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 methodological development and data integration across various types of omics data, including metabolomic and transcriptomic data. She is particularly interested in domain adaptation in bioinformatics and how advanced machine learning methods can facilitate learning across different domains, such as organisms, tissues, and batches of data. One of her significant contributions is the development of SetPCA, a method that leverages background knowledge of variables to enhance the interpretability of multivariate methods, including Principal Component Analysis (PCA) and Partial Least Squares (PLS). Additionally, she applies deep learning techniques to extract features from biological images, further bridging the gap between computational methods and biological research. Rachel has a rich academic background, having completed her PhD at the University of York, England, and held several research positions, including at the Computer Science Department of Robert Gordon University in Aberdeen, and as a Research Associate in Computational Systems Medicine at Imperial College London.

Research Interests

Experience