multiple sources including National Natural Science Foundation of China ($80,000), iMOVE Australia Limited ($300,000), and various internal university grants. Her current projects focus on AI-driven bus network optimization, parking management models, and enhancing user mobility experience through business analytics. Dr. Xi serves as CHSF College Research Committee Member and NBS Equity Diversity and Inclusion (EDI) Committee Member at the University of Newcastle. She is Co-chair of the Multimodal Urban Transportation Systems Analysis Committee in the World Transport Congress (2024-2026) and serves on editorial boards for International Journal of Transportation Science & Technology and Transportation Safety and Environment. She also acts as a peer reviewer for top transportation journals including Transportation Science and Transportation Research series.
