Martin Lukac

Martin Lukac

LSE Fellow in Computational Social Science

Department of Methodology

Telephone
TBC
Room No
COL 7.07
Office Hours
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Languages
Czech, English, German, Russian, Slovakian
Key Expertise
Computational Social Science, Network Analysis, Agent-Based Modelling

About me

Martin Lukac is an LSE Fellow in Computational Social Science in the Methodology Department at the London School of Economics. He is working towards his PhD in Sociology at KU Leuven where he also studied MSc in Statistics and MSc in Social Policy Analysis. Before starting his PhD, Martin worked as a Data Scientist at IBM. For more information, see https://mblukac.github.io.

Research interests

Martin’s methodological research interests focus on latent variable modelling, causal inference with observational and experimental data, social network analysis, agent-based modelling, and survey methodology.

His applied research revolves around labour market inequalities, online labour market platforms, and skill use—especially in context of digitalisation and automation. His is interested in using tools from complexity systems science to generate new insights and understanding of ongoing labour market processes. Martin also worked on welfare attitudes in Europe.

Expertise Details

Computational Social Science; Network Analysis; Agent-Based Modelling

Publications

 

  • Lukac, M. and Grow, A. (2020). Reputation systems and recruitment in online labor markets: insights from an agent-based model. Journal of Computational Social Science. Online First.
  • Doerflinger, N., Pulignano, V. and Lukac, M. (2019). The social configuration of labour market divides: an analysis of Germany, Belgium and Italy. European Journal of Industrial Relations 26 (2): 207-223.
  • Lukac, M., Doerflinger, N. and Pulignano, V. (2019). Developing a cross-national comparative framework for studying labour market segmentation: measurement equivalence with latent class analysis. Social Indicators Research 145: 233–255.