Research Interests

  • Gender Inequality & Gender Bias
  • Role of AI in Migration, Asylum and Border Control
  • Social Consequences of AI Systems
  • Fairness in Automated-Decision Making (ADM)
  • Survey Methodology

Short Description

Clara Strasser Ceballos holds a Master's degree in Statistics and a Bachelor's degree in Economics from the University of Munich (LMU). In her Master's thesis, she used a machine learning algorithm to identify risk factors associated with psychological intimate partner violence (IPV) against women in Mexico. This involved meticulous handling of diverse survey datasets from Mexico and careful tuning of the machine learning algorithm to identify groups of women most at risk of experiencing psychological IPV.

From 2021 to 2022, Clara worked as a research assistant at the ifo Institute in Munich, where she gained extensive insights into policy-oriented empirical economic research and made statistical contributions to various research projects. In 2023, Clara worked as a research assistant and student statistical consultant in the Statistical Consulting Lab (StaBLab) at the LMU. During her time at the StaBLab, Clara consulted undergraduate and postgraduate students working on their Bachelor's/Master's theses and dissertations in the fields of psychology, social sciences and communication. Additionally, Clara works as a mentor and social media coordinator for the women's refugee project Juno Munich.

Following the completion of her Master's degree in the winter semester of 2023/24, Clara continued her academic journey at LMU, focusing her research on investigating the social consequences of AI systems and their role in perpetuating social inequality. Her goal is to leverage data science for social good, thereof by addressing and preventing the social inequalities exacerbated by AI systems.