I completed both my bachelor’s and master’s degrees in Artificial Intelligence (AI) at the University of Amsterdam while simultaneously pursuing a bachelor's degree in Theatre. During my master’s in AI, I specialized in geometric deep learning, a subfield that incorporates geometric properties like distance, shape, and relative position into deep learning methods. This enables AI to effectively process flat (not Euclidean) data, such as graphs, molecules, and manifolds.
While working on my thesis, I got accepted into the SGI fellowship program at Massachusetts Institute of Technology (MIT) in the United States. This opportunity allowed me to further develop my knowledge about geometry and geometric deep learning.
Alongside my studies, I worked at VHTO, the Dutch expertise center of gender bias in Science, Technology, Engineering, and Mathematics, also known as STEM. In this role, I engaged with primary and high schools, conducting coding workshops and sharing my experiences as a role model for aspiring tech enthusiasts.
Now, as a PhD student at the AI for Oncology group, I'm excited about applying my acquired knowledge and skills to address crucial challenges in cancer research.
I like to combine fundamental AI with medical knowledge to advance both AI and cancer research. My focus is on creating innovative deep learning solutions that not only contribute to fundamental technical AI research but also aim to improve cancer diagnosis and treatment, hopefully contributing to this fast-developing field.
As a PhD student, I am involved in the aiEMBRACE project, which aims to revolutionize breast cancer care using deep learning techniques. Our project aims to achieve several key objectives, including predicting the benefits of breast MRI for women based on their mammograms, assisting in the interpretation of breast MRIs, personalizing treatment plans based on response predictions, and forecasting disease recurrence and long-term outcomes. Our goal is to integrate AI throughout the entire patient journey - from risk assessment and diagnosis to treatment and surveillance - with the aim of transforming breast cancer care.
In addition, in a recent study, I introduced a novel artificial neural network tailored specifically for esophageal cancer research. This model efficiently encodes unlabeled data and shows promise in modeling the progression of Barrett’s Esophagus, a precursor lesion to esophageal cancer, through analysis of pathological images. Such a model could provide valuable insights into disease progression and potentially uncover novel biomarkers for individual patient care.
Besides the technical aspect of my work, I am passionate about inspiring the next generation of students, especially girls, to pursue a career in STEM fields. For several years, I have been acting as a role-model, teaching coding workshops in schools, aimed to show girls how fun it is! Through sharing my experiences in studying technology, I hope to break stereotypes. As someone with a background in both theater and AI, my goal is to demonstrate that anyone can excel in tech or AI. You don't need to conform to the stereotypical image of a "tech person" to have a genuine interest and skill in technology. Whether you're passionate about arts, fashion, or languages, you can also find your place in the world of computers, math, and programming.
Anyone can do AI! Achieving success in this field is more about dedicated hard work than being exceptionally technical or talented in mathematics or physics from a young age. You can go a long way by putting in the effort, and remember, you can always acquire the necessary math and programming skills later on. The key is determination and a willingness to learn.