Dr. Rachel Cavill

Biography

Rachel Cavill is an Assistant Professor in the Department of Data Science and Knowledge Engineering at Maastricht University. Her research focuses on method development for data integration of various types of omics data, including metabolomic and transcriptomic data. She is involved in domain adaptation within bioinformatics and applies advanced machine learning techniques to facilitate learning across different domains, such as organisms or tissue types. Rachel has developed a method called SetPCA, which utilizes background knowledge about variables to make multivariate methods, including PCA (Principal Component Analysis) and PLS (Partial Least Squares), more interpretable. Additionally, she explores applications of deep learning for feature extraction from biological images. Before joining Maastricht University, she earned her PhD from the University of York and has held research positions at Robert Gordon University and Imperial College London, contributing to various projects in computational systems medicine and toxicogenomics. Her diverse career reflects a strong commitment to advancing techniques in data science and bioinformatics.

Research Interests

Experience