1 Thomas Robinson
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Dr Thomas Robinson

Dr Thomas Robinson

Assistant Professor

Department of Methodology

Email
t.robinson7@lse.ac.uk
Room No
CON.1.07B
Office Hours
Please refer to StudentHub to book office hours
orcid
https://orcid.org/0000-0001-7097-1599
Connect with me

Twitter

Website

Languages
English
Key Expertise
Voter behaviour; money in politics; machine learning; neural networks

About me

Thomas Robinson is an Assistant Professor in the Department of Methodology. He received his PhD in Politics from the University of Oxford in 2020. Before joining LSE, he was an Assistant Professor in the Centre for Institutions and Political Behavior at Durham University.

Thomas' research uses tools from machine learning and causal inference to study questions related to money in politics, voter behaviour, and policy preferences. His ongoing projects include studying how voters respond to campaign finance information and how citizens' beliefs and behaviours are being shaped by the COVID-19 pandemic.

Thomas' methodological research is mainly centred on machine learning, causal inference, and experiments. He is particularly interested in neural network modelling, and his current projects include work on synthetic data, active learning, and missing data. As part of this research, Thomas has ongoing collaborations in both the education policy sector and tech industry.

Publications

When do voters respond to campaign finance disclosure? Evidence from multiple election types, Political Behavior, 2022, pp. 1-24.

Citizens from 13 countries share similar preferences for COVID-19 vaccine allocation priorities. (with Raymond Duch et al), Proceedings of the National Academy of Sciences, Vol. 118, No. 38 (September 2021).

Reply to Spreco, Schön, and Timpka: Perceived Corruption and Preferences for COVID-19 Vaccine Allocations (with Raymond Duch, Philip Clarke, Laurence Roope, and Mara Violato), Proceedings of the National Academy of Sciences, Vol. 119, No. 19 (May 2022).

How Campaigns Respond to Ballot Position: A New Mechanism for Order Effects (with Nelson Ruiz and Saad Gulzar), Journal of Politics, Vol. 84, No. 2 (April 2022), pp. 1256-1261.

The MIDAS Touch: Accurate and Scalable Missing-Data Imputation with Deep Learning (with Ranjit Lall), Political Analysis, Vol. 30, No. 2 (2022), pp. 179-196. 

Nativist Policy: the comparative effects of Trumpian politics on migration decisions (with Raymond Duch, Denise Laroze, and Constantin Reinprecht), Political Science Research and Methods, Vol. 10, No. 1 (2022), pp. 171-187.

Multi-modes for Detecting Experimental Measurement Error (with Raymond Duch, Denise Laroze, and Pablo Beramendi), Political Analysis, Vol. 28, No. 2 (2020), pp. 263-283.

Where Will the British Go? And Why? (with Raymond Duch, Denise Laroze, and Constantin Reinprecht), Social Science Quarterly, Vol. 100, No. 2 (2019), pp. 480-493.

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