cv

PhD, Computational Biology

• Improving and scaling deep (self-)supervised models of the gene regulatory code

MSc, Informatics

• Master thesis: Self-supervised learning for mass spectrometry

BSc, Informatics

• Bachelor thesis : Generative models for protein folding

Research associate

Data Engineering Intern, Research Scientist Intern

• Scooby, Probabilistic Modeling in Genomics, CSHL, talk
• Scooby and Flashzoi, Aerts lab, KU Leuven, invited talk

• scooby: Sequence-to-function modeling at single-cell resolution, Kundaje lab, Stanford University, online talk
• Species LMs and nucleotide dependencies, Buenrostro lab, Harvard University, talk
• Species LM, EMBL Symposium: AI and biology, Heidelberg, poster

• Species-aware DNA language models, Kipoi Summit, talk
• Species LMs, ISMB, Lyon, poster

• Deep learning-based guided mutations improve de novo sequencing, ISMB, Madison, poster