Agathe Balayn

Web Information Systems Group, Department of Software Technology, Faculty of Electrical Engineering, Mathematics and Computer Science, TU Delft

Office W4.920

4th floor, Building 28

V Mourik Broekmanweg 6

2628XE, Delft

Netherlands

I am a PhD candidate in Computer Science at the Web Information Systems group (WIS) of the Faculty of Electrical Engineering, Mathematics and Computer Science, at Delft University of Technology.

My research is focused on uncovering, understanding, and mitigating some of the harms that the deployment of machine learning systems into society can raise. The harms that I study are related to issues of biases in the outputs of the systems, potentially resulting in safety hazards or discrimination and unfairness. While I’m interested in any kind of machine learning systems, my research primarily focuses on the ones using image data –machine learning based computer vision– (or sometimes tabular data) to perform classification or regression tasks.

In my research, I aim at making contributions of varying nature using a mixed methodology.

  • Empirical studies. I study how practitioners develop, deploy, and evaluate machine learning systems using various tools. This allows to identify patterns and limitations in existing practices.
  • Methods. I develop algorithmic methods (e.g., relying on explainability methods) to facilitate the identification of the potential harms of developed systems before they occur.
  • Other tools. I create user-interfaces to make existing methods more usable by practitioners, and to study their actual use in practice. Besides, I would like to develop other kinds of tools (e.g., conceptual frameworks, documentations, etc.) to further support machine learning practitioners in their daily practice with regard to harms.
  • Literature surveys. I perform rigorous surveys of the scientific literature, to understand harms and existing approaches towards assessing or mitigating these harms, and to identify possible necessary re-orientations of the research based on insights from the empirical studies.

Daily, in my research, I work in close collaboration with Jie Yang and Seda Guerses on these topics. My PhD promotors are Alessandro Bozzon and Geert-Jan Houben.

Prior to that, I had the opportunity to work on other machine learning -related topics pertaining to the automatic detection of hate speech, the automatic translation of Japanese sign language to Japanese, and to the human-guided control of a robotic arm.

I hold an MSc degree in Computer Science from the TU Delft, the Netherlands, and an engineering diploma (with its MSc degree equivalence) in Systems and Control from the ENSTA ParisTech, Institut Polytechnique de Paris, France.

You can find my CV here.