
Dr Qixiu Cheng
Current positions
Lecturer in Artificial Intelligence & Data Analytics
School of Management - Business School
Contact
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Research interests
My name is Qixiu Cheng (程启秀). I have been a Lecturer in Artificial Intelligence and Data Analytics at the University of Bristol (UoB) Business School since September 2023. I’m focusing on exploring smart mobility systems with quantitative methods from multiple disciplines, e.g., transportation engineering, operations research, statistical analysis, and artificial intelligence. I am broadly interested in the research topics on transportation network modeling and optimization, traffic flow theory and control, and AI applications in transportation. My full publications can be found in my Google Scholar.
I am looking for self-motivated PhD students with a solid background in transportation engineering, operations research, and/or AI algorithms. The applicant should be familiar with at least one programming language (e.g., Python, Matlab, and C++). The English language requirement can be found here. If you are interested in pursuing a PhD degree working with me at the University of Bristol Business School, please send me your CV and transcripts at any time, and we can discuss more on your research topic. I also welcome visiting scholars and visiting PhD students, please send me an email if you are interested.
Projects and supervisions
Research projects
Beyond Real Data: Quantifying and Addressing Risks of Partial AI-Generated Data in LLM Training for Autonomous Systems
Principal Investigator
Managing organisational unit
School of Management - Business SchoolDates
01/03/2025 to 28/02/2026
Publications
Selected publications
01/06/2024Using frequency domain analysis to elucidate travel time reliability along congested freeway corridors
Transportation Research Part B: Methodological
Analytical formulation for explaining the variations in traffic states
European Journal of Operational Research
An s-shaped three-parameter (S3) traffic stream model with consistent car following relationship
Transportation Research Part B: Methodological
Recent publications
01/01/2025Traffic Flow Outlier Detection for Smart Mobility Using Gaussian Process Regression Assisted Stochastic Differential Equations
Transportation Research Part E: Logistics and Transportation Review
A fundamental diagram based hybrid framework for traffic flow estimation and prediction by combining a Markovian model with deep learning
Expert Systems with Applications
Analysis of congestion key parameters, dynamic discharge process, and capacity estimation at urban freeway bottlenecks: a case study in Beijing, China
Transportation Letters
Analytical formulation for explaining the variations in traffic states
European Journal of Operational Research
Dynamic Systems Modeling and Integrated Transportation Demand-and-Supply Management with a Polynomial Arrival Queue Model
Journal of Transportation Engineering, Part A: Systems