Railways and Transport Laboratory

Matina Lai-Ying Chau

PhD Candidate

MSc (University of Sussex), BSc (Durham University)

Contact Details

Address: Office 89, NTUA Campus, Iroon Polytechniou 5, GR-15773 Athens, Greece.
Email: mchau@mail.ntua.gr
Phone: (+30) 210 772 1723
Scopus: N/A


Matina Chau is a PhD Candidate and Research Associate at the Department of Transportation Planning and Engineering of the National Technical University of Athens (NTUA). After having graduated from Durham University with a joint-honours degree in Mathematics and Psychology, she went on to pursue a M.Sc. at the University of Sussex in Robotics and Autonomous Systems. Throughout the course of her studies, she had developed a focus of research experience and interest on machine learning, data analysis and smart-city development.

At NTUA she is currently pursuing her doctoral thesis on the development of dynamic optimization approaches for multi-modal transport systems using Big Data and deep learning methods under the supervision of Assistant Professor Dr Konstantinos Gkiotsalitis. Her research is supported by the scholarship she receives as a research associate for the “CONDUCTOR EU H2020 Project: Fleet and Traffic Management Systems for conducting Future Cooperative Mobility” project.

Professional Experience
  • 2022-current: Research Associate, Department of Transportation Planning and Engineering, School of Civil Engineering, National Technical University of Athens.
  • MSc in Robotics and Autonomous Systems, University of Sussex.
  • BSc in Mathematics and Psychology, Durham University.
  1. Chau, M. L., Koutsompina, D., & Gkiotsalitis, K. (2024). The Electric Vehicle Scheduling Problem for Buses in Networks with Multi-Port Charging Stations. Sustainability, 16(3), 1305. https://doi.org/10.3390/su16031305
  1. Conductor, European Commission – H2020, Innovation Action, National Technical University of Athens, 2022-2025.


Engineering Areas

#Public Transport
#Fleet Management


#Machine Learning

Social Sciences

#Mobility as a Service
#Resource Allocation
#Public Transport