Department of Radiology, University of Cambridge School of Clinical Medicine.
Email:Leonardo Rundo Tel.: + 44 (0)1223 256255
Leonardo Rundo received his Bachelor’s and Master’s Degrees in Computer Science Engineering from the University of Palermo, Palermo, Italy, in 2010 and 2013, respectively. His Master thesis area was on adaptive data-driven Graphical User Interfaces (GUIs) based on DICOM for medical imaging software. Since December 2013, he was Research Fellow at the Institute of Molecular Bioimaging and Physiology, National Research Council of Italy (IBFM-CNR), Cefalù (PA), Italy. He obtained his Ph.D. in Computer Science with a thesis on “Computer-Assisted Analysis of Biomedical Images”, under the supervision of Prof. G. Mauri, at the University of Milano-Bicocca, Milan, Italy, in February 2019. During his Ph.D. programme, he was invited as Visiting Scholar at the Department of Cancer Biology (Vanderbilt University, Nashville, TN, USA), the Department of Creative Informatics (The University of Tokyo, Tokyo, Japan), and the Computer Laboratory (University of Cambridge, Cambridge, UK).
Since November 2018, he is a Research Associate at the Department of Radiology of the University of Cambridge, Cambridge, UK. His research activities are focused on oncological image analysis, strictly collaborating also with the CRUK Cambridge Centre. These multidisciplinary efforts aim at performing data integration analyses to precisely characterize the cancer mechanisms at the single individual level, by appropriately combining the heterogeneous patient’s information conveyed by multiparametric or multimodal imaging datasets (exploiting advanced Machine Learning and Radiomics approaches) and high-throughput technologies.
His main scientific interests include Digital Image Processing, Biomedical Image Analysis, Machine Learning, Computational Intelligence, Natural Computing, Computational Biology, and High-Performance Computing. His research contributions concern oncological imaging (Magnetic Resonance Imaging, Computed Tomography, and Positron Emission Tomography), multimodal image registration and fusion, High Intensity Focused Ultrasounds, radiation therapy, and neuro-radiosurgery, as well as live-cell imaging.