Info
Larissa de Ruijter
Work address
Biosystems Data Analysis, University of Amsterdam
Room C2.202, Science Park 904, 1098 XH, Amsterdam
Email: l.deruijter@uva.nl
Professional Career
I completed a Bachelor’s degree in Pure Mathematics at the University of Amsterdam in 2021 and a Master’s degree in Artificial Intelligence in 2023, also at the University of Amsterdam. I have always been interested in both mathematics and the life sciences, which motivated me to work on several interdisciplinary projects during my studies.
As part of my bachelor’s, I completed a research internship at the Swammerdam Institute for Life Sciences, where I developed computational models to study how excitatory and inhibitory neurons maintain balance in the cortical microcircuit. After my bachelor’s, my interest in the potential of artificial intelligence to solve real-world problems, including in biology, led me to pursue a master’s in AI.
I completed my master’s with a research internship at the QUVA Lab (Qualcomm-UvA Research Group), where I worked on geometric deep learning and cryo-electron microscopy (Cryo-EM)—a technique for reconstructing the 3D structure of proteins. Specifically, I investigated how equivariant encoders affect convergence issues when applying autoencoders to the Cryo-EM reconstruction problem.
As of March 2025, I am a PhD candidate in the Biosystems Data Analysis group, where I work on developing deep learning methods for single-cell sequencing data analysis.
Research
My PhD research focuses on developing deep learning methods for single-cell sequencing data analysis, with an emphasis on integrating biological knowledge to improve model performance and interpretability. I aim to explore how prior biological information can be leveraged in deep learning approaches to gain new insights into biological questions, for example on cellular heterogeneity, cell differentiation during development, or cell-cell communication.