Maria Heuss

I am a PhD candidate at the UvA under the supervision of Maarten de Rijke. In my research I focus mostly on questions around fairness and explainability within the field of Information Retrieval. Currently I am most interested in how uncertainty about different assumptions that we make when creating a ranking model interacts with the fairness and explainability of models as well as in the intersection of fairness and explainability.

Background

Intrigued by patterns and puzzles from a young age, I pursued Mathematics at Freiburg, earning my Bachelor’s degree (with a final grade of 2.2, where 1 is the best and 4 is the passing minimum) and my Master’s degree (with a final grade of 1.1) including two Erasmus exchange years in Utrecht, the Netherlands. My Master’s research was primarily in pure mathematics, focusing on algebraic topics. After completing my studies, I shifted my focus to Artificial Intelligence, seeing it as a field where I could have a more direct impact. I interned as a data-scientist at Green-Pocket and worked as a Deep Learning Scientist at Plumerai, researching binarized neural networks, before deciding to return to academia.

Advocating for Diversity and Inclusion

Driven by personal experiences and the stories of others, I have made it my mission to improve working environment for individuals from minority groups and those who struggle in the prevailing work environments of our field. I aim to raise awareness about the diverse needs and working styles of individuals and actively contribute to shaping a more inclusive culture within my current group. Additionally, I organize meetups for women and gender minorities in AI several times a year. I am eager to learn more about the experiences and challenges of others that I may not yet be aware of.