Thematic Area 7 - Enabling Technologies

Annette Dariose Diffo Mboudjiho

Annette Dariose Diffo Mboudjiho

Big Data handling in Next-generation Particle and Astroparticle Physics Experiments

University of Bologna, Data Science and Computation

 

PhD student in Data Science and Computation, University of Bologna, Department of Physics and Astronomy. My research focuses on Big Data handling in Next-generation Particle and Astroparticle Physics Experiments, including real-time data acquisition, event filtering, and anomaly detection for large-scale facilities such as the HL-LHC, FCC, and ET. From Cameroon, I studied Physics at the Bachelor, then AI for Science Master at AIMS South Africa, later a Quantitative Life Sciences pre-PhD at ICTP.

 

Atefeh Ghanbari

Atefeh Ghanbari

Neuro-symbolic artificial intelligence for big data

University of Ferrara, PhD in Translational Neurosciences and Neurotechnologies

 

I'm holding an MSc in Artificial Intelligence – Robotics from Yazd University. My Master’s thesis focused on segmentation and recognition of pulmonary nodules in CT scans, and I published a paper titled “Lung Nodule Detection Using Fuzzy-Tsallis Entropy and SVM. I am also interested in LLMs and Probabilistic Logic Programming. I contributed as the second author to the paper “An Evaluation of Open Source LLMs for Neuro-Symbolic Integration.” I am passionate about research in Neuro-Symbolic AI.

Christina Karagianni

Christina Karagianni

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. 

 

Joshua Raphael Lemus Castilllo

Joshua Raphael Lemus Castilllo

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.

Rodrigo Pérez Ortiz

Rodrigo Pérez Ortiz

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.

 

 

Samira Johanna Breitling

Samira Johanna Breitling

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.