Richard Connors

Research | Mathematical Models | Transport

Junglinster, Grevenmacher, Luxembourg

About

Research interests include: Network design. Bi-level optimization. Mathematical programmes with equilibrium constraints. The role of stochasticity in transport network analysis, in demand and supply, within-day and day-to-day. Developing new mathematical models, and exploring them via simulation. Algorithm design. The dependence of transport system properties (such as reliability & vulnerability) on the configuration of network infrastructure. Network topology, network evolution. The mathematical analysis of traffic networks: analytical properties of different formulations. Approximation, aggregation and scales of representation in traffic networks. The compromise between simplicity and fidelity when modelling complex systems. Models of behaviour, choice models, particularly with regard to route choice. Predictive accident models.

Experience

  • Senior Research Scientist at Luxembourg Institute of Science and Technology (LIST)
    Apr 2025 - Present · 1 yr 4 mos

  • Research Scientist at University of Luxembourg
    Nov 2019 - Nov 2024 · 5 yrs 1 mo

  • Senior Research Fellow at University of Leeds
    Apr 2003 - Sep 2023 · 20 yrs 6 mos

    Research in transportation and mobility. Transport systems comprise cost-sensitive individuals making travel decisions in a congestible network infrastructure. Modelling such systems requires representation of traveller demand and human behaviour, mobility services and operators, the physical infrastructure and interacting network flows. Modelling and simulation of this complex socio-technical system is deeply interdisciplinary, synthesising understanding from many fields including mathematics, physics, engineering, computer science, economics, geography and psychology. My methodological focus includes • Formulating mathematical models & establishing their analytical properties. • Building models derived from theory, models based on empirical data, and on ensembles of synthetic data. • Extending and generalizing existing models to account for heterogeneity, stochasticity, uncertainty. • Defining and solving optimisation problems (including bi-level, MPEC, multi-objective). • Creating and coding solution algorithms. Establishing convergence. Interrogating efficiency.

  • Visiting Professor at University of Tokyo
    2007 - 2007 · Less than a year

  • Software Engineer at MathWorks
    Apr 2000 - Apr 2003 · 3 yrs 1 mo

    Creating bespoke tools for research scientists in the pharmaceutical, financial & automotive sectors, in close collaboration with technical experts in these industries. A key project I worked on was developing software incorporating design of experiments and the estimation of hierarchical statistical models that won the Henry Ford Technology Award, the highest honour within Ford Motor Company in recognition of exceptional technical contribution. As the MATLAB Model-based Calibration toolbox it is currently used in engine development worldwide.