Mark Birkin

3.3k total citations
110 papers, 1.9k citations indexed

About

Mark Birkin is a scholar working on Management Science and Operations Research, Transportation and Demography. According to data from OpenAlex, Mark Birkin has authored 110 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Management Science and Operations Research, 33 papers in Transportation and 21 papers in Demography. Recurrent topics in Mark Birkin's work include demographic modeling and climate adaptation (39 papers), Urban Transport and Accessibility (23 papers) and Insurance, Mortality, Demography, Risk Management (15 papers). Mark Birkin is often cited by papers focused on demographic modeling and climate adaptation (39 papers), Urban Transport and Accessibility (23 papers) and Insurance, Mortality, Demography, Risk Management (15 papers). Mark Birkin collaborates with scholars based in United Kingdom, China and United States. Mark Birkin's co-authors include Martin Clarke, Graham Clarke, Philip Rees, Graham Clarke, Alison Heppenstall, Paula Williamson, Michael Clarke, Nick Malleson, Belinda Wu and Alan Wilson and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Social Science & Medicine.

In The Last Decade

Mark Birkin

108 papers receiving 1.8k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Mark Birkin 629 563 355 329 274 110 1.9k
Alison Heppenstall 278 0.4× 783 1.4× 98 0.3× 255 0.8× 434 1.6× 85 2.3k
Alex Singleton 106 0.2× 1.0k 1.8× 96 0.3× 447 1.4× 292 1.1× 108 2.7k
Karima Kourtit 118 0.2× 729 1.3× 92 0.3× 677 2.1× 223 0.8× 194 2.5k
Prem Chhetri 89 0.1× 418 0.7× 54 0.2× 231 0.7× 258 0.9× 123 2.2k
Denzil G. Fiebig 244 0.4× 142 0.3× 74 0.2× 1.5k 4.6× 89 0.3× 90 2.6k
Lanndon Ocampo 572 0.9× 97 0.2× 79 0.2× 190 0.6× 136 0.5× 178 2.3k
Pieter Hooimeijer 64 0.1× 329 0.6× 316 0.9× 567 1.7× 192 0.7× 127 3.0k
Daniel Arribas‐Bel 79 0.1× 749 1.3× 59 0.2× 604 1.8× 263 1.0× 92 2.1k
Paul Waddell 295 0.5× 2.4k 4.2× 141 0.4× 1.3k 4.0× 945 3.4× 89 4.4k
Aloys Borgers 59 0.1× 1.4k 2.4× 71 0.2× 774 2.4× 456 1.7× 114 2.6k

Countries citing papers authored by Mark Birkin

Since Specialization
Citations

This map shows the geographic impact of Mark Birkin's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Mark Birkin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark Birkin more than expected).

Fields of papers citing papers by Mark Birkin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mark Birkin. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Mark Birkin. The network helps show where Mark Birkin may publish in the future.

Co-authorship network of co-authors of Mark Birkin

This figure shows the co-authorship network connecting the top 25 collaborators of Mark Birkin. A scholar is included among the top collaborators of Mark Birkin based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mark Birkin. Mark Birkin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Birkin, Mark, et al.. (2025). Digital twins and AI for healthy and sustainable cities. Computers Environment and Urban Systems. 120. 102305–102305. 1 indexed citations
2.
Luo, Man, Bowen Du, Wenzhe Zhang, et al.. (2023). Fleet Rebalancing for Expanding Shared e-Mobility Systems: A Multi-Agent Deep Reinforcement Learning Approach. IEEE Transactions on Intelligent Transportation Systems. 24(4). 3868–3881. 13 indexed citations
3.
Clark, Stephen, et al.. (2023). Retail banking closures in the United Kingdom. Are neighbourhood characteristics associated with retail bank branch closures?. Transactions of the Institute of British Geographers. 49(3). 3 indexed citations
4.
Clark, Stephen, Michelle Morris, Nik Lomax, & Mark Birkin. (2021). Can a data driven obesity classification system identify those at risk of severe COVID-19 in the UK Biobank cohort study?. International Journal of Obesity. 45(10). 2281–2285. 2 indexed citations
5.
Clark, Stephen, et al.. (2021). Understanding Barriers to Novel Data Linkages: Topic Modeling of the Results of the LifeInfo Survey. Journal of Medical Internet Research. 23(5). e24236–e24236. 15 indexed citations
6.
Morris, Michelle, et al.. (2021). Local and Application-Specific Geodemographics for Data-Led Urban Decision Making. Sustainability. 13(9). 4873–4873.
7.
Clark, Stephen, et al.. (2021). Clustering Accelerometer Activity Patterns from the UK Biobank Cohort. Sensors. 21(24). 8220–8220. 8 indexed citations
8.
Spooner, Fiona, Jesse F. Abrams, Karyn Morrissey, et al.. (2021). A dynamic microsimulation model for epidemics. Social Science & Medicine. 291. 114461–114461. 20 indexed citations
9.
Clark, Stephen, et al.. (2021). Dietary Patterns Derived from UK Supermarket Transaction Data with Nutrient and Socioeconomic Profiles. Nutrients. 13(5). 1481–1481. 20 indexed citations
10.
Clark, Stephen, Mark Birkin, Nik Lomax, & Michelle Morris. (2020). Developing a whole systems obesity classification for the UK Biobank Cohort. RePEc: Research Papers in Economics. 2 indexed citations
11.
Morris, Michelle, et al.. (2020). Assessing diet in a university student population: a longitudinal food card transaction data approach. British Journal Of Nutrition. 123(12). 1406–1414. 9 indexed citations
12.
Clark, Stephen, Mark Birkin, Nik Lomax, & Michelle Morris. (2020). Can a data driven obesity classification system identify those at risk of severe COVID-19 in the UK Biobank cohort study?. OSF Preprints (OSF Preprints). 1 indexed citations
13.
Wilkins, Emma, Amy Downing, Adam Drewnowski, et al.. (2020). Evidence from big data in obesity research: international case studies. International Journal of Obesity. 44(5). 1028–1040. 3 indexed citations
14.
Birkin, Mark, Emma Wilkins, & Michelle Morris. (2019). Creating a long-term future for big data in obesity research. International Journal of Obesity. 43(12). 2587–2592. 4 indexed citations
15.
Morris, Michelle, et al.. (2018). Identifying Methods for Monitoring Foodborne Illness: Review of Existing Public Health Surveillance Techniques. JMIR Public Health and Surveillance. 4(2). e57–e57. 20 indexed citations
16.
Morris, Michelle, Emma Wilkins, Kate A. Timmins, et al.. (2018). Can big data solve a big problem? Reporting the obesity data landscape in line with the Foresight obesity system map. International Journal of Obesity. 42(12). 1963–1976. 29 indexed citations
17.
Birkin, Mark, et al.. (2014). The achievements and future potential of applied quantitative geography: A case study. Geographia Polonica. 87(2). 179–202. 5 indexed citations
18.
Khawaldah, Hamzah, Mark Birkin, & Graham Clarke. (2012). A review of two alternative retail impact assessment techniques: the case of Silverburn in Scotland. Town Planning Review. 83(2). 233–260. 10 indexed citations
19.
Birkin, Mark, et al.. (2012). Investigating the Behaviour of Twitter Users to Construct an Individual-Level Model of Metropolitan Dynamics.. 39(34). 16–16. 3 indexed citations
20.
Malleson, Nick & Mark Birkin. (2011). Towards victim-oriented crime modelling in a social science e-infrastructure. Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences. 369(1949). 3353–3371. 11 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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