Methodologies and technologies of data science and data analytics: beyond the analytics of high energy physics big data
University of Ferrara, PhD in Physics
I am Christina Karagianni from Greece. I hold a Bachelor's degree in Physics and two Master's degrees - one in Nuclear Physics and another in Machine Learning and Data Science. Through this PhD, I aim to combine my interdisciplinary background to contribute to understanding fundamental particles and the origin of matter. My research focuses on the Deep Underground Neutrino Experiment (DUNE), a global effort to study neutrino oscillations, proton decay, and supernova neutrinos.
Data-driven modeling of brain circuits for advanced digital twins
University of Modena and Reggio Emilia, PhD in Neuroscience
Born in Guatemala, I studied Physics before moving to Mexico for an M.Sc. in Neurobiology. I later merged these paths through a diploma in Quantitative Life Sciences at the International Center for Theoretical Physics, in Italy. Now I'm a PhD student in Neuroscience at the University of Modena and Reggio Emilia, where I use computational models, graph theory and information theory to study the dynamical transition between brain states, with a particular interest in conscious/unconscious states.
Computational Approaches in (Big) Data-driven Medical Modeling
University of Bologna, PhD in Mathematics
I am a PhD candidate at the Faculty of Mathematics, University of Bologna. Previously, I was part of the CHORAL group led by Jean Barbier at ICTP. I hold a Master’s in theoretical physics from EPFL, where my thesis was advised by Lenka Zdeborová. My research lies at the intersection of machine learning theory, high-dimensional statistics, and statistical physics, focusing on how data and model architecture shape learning in high dimensions, with potential applications in medical modeling.
Mathematical Modelling for Medical Practice
University of Bologna, PhD in Mathematics
I am a PhD student at the University of Bologna and hold a Master’s degree in Bioinformatics from the University of Tübingen. My research primarily focuses on mathematical modeling of Alzheimer’s disease. This includes various approaches to simulate and predict the spread of Tau tangles and Amyloid-beta oligomers in the brain. By leveraging Physics-Informed Neural Networks, I aim to gain deeper insights into the dynamics of neurodegeneration and contribute to personalized medicine.