Robin Lovelace

Robin Lovelace

Associate Professor of Transport Data Science

University of Leeds

About me

Hi, I’m Robin. Welcome to my personal website πŸŽ‰

Here I share my publications and previous/upcoming talks, with links aplenty to visual/audio/video content that you can read/listen/watch to in your own time πŸ“–πŸŽ§πŸ“Ί I share lots of code for data science and reproducible research, this could be a good place to find resources to get started and try out things if you’re interested in reproducing or building on some of the work that I’ve done (which in turn builds on the work of others as all research does). I also occasionally share blog posts and other things here. If you’d like to get in touch, see here πŸš€

In my main academic job I’m Associate Professor of Transport Data Science at the University of Leeds. At Leeds, I’m based primarily at the Institute for Transport Studies where I research, develop and teach free, open, reproducible and internationally scalable techniques for working with data to support evidence-based policies.

I am author of papers and books on transport planning, energy, geographic data analysis and modelling. I lead the Transport Data Science module, which is available to students taking Data Science and Data Analytics and Data Science and Urban Analytics courses at the University of Leeds.

You can find me on various platforms, including Mastodon, Google Scholar, and GitHub.

  • Geocomputation
  • Transport modelling
  • Reproducible geographic data analysis
  • Mode shift, especially uptake of active modes
  • PhD in Transport and Energy, 2013

    University of Sheffield

  • MSc in Environmental Science and Management, 2009

    University of York

  • BSc in Environmental Geography, 2008

    University of Bristol

Upcoming & Recent Talks

Recent Publications

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(2023). A Road Segment Prioritization Approach for Cycling Infrastructure. Journal of Transport Geography.

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(2023). Road Lighting and Cycling: A Review of the Academic Literature and Policy Guidelines. Journal of Cycling and Micromobility Research.

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(2023). Where to Invest in Cycle Parking: A Portfolio Management Approach to Spatial Transport Planning. Environment and Planning B: Urban Analytics and City Science.

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(2023). Packaging Code for Reproducible Research in the Public Sector. arXiv.

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(2023). Cycle network policy, planning and investment transformed by the Propensity to Cycle Tool. Research Excellence Framework.

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Recent Posts


Data science




Transport modelling



Associate Professor
Jan 2019 – Present Leeds
Teaching and researching transport data science.
Principle Investigator
Apr 2019 – Present UK

Responsibilities include:

  • Project Management
  • Data analysis
  • Modelling
Lead Developer
Jan 2015 – Present UK

Responsibilities include:

  • Cycle uptake modelling
  • Software development
  • Deployment
Principle Investigator
Apr 2017 – Mar 2018 UK

Responsibilities include:

  • Project Management
  • Data analysis
  • Modelling


Feel free to get in touch in using the form below. It may be worth considering contacting me in other ways, however, including:

  • On GitHub, by commenting on an existing issue or discussion or creating a new one. I put this one first not because I love the world’s premier code-sharing side (although I do β™₯) but because I get a lot of software questions. For example: “I have got xx, data, can I get xx outputs using one of your tools?” It’s good to see these questions but often a most appropriate to ask in an open forum such as GitHub or StackOverflow, because:
    • You’re likely to get a response quicker
    • Other people can benefit from your answer (see here for a good example of how to ask a good question on GitHub)
    • I prioritise well-asked questions, ideally with a reproducible example, over vague questions sent directly to me
  • On Discord, a great place to ask questions about methods and technology. You can join the Geocompr Discord Server and ask questions here:
  • In a comment below one of the pages on this website. See the bottom of this page for an example of this in relation to the Propensity to Cycle Tool (note: you need a GitHub account to add comments in this way, as you do to ask questions on GitHub)
  • On social media where I can be found, hopefully with the aim of increasing the signal-to-noise and light-vs-heat ratios on such platforms
  • Via my work email address which you can find online if it’s directly related to my work