Angelos Markos bio photo

Angelos Markos

Data Scientist, Professor, Runner

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Full CV: English / Greek

Selected Publications

Dimensionality reduction and clustering

  1. Greenacre, M., Groenen, P.J.F., Hastie, T., Iodice D'Enza, A., Markos, A., & Tuzhilina, E. (2022). Principal Component Analysis. Nature Reviews Methods Primers (to appear)

  2. Costa, E., Papatsouma, I., & Markos, A. (2022). Benchmarking distance-based partitioning methods for mixed-type data. Advances in Data Analysis and Classification (online first)

  3. Moschidis, S., Markos, A., & Thanopoulos, A. (2022). "Automatic" interpretation of Multiple Correspondence Analysis (MCA) results for non-expert users, using R programming. Applied Computing and Informatics

  4. Moschidis, O., Markos, A., & Chadjipadelis, T. (2022). Hierarchical clustering of mixed-type data based on barycentric coding. Behaviormetrika (online first).

  5. Iodice D' Enza, A., Markos, A., & Palumbo, F. (2021). Chunk-wise regularised PCA-based imputation of missing data. Statistical Methods & Applications, 31, 365–386.

  6. van de Velden, M., Iodice D'Enza, A., & Markos, A. (2019). Distance-based clustering of mixed data. WIREs Computational Statistics, 11(3), e1456. DOI:10.1002/wics.1456.

  7. Markos, A., Moschidis, O., & Chadjipantelis, T. (2019). Sequential dimension reduction and clustering of mixed-type data. International Journal of Data Analysis Techniques and Strategies, 12(3), 228–246.

  8. Markos, A., & Iodice D’Enza, A. (2017). A Framework for the Incremental Update of the Multiple Correspondence Analysis Solution. Italian Journal of Applied Statistics, 29(2-3), 217–231.

  9. Markos, A., & Iodice D’ Enza, A. (2016). Incremental Generalized Canonical Correlation Analysis. In A. Wilhelm, A. Kestler (eds), Analysis of Large and Complex Data, Studies in Classification, Data Analysis, and Knowledge Organization, pp. 185-194, Springer [Best Paper Award].

  10. Iodice D’ Enza, A., & Markos, A. (2015). Low-dimensional tracking of association structures in categorical data. Statistics and Computing, 25(5), 1009–1022.

Statistical Software

  1. Markos, A., Iodice D’Enza, A., & van de Velden, M. (2019). Beyond Tandem Analysis: Joint Dimension Reduction and Clustering in R. Journal of Statistical Software, 91(10), 1–24.

  2. Iodice D’Enza, A., Markos, A., & Buttarazzi, D. (2018). idm: Incremental Decomposition Methods in R. Journal of Statistical Software, Code Snippets, 86(4), 1–24.

  3. Markos, A., Menexes, G., & Papadimitriou, I. (2010). The CHIC Analysis Software v1.0. In H. Loracek-Junge & C. Weihs (eds), Classification as a Tool for Research, Proceedings of the 11th IFCS Conference. Springer Berlin, pp. 409–416.

Test Validations & Adaptations

  1. Kokkinos, C.M., Markos, A., Michaelides, M., & Voulgaridou, I. (2020). Disentangling the factorial structure of the Greek Big Five Questionnaire for Children – Short Form. Personality and Individual Differences, 156, 109742.

  2. Mavrommatidou, S., Gavriilidou, Z., & Markos, A. (2019). Development and Validation of the Strategy Inventory for Electronic Dictionary Use (S.I.E.D.U.). International Journal of Lexicography, ecz015.

  3. Markos, A., & Kokkinos, C.M. (2017). Development of a Short Form of the Greek Big Five Questionnaire for Children (GBFQ-C-SF): Validation among Preadolescents. Personality and Individual Differences, 112, 12–17.

  4. Markos, A., Boubonari, T., Mogias, A., & Kevrekidis, T. (2017). Measuring Ocean Literacy in Pre-service Teachers: Psychometric Properties of the Greek Version of the Survey of Ocean Literacy and Engagement (SOLE). Environmental Education Research, 23(2), 231–251.

  5. Kokkinos, C.M., & Markos, A. (2017). The Big Five Questionnaire for Children (BFQ-C): Factorial Invariance across Sex and Age in a Greek Sample of Preadolescents. European Journal of Psychological Assessment, 33(2), 129–133.

Databases: Scopus - Google Scholar - ResearchGate


I am current developer and maintainer of the following R packages

  • clustrd - Joint Dimension Reduction and Clustering in R
  • idm - Incremental Decomposition Methods in R (incremental versions of Principal Components Analysis and Multiple Correspondence Analysis)
  • caGUI - a Tcl/Tk GUI for the functions of the ca package.

and the following standalone software written looong ago in Matlab & Delphi:

  • CHIC Analysis - Correspondence & HIerachical Cluster Analysis
  • Procrustes - Generalized Procrustes Analysis (in Greek)