Machine Learning for Precision Medicine researcher
My main research focus is deep representation learning applied to sequencing and imaging data for the study of cancer, with a secondary focus on interpretability and explainability (XAI).
One of the greatest innovations that deep learning brought to the field of data science is the capability to seamlessly integrate different sources of information in a unified framework that can be used to make new predictions. The field of representation learning revolves around the techniques and methods necessary to create a representation of the data suitable for analysis and inference. Interpretability of such representations is also a fundamental component to connect the biological domain knowledge and the results obtained through machine learning and data analysis.
During my PhD project at the Max-Planck Institute for Intelligent Systems in Tübingen, I aim to study the use of deep learning models to lean rich data representations from datasets such as The Cancer Genome Atlas (TCGA), and Genomics of Drug Sensitivity in Cancer (GDSC). With a focus on multi-view representation learning, through which we can combine the different sources of information such as phenotypic and -omics data, and an exploration of the techniques to interpret the learned embeddings, I will employ these rich representations for tasks such as mode of action prediction and chemical genetic interactions discovery.
My passion is the application of modeling methods, data mining and analysis applied to the medical field. While earning my Physics bachelor and master degrees from the Universities of Turin and Trent, I focused on the field of medical physics. My works in this field, which ranged from simulations of contrast media for radiotherapy, to the applications of nanomaterials for drug delivery, left me with a deep fascination for multidisciplinary approaches to tackle medical problems. I further explored my deep interest for the field of machine learning and data science at the University of Edinburgh, where I successfully completed the Artificial Intelligence MSc. In December 2019, I joined MPI-IS in Tübingen, as part of the Epi-Logos group lead by Gabriele Schweikert and the Empirical Inference department under the supervision of Bernhard Schölkopf.