Recent publications, collaborations, events and milestones, followed by the migrated archive from the former website.
A new interactive geographic atlas to explore Italy’s PRIN 2026 research projects, including the standard, Hybrid and Synergy programmes. Developed by M.O.D.A.L. and hosted at Federico II.
Explore the PRIN 2026 Atlas ↗Professor Zenglin Xu (Fudan University) will speak on Trustworthy Federated Learning: Toolboxes, Benchmarks, and Models at the Department of Mathematics and Applications, Federico II.
Seminar details and poster →Led by Prof. Francesco Piccialli, SCULPT launches a two-year research programme within the Federico II STAR Junior PI Grants, exploring modular Digital Twins, Generative AI and Multi-Agent Systems.
Explore the SCULPT project →Published in Applied Energy, SAGE introduces energy-aware client selection that jointly considers remaining battery, data divergence and the use of renewable energy.
Read the paper ↗The FU-MARL research framework brings federated unlearning together with multi-agent reinforcement learning for trustworthy Industrial IoT systems.
Read the paper ↗Two complementary contributions address privacy-preserving collaborative learning in drug discovery and practical, reproducible AI modelling protocols.
Federated Learning chapter ↗M.O.D.A.L. welcomed Prof. Hangli G. from The University of Tokyo for an exchange on Artificial Intelligence, data, cities and future research directions.
LinkedIn update ↗M.O.D.A.L. contributed with FLIP4Tab in the Main Research Track and with the AGENSYS workshop on agentic systems and distributed intelligence.
Event details →A new trustworthy-AI contribution combining generative surrogates and optimal transport to remove a client's contribution without restarting federated training from scratch.
Paper ↗Cross-city traffic prediction is reformulated around sharing transferable temporal knowledge while retaining city-specific spatial structure locally.
Paper ↗Deep learning and geophysics are combined to estimate earthquake focal mechanisms in the Campi Flegrei caldera under noisy and incomplete-data conditions.
Paper ↗Diffusion-based voice editing and federated fine-tuning enable privacy-aware personalization while keeping raw speech data local.
Paper ↗The milestone marks a new stage in Fabio Giampaolo's academic career and in the continuing growth of the M.O.D.A.L. research group.
People →The group announced acceptance of a federated prompt-learning paper in the IEEE ICDM 2026 Main Research Track alongside a comprehensive review of loss-function design for Physics-Informed Neural Networks.
Publications →DON-B-STRESSED and secure IoMT research published in Information Sciences.
The Industry 4.0 Explainable AI survey recognized as a Web of Science Highly Cited Paper.
Marzia Canzaniello joined the M.O.D.A.L. research group.
Research on structuring e-health booking data through Knowledge Graphs.
Dutch Polymer Institute project on deep-learning-aided GPC-IR fingerprinting of polyolefin mixtures.
“Cut the Peaches” received the Best Paper Award at UDML@ICDM 2022.
A data-driven neural model for ground-motion prediction from induced seismicity.
Publication of the survey “Where we are and What’s Next” in the Journal of Scientific Computing.
Daniela Annunziata and Martina Savoia joined the laboratory.
The survey on deep learning in medicine was recognized as a Web of Science Highly Cited Paper.
First research results of the BIOCHIP project published in Biosensors and Bioelectronics.
Predictive analytics for smart parking using Deep Learning and IoT data.
Forecasting medical bookings through multi-source time-series fusion.
PNRR support for strengthening Italian infrastructure for omics data and bioinformatics.
Rokas Gipsikis joined the group as a visiting Ph.D. researcher with a focus on Explainable AI.
MariaPia De Rosa and Stefano Izzo joined the laboratory as Ph.D. students.
Research on automatic segmentation and classification of salivary-gland tumours with Deep Learning.
Victor Rodriguez joined the research community as a visiting researcher.
Publication on the role of Artificial Intelligence in fighting the COVID-19 pandemic.
Industrial Ph.D. project “Predictive Data Intelligence for Cities’ Territory and Sustainability”.
Edoardo Prezioso joined the laboratory as a Ph.D. student.
