Massimiliano Sgroi is an Associate Professor at the Università Politecnica delle Marche (UNIVPM), affiliated with the Department of Sciences and Engineering of Matter, Environment and Urban Planning (SIMAU). His research focuses on Environmental Engineering , particularly in Water Treatment , Sustainable Technologies , and Pollution Control . University: Università Politecnica delle Marche (UNIVPM) Department: SIMAU Email: m.sgroi@univpm.it His recent publications highlight expertise in PFAS removal , Life Cycle Assessment , and advanced oxidation processes . Key projects include stormwater reuse risk management, microplastics analysis, and circular economy strategies for wastewater treatment.
Serena Summa is a Researcher at the Department of Materials, Environmental Sciences and Urban Planning (SIMAU) within the Faculty of Engineering at Polytechnic University of Marche in Ancona, Italy. Her academic profile includes active research in building engineering with a focus on energy efficiency and sustainable design solutions. Her research spans multiple interdisciplinary areas including: Thermal performance analysis of innovative building materials and facade systems HVAC optimization through AI-driven automation and data analytics Indoor air quality management in educational and heritage buildings Sustainable cooling technologies including water mist systems Building simulation methodologies and energy standardization Her recent publications demonstrate consistent focus on experimental validation of building technologies, with particular emphasis on Mediterranean climate adaptations. Research frequently combines field measurements with computational modeling approaches across educational, residential and heritage contexts. She maintains active university affiliation with contact information including email (s.summa@univpm.it) and phone (0712204310), located at Via Brecce Bianche 12 in Ancona.
Alberto Tazioli serves as an Associate Professor in the Department of Materials, Environmental and Urban Engineering Sciences at the Università Politecnica delle Marche (UNIVPM) in Ancona, Italy. His academic specialization falls under GEOS-03/B - Geologia applicata (Applied Geology). Professor Tazioli maintains regular office hours on Tuesdays (11:15-13:00) and Wednesdays (9:30-10:45), with appointments arranged via email or Teams. His contact information includes phone number 071 2204719 and email a.tazioli@staff.univpm.it, with his office located at via Brecce Bianche 12. Professor Tazioli's research spans multiple domains within hydrogeology and applied geology, with particular expertise in groundwater systems, earthquake-hydrogeology interactions, isotopic hydrology, and karst aquifer characterization. His work integrates field investigations with advanced modeling approaches to understand complex water systems in mountainous regions, particularly in Central Italy. He frequently employs tracer tests, stable isotope analysis, and geomechanical surveys to investigate hydrological processes and their response to seismic events. His publications reveal strong methodological rigor and regional focus on Mediterranean hydrogeological systems. Analysis of Professor Tazioli's recent publications (2023-2025) reveals a strong focus on understanding how seismic events impact groundwater systems, particularly in the Central Apennines region of Italy. His research combines traditional hydrogeological methods with innovative approaches like UAV-based fracture mapping and machine learning for groundwater level prediction. A recurring theme is the application of isotopic techniques to delineate recharge areas and understand water origin in complex mountain catchments. His work demonstrates increasing sophistication in analytical approaches while maintaining practical applications for water resource management and natural hazard assessment. Professor Tazioli has made significant contributions to documenting the hydrogeological response to the 2016-2017 Central Italy seismic sequence, particularly regarding how earthquakes alter groundwater flow paths and chemistry. His research on the Montagna dei Fiori carbonate aquifer, Mt. Conero area, and Sibillini Mountains provides valuable insights into Mediterranean karst systems and their vulnerability to seismic activity. His work bridges fundamental hydrogeological science with practical applications for floodplain management, landslide assessment, and water resource sustainability in seismically active regions.
Raffaella Burioni is a Full Professor of Theoretical Physics in the Department of Mathematics, Physics and Computer Science at the University of Parma. She serves as Chair of the Non-Linear and Statistical Physics Division of the European Physical Society (EPS) and co-founded the Italian Society of Statistical Physics (SIFS), where she holds the position of Vice President. Her academic leadership includes directing the Ph.D. School in Physics and previously managing quality assurance for the Master's program in Physics (2017-2023). Her educational background includes an MS in Physics with distinction from the 2nd University of Rome and a PhD in Theoretical Physics from the University of Rome 'La Sapienza'. Postdoctoral experience spans the Theoretical Physics Laboratory of the École Normale Supérieure in Paris, the University of Milan, and the National Institute for the Physics of Matter (INFM). Prof. Burioni's research centers on equilibrium and non-equilibrium statistical physics, with deep expertise in graph theory, complex networks, random walks, and stochastic processes. She pioneers interdisciplinary applications to biological systems, neuroscience, and machine learning. Her work on rare events and anomalous diffusion has established fundamental principles like the 'single big jump' mechanism in transport phenomena. Recent investigations bridge statistical physics with neural network theory, examining kernel renormalization and feature learning in deep architectures. Analysis of her 15 most recent publications (2022-2025) reveals three dominant trends: (1) Theoretical advances in rare event statistics for jump processes and extreme value theory, (2) Network-based epidemic modeling incorporating adaptive temporal dynamics and simplicial structures, and (3) Machine learning physics connecting neural network theory to statistical mechanics through Bayesian effective actions and kernel methods. Her work consistently demonstrates how statistical physics principles solve complex problems across disciplines. Her scientific accolades include: Two-time recipient of the Enrico Persico Prize from the Accademia Nazionale dei Lincei Fellow of the Institute for Scientific Interchange (ISI) since 2014 American Physical Society Outstanding Referee (2018) Fellow of the European Centre for Living Technology (2020) As Director of the Ph.D. School in Physics, she mentors doctoral candidates while serving on editorial boards for Physical Review E, JSTAT, and Journal of Physics A. Her research is supported by international collaborations with institutions including the Kavli Institute for Theoretical Physics, Max Planck Institute, and Ben-Gurion University, evidenced by frequent keynote invitations at major conferences like StatPhys, ECCS, and APS March Meetings. Prof. Burioni leads collaborative research networks through her EPS division chairmanship and SIFS leadership, fostering cross-institutional projects on statistical physics applications. Her campus-based studies leverage Wi-Fi data from Parma University to model pedestrian dynamics and epidemic spreading in real-world constrained environments.
Francesco Morandin is a Researcher (Assistant Professor) in Probability and Statistics at the Department of Mathematical, Physical and Computer Sciences, University of Parma. His research spans theoretical and applied mathematics, focusing on nonlinear PDEs, SPDEs, and stochastic processes like branching and generalized urn models, with applications in medical data analysis, industrial statistics, and computational biology. Education: Mathematics degree from Scuola Normale Superiore di Pisa (1998), PhD program (1999-2000). Collaborations: University of Pisa (microarray analysis), Avio S.p.A. (mechanical failure detection), Parma burial office (cremation dynamics), Heinz-Plasmon (quality control). His recent work in machine learning includes SwitchPath activation functions for exploration enhancement, GloNets for global connectivity, and reinforcement learning applications in healthcare and game theory. He has supervised 4 bachelor's, 13 master's, and co-supervised 15 theses, with a focus on industrial and medical statistics education. His publications integrate probability theory with applications in cancer therapy prediction, single-cell RNA analysis, and stochastic modeling of turbulence.
Enea Zaffanella is an Associate Professor in Computer Science at the University of Parma , where he has been affiliated since 2000. His academic career spans from Fellow Researcher to Assistant Professor, culminating in his current role since 2006. He teaches courses in Programming Methodologies , Compilers , and Foundations of Computer Science at both undergraduate and graduate levels. PhD in Computer Science from School of Computing, University of Leeds (2002) Laurea in Computer Science from University of Pisa (1993) Research focuses on Static Analysis and Software Verification using Abstract Interpretation . Key contributions include theoretical frameworks for Constraint Logic Programs analysis, Convex Polyhedra abstractions, and Widening Operators design. His work bridges formal theory with practical implementations like the Parma Polyhedra Library (PPL) and its successor PPLite . Recent publications explore Hybrid Systems verification, Data Science linting tools (Pyra), and EVM Bytecode analysis. He received the Radhia Cousot Young Researcher Best Paper Award in 2019. Collaborations include academic Research Projects (PRIN, ESPRIT) and industrial partnerships through BUGSENG srl .
Filippo De Angelis is a Professor at the University of Perugia, where he coordinates the Doctoral Program in Chemical Sciences and serves as the University Representative for the National Interuniversity Consortium for Materials Science and Technology (INSTM). His research focuses on the computational and experimental development of advanced perovskite materials for optoelectronic and photovoltaic applications. Research interests span perovskite design, stability engineering, and device integration, with emphasis on: Chiral and low-dimensional perovskites for spintronics Tin-halide systems for LEDs/solar cells Defect physics and doping mechanisms Ab initio molecular dynamics simulations Recent publications (2024–2025) highlight trends in computational materials science, perovskite stability strategies, and chiral structure-property relationships. Works frequently employ machine learning, solid-state NMR, and in situ characterization to address challenges in carrier dynamics, halide segregation, and interfacial phenomena. No awards, students, or grant details are reported in the source text. Laboratory activities are centralized at www.clhyo.org , focusing on hybrid/organic photovoltaics and computational modeling.
Roberto Bruschi serves as a Full Professor in the Department of Naval, Electrical, Electronic, and Telecommunications Engineering (DITEN) at the University of Genoa, Italy. He instructs Master's-level courses including Internet Technologies: Architectures and Protocols, Wireless Networks (5G) and Cloud/Edge Computing, and 5G, Cloud and IoT across Electronic Engineering, Computer Engineering, and Internet and Multimedia Engineering programs. His research concentrates on next-generation telecommunications with emphasis on: 5G/6G network sustainability and ethical frameworks Energy-efficient network virtualization and resource management Cloud/edge computing integration for medical and industrial applications Human-robot collaboration over beyond-5G networks Performance optimization of containerized network functions His work bridges telecommunications engineering, computer science, and environmental sustainability, targeting carbon footprint reduction in future networks. Analysis of his 2023-2025 publications reveals a pronounced shift toward ethical and sustainable network design , with 80% of recent work addressing energy efficiency metrics, monitoring frameworks for B5G sustainability, and ethical AI governance in 6G. Key methodological approaches include stochastic modeling for queue management, open-source analytics prototypes, and real-world validation of power consumption in O-RAN deployments. No scientific awards or honors were documented in the source materials. Information regarding student advising, research grants, or laboratory affiliations was not provided in the available documentation.
Silvana Dellepiane serves as an Associate Professor in the Department of Naval, Electrical, Electronic, and Telecommunications Engineering (DITEN) at the University of Genoa's Polytechnic School. Her academic roles include teaching Electrical Communications for Biomedical Engineering and Digital Image Processing across multiple Master's programs including Internet and Multimedia Engineering, Electronic Engineering, and History of Art and Artistic Heritage Valorization. Her research spans interdisciplinary domains with primary focus on Medical Image Processing and Tele-rehabilitation Systems . Key areas include developing exergame-based rehabilitation protocols for systemic sclerosis and multiple sclerosis, lung cancer detection via deep learning, and hepatic disease staging using ultrasound morphological features. She integrates Remote Sensing techniques for flood monitoring through SAR image analysis and contributes to Digital Cultural Heritage Preservation via pigment identification algorithms for artworks. Her work consistently bridges biomedical engineering with telecommunications. Recent publications demonstrate strong trends toward AI-driven healthcare solutions, particularly in markerless telerehabilitation (ReMoVES system) and medical diagnostics (YOLOv8 for lung cancer). Cross-disciplinary applications appear in cultural heritage (digital processing of historical-artistic images) and environmental monitoring (flood risk assessment using satellite data). Over 50 publications since 2002 show consistent output in IEEE/Springer venues with increasing focus on clinical validation studies. As Member of the Joint Teacher-Student Commission, she actively shapes curriculum development. Her technical leadership appears in projects like STORMS (occupational tele-rehabilitation for MS patients) and SPeRA (web portal for Africa-focused health cooperation). Current research involves integrating graph signal processing with Markov modeling for unsupervised image segmentation across medical and remote sensing domains.
Stefano Gaggero is an Associate Professor at the University of Genoa's Department of Naval, Electrical, Electronic and Telecommunications Engineering (DITEN). His teaching portfolio includes advanced courses such as Numerical Naval Architecture, Geometry of Floating Bodies, Numerical Marine Hydrodynamics, and Ship Stability for both undergraduate (Maritime Science and Technology) and graduate programs (Naval Engineering, Yacht Design). His research focuses on computational marine hydrodynamics with emphasis on: Advanced propeller and thruster design (including rim-driven systems and pumpjets) CFD-based optimization for noise reduction and efficiency enhancement Cavitation modeling and hydrodynamic performance prediction Machine learning applications in naval architecture Scale effects in experimental hydrodynamics Underwater radiated noise control Publications from 2023-2025 demonstrate a consistent focus on simulation-driven optimization of marine propulsion systems. Over 65% of recent works leverage CFD/RANS methods to innovate propeller designs, while 40% incorporate machine learning or reduced-order modeling. Key trends include robust optimization under uncertainty, hybrid physics-AI methodologies, and full-scale validation of marine propulsors.
Lucio Marcenaro is an Associate Professor in the Department of Naval, Electrical, Electronic and Telecommunications Engineering at the University of Genoa, where he serves as Coordinator of the Bachelor's Degree Course in Electronic Engineering and participates in university research committees. His teaching responsibilities span undergraduate and graduate programs including Fundamentals of Telecommunications and Signal Processing, Multimedia Signal Processing for Autonomous Systems, and Pervasive Dynamic Electronics across Computer Science, Electronic Engineering, and Internet and Multimedia Engineering curricula. His research centers on autonomous systems with emphasis on Bayesian inference frameworks and active inference methodologies. Key investigation areas include vehicle localization using dynamic Bayesian networks, anomaly detection in vehicular networks through generative models, UAV trajectory optimization, and resource allocation in cognitive radio systems. His work integrates signal processing, machine learning, and robotics to develop self-aware systems capable of real-time adaptation in dynamic environments, particularly focusing on explainable AI implementations for autonomous agents. Analysis of his 2024-2025 publications reveals a dominant trend toward generative Bayesian models for autonomous systems, with consistent application across autonomous vehicles, UAV networks, and intelligent radios. His research demonstrates strong interdisciplinary integration of probabilistic modeling with physical layer implementations, showing particular innovation in explainable decision frameworks and anomaly detection systems that bridge theoretical AI with practical engineering constraints in mobile networks.
Renato Procopio is a full-time Professor at the Department of Naval, Electrical, Electronic and Telecommunications Engineering (DITEN), University of Genoa , Italy. His work focuses on power systems, lightning protection, renewable energy integration, and machine learning applications in energy systems. Current research includes lightning-induced overvoltage analysis , optimal inertia allocation for transmission networks, and vehicle-to-home energy systems Recent publications highlight applications of machine learning in lightning location, photovoltaic microgrid optimization , and energy storage virtual partitioning . His work addresses grid stability in renewable-heavy networks and soil conductivity impacts on distribution line performance. He is organizing the 2025 AEIT HVDC International Conference in Genoa, Italy.
Matteo Saviozzi is an Associate Professor at the Department of Naval, Electrical, Electronic and Telecommunications Engineering (DITEN) within the School of Engineering at the University of Genoa. His academic profile focuses on electrical engineering, renewable energy integration, and optimization of energy systems. Academic Rank: Associate Professor University: University of Genoa School: School of Engineering Department: Department of Naval, Electrical, Electronic and Telecommunications Engineering Research Interests: His work explores advanced control strategies for microgrids, load forecasting methodologies, and optimal management of renewable energy systems. He specializes in virtual inertia support, energy storage integration, and applications of machine learning to energy consumption prediction. Recent Publication Trends: Current research emphasizes stochastic optimization for energy communities, synthetic inertia in grid-forming inverters, and hybrid modeling approaches combining traditional statistical methods with neural networks. His work spans both theoretical development and practical implementation in naval and terrestrial power systems. Contact: Email: matteo.saviozzi@unige.it Office: Dipartimento DITEN, Via Opera Pia 11A
Marco Storace is a Full Professor at the Department of Naval, Electrical, Electronic, and Telecommunications Engineering (DITEN) at the University of Genoa. His research focuses on nonlinear circuits, power electronics, and control systems, with a particular emphasis on inductor modeling for switch-mode power supplies (SMPS), model predictive control (MPC) algorithms, and synchronization phenomena in adaptive networks. Recent research highlights include the development of nonlinear behavioral models for ferrite-core and amorphous-core inductors, FPGA implementations of nonlinear MPC for power converters, and studies on cluster synchronization in networks with neural plasticity. His work bridges theoretical advancements in nonlinear dynamics with practical applications in energy systems and biomedical engineering. Marco Storace has received recognition for his contributions to modeling techniques, control system design, and neural connectivity analysis. He has developed toolboxes such as MOBY-DIC for embedded MPC and BAL for dynamical system analysis, advancing methodologies in circuit design and computational neuroscience. He teaches courses on circuit theory, nonlinear circuits and systems, and power management at both undergraduate and master's levels. His teaching integrates advanced concepts with hands-on laboratory work, emphasizing the design and analysis of nonlinear and programmable systems.
Giuliano Vernengo is an Associate Professor in the Department of Naval, Electrical, Electronic and Telecommunications Engineering at the University of Genoa. He teaches Experimental Naval Architecture, Ship Dynamics, Geometry of Floating Bodies, and Yacht Dynamics for Master's programs in Naval Engineering and Yacht Design. His research centers on Naval Architecture and Marine Hydrodynamics , with emphases on seakeeping , ship resistance , computational fluid dynamics , and yacht design . He develops advanced numerical methods for hydrodynamic analysis while pioneering AI integration in maritime applications like wake detection and metocean data processing. His work bridges theoretical modeling with practical ship design optimization. Analysis of recent publications (2022-2025) reveals three dominant research thrusts: (1) AI-enhanced maritime surveillance (UEIKAP framework for satellite-based wake detection), (2) Advanced CFD methodologies for ship hydrodynamics and optimization, and (3) Renewable energy applications including floating wind turbine stability. His interdisciplinary approach combines fluid dynamics, AI, and naval structural analysis. Dr. Vernengo actively collaborates on international projects involving ship performance prediction, submarine maneuverability, and hydrofoil propulsion systems. His research demonstrates strong industry relevance for naval architects, maritime safety agencies, and renewable energy developers.
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