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Maria Iannario

University of Naples Federico II

About

Associate Professor in Statistics at UNINA. The main results of her work consist of the study and development of a class of statistical models used for the analysis of ordinal data. Specifically, she proved the identifiability of this class of models and extended the models for adapting them to non-standard situations as in multilevel/hierarchical contexts and when overdispersion or shelter effects are present. She has been visiting Fellow at Lancaster, Genève, Iowa Universities, London School of Economics, Athens University of Economics and Business, Technische Universität Dortmund. She has been awarded with grants with an international profile as a DAAD scholarship Research, Fulbright scholar and the Virtual Mobility Grant - Cost action FinAI (CA19130 – Fintech and Artificial Intelligence in Finance – Towards a transparent financial industry): https://fin-ai.eu/. She is the Principal Investigator of Erasmus+ KA131Blended Intensive Programme Advanced Analytics for Data Science (2022) and Methods for Fintech and Artificial Intelligence in Finance (2023). She received in 2023 an International Advanced Fellowship - Babes-Bolyai University Statistical Modelling Data Analytics for FinTech (SMART) supported by a grant of Ministry of Research, Innovation and Digitization Program 1 Subprogramme 1.2 - RDI Funding Excellence Projects, contract number 21PFE 2021. She is Associate Editor of Journal of the Royal Statistical Society – series C, Metrika, Statistical Modelling. She is a research author of over 100 papers in the field of statistical modeling, She has recently included Analytics in Health, Fintech, financial inclusion and inequality in her research interests.

Key Achievements and Outputs

Research Interests

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Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or Horizon Europe: Marie Skłodowska-Curie Actions. Neither the European Union nor the granting authority can be held responsible for them. This project has received funding from the Horizon Europe research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 101119635

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