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Violetta LonatiView profile

Assistant Professor

• Formal Languages and Automata
• Computer Science Education
• Theoretical Computer Science
• +2 more

Violetta Lonati is an Assistant Professor at the University of Milan 's Department of Computer Science since 2005. Her research spans Formal Languages and Automata (operator precedence languages, Wang automata, tiling systems) and Computer Science Education . She co-authored over 15 publications in theoretical computer science and education, focusing on 2D language recognition, logic characterization of automata, and pattern statistics in stochastic models. Education : PhD in Computer Science (2005) and Laurea in Mathematics (2001) from University of Milan Research Groups : ALaDDIn Lab for Didactics and Dissemination of Informatics, Bebras International Initiative Her work on Wang automata established their equivalence to tiling systems while introducing deterministic variants. In education, she designed workshops for schools and contributed to Italy's national computing curriculum proposal (2019). She held leadership roles at ACM ITiCSE (WG5 leader 2022), served as Associate Program Chair (2019-2022), and reviewed for top venues like ICER and SIGCSE TS. She received Google CS[4]HS and Informatics Europe awards for her educational contributions. Key Publications (2017-2001): Input-driven locally parsable languages (TCS 2017) Operator precedence logic characterization (SICOMP 2015) Snake-deterministic tiling systems (MFCS 2009) Graph fibrations and PageRank (RAIRO 2006) Pattern statistics in rational models (STACS 2005) Scientific awards include Google CS[4]HS (2011, 2017, 2019) and the Informatics Europe Best Practices in Education (2016). As part of ALaDDIn, she developed teacher training programs and graduate courses on computing education. Her teaching experience covers Algorithms & Data Structures (2013-2023), Computer Science Teaching (2014-2023), and courses for Biotechnology and Geological Sciences programs (2005-2007).

Laura Emilia Maria RicciView profile

Professor

• Blockchain Technology
• Layer-2 Solutions for Blockchain
• Cryptographic Techniques
• +3 more

Laura Emilia Maria Ricci is a Full Professor at the University of Pisa's Department of Computer Science, leading the Pisa Distributed Ledger Laboratory (Pisa DLT Lab). Her research focuses on blockchain technology, layer-2 solutions, cryptographic techniques, and self-sovereign identity frameworks. She coordinates the National PhD program in Blockchain and Distributed Ledger Technologies and leads the PRIN research project 'AWESOME' (2023-2025). Ricci serves as an associate editor for the ACM Distributed Ledger Technologies: Research and Practice journal and the Springer Nature SN Computer Science section on blockchain innovations. Her research emphasizes blockchain scalability, transaction analysis, and social network dynamics. Recent work includes studies on NFT architectures, post-quantum cryptography in Ethereum, and query authentication protocols. She co-organized the 7th IEEE International Conference on Blockchain and Cryptocurrencies (2025) and actively participates in global blockchain initiatives. Ricci has been awarded Best Paper Awards for her contributions to decentralized cloud scheduling, hybrid architectures for online games, and distributed virtual environments. She advises numerous PhD students and oversees grants like the H2020 'HELIOS' project. Ricci's academic roles include teaching blockchain, peer-to-peer systems, and web scraping at the University of Pisa. Her lab collaborates on projects such as the AQuSDIT grant (2024-2025) and the Ethereum Foundation's 'Cross Chain Authenticated Queries.' She also chairs conferences like IEEE Blockchain and co-edits special issues on blockchain-based pervasive systems and social media analysis.

Sebastiano VASCONView profile

Associate Professor

• Artificial Intelligence
• Computer Vision
• Machine Learning
• +4 more

Sebastiano Vascon is an Associate Professor at Ca' Foscari University of Venice's Department of Environmental Sciences, Computer Science and Statistics (DAIS), and affiliated with the European Center for Living Technology. He earned his PhD in 2016 from the Italian Institute of Technology and University of Genoa, focusing on evolutionary game theory in pattern analysis and computer vision. His postdoctoral work spanned institutions like the Technical University of Munich and ETH Zurich, where he specialized in Active Learning and multi-object tracking. His research merges AI with interdisciplinary challenges, including climate change, environmental science, and cultural heritage preservation. Key areas include graph neural networks, computer vision, and game-theoretic models. He leads projects like RePAIR (AI for cultural heritage reassembly) and EasyWalk (AI-driven mobility solutions), and contributes to initiatives like MEMEX (digital storytelling). Teaching spans courses in Deep Learning, Machine Learning for Environmental Applications, and AI in Cultural Management. Research projects include: RePAIR: AI-driven 3D puzzle solving for artifact reconstruction EasyWalk: Socially-aware navigation systems MEMEX: AI for inclusive digital storytelling Climate modeling with IceBoost framework Publications highlight innovations in trajectory forecasting, environmental risk assessment, and graph-based methods. He actively reviews for top conferences (CVPR, ECCV) and journals.

• Aerodynamics
• Aeroacoustics
• Renewable Energy Systems
• +4 more

Delibra Giovanni is an Associate Professor at Sapienza University of Rome, specializing in aerodynamics, aeroacoustics, and renewable energy systems. His research focuses on optimizing turbomachinery performance, including axial fans, wind turbines, and hydrogen storage systems. He employs advanced computational fluid dynamics (CFD) and machine learning techniques to address challenges in renewable energy integration, thermal management, and noise reduction. Key research areas include: Wind energy systems and offshore wind farm design Hydrogen storage and safety in green energy applications Aeroacoustic control in industrial fans and turbines CFD-based optimization of heat exchangers and cooling systems Recent work emphasizes the integration of photovoltaic and biomass systems in renewable energy communities, as well as experimental validation of wave energy turbines. His publications highlight innovations in fan blade design, leakage modeling, and multi-objective optimization frameworks for sustainable energy infrastructure. Collaborations involve both academic institutions and industry partners, focusing on real-world applications such as tunnel ventilation systems and Mediterranean island energy solutions. Giovanni's contributions bridge theoretical modeling with practical engineering challenges in the transition to clean energy.

Roberto MenichettiView profile

Researcher

• Theoretical Physics
• Computational Physics
• Statistical Mechanics
• +7 more

Roberto Menichetti is a theoretical physicist at the University of Trento , affiliated with the Department of Physics and the VARIAMOLS research group . His work integrates computational physics, statistical mechanics, and machine learning to model biomolecules and soft matter systems. Prior roles include postdoctoral research at the Max Planck Institute for Polymer Research (2016-2018) and academic training at the University of Rome 'La Sapienza'. PhD in Physics (La Sapienza, 2016) BSc/MSc in Physics (La Sapienza, 2012) His research spans: Coarse-Graining Methods for polymers, colloids, and biomolecules High-throughput Molecular Dynamics Simulations in drug-membrane permeability studies Integration of Machine Learning with physical models for multi-scale analysis Applications in Biophysics (e.g., chromatin condensates, protein dynamics) Article trends highlight his focus on computational frameworks like EXCOGITO and theoretical investigations of non-equilibrium systems and allosteric regulation . He actively develops tools for systematic model reduction and conformational sampling in biomolecular systems. Contact: roberto.menichetti@unitn.it

Annalisa MarzuoliView profile

Professor

• Quantum Computing
• Quantum Gravity
• Geometric Methods in Quantum Field Theory
• +7 more

Annalisa Marzuoli is a Full Professor at the Department of Mathematics, University of Pavia, specializing in Mathematical Physics. Her research focuses on geometric methods in quantum field theory, discrete models in gravity, quantum computing, and data science. She is affiliated with the Mathematical Physics group and has contributed to advancements in spin networks, quantum triangulations, and topological quantum computing. Her work bridges quantum mechanics and geometry, exploring topics like Ricci flow, non-linear sigma models, and topological invariants. Recent publications emphasize knotted optical fields, Ponzano-Regge models, and quantum angular momentum configurations. Her research also addresses geometric structures in quantum gravity and computational approaches to topological phases. Marzuoli's articles reveal a focus on interdisciplinary applications of geometric and combinatorial techniques to quantum systems. Key themes include spin network dynamics, topological quantum computing architectures, and geometric flows in theoretical physics. Her contributions to mathematical physics underscore the interplay between discrete models and continuous geometric frameworks. She has no listed scientific awards but maintains an active research profile with collaborations in quantum geometry and computational physics. No advising or grant details are provided in the text. Her group explores quantum geometry through projects like spin network quantum circuits and discrete gravity models, reflecting a commitment to advancing foundational theories in mathematical physics.

Marc MezardView profile

Professor

• Statistical Physics
• Machine Learning
• Information Theory
• +5 more

Marc Mezard is a Professor of Theoretical Physics at Bocconi University, where he leads the newly established Department of Computational Sciences. Previously, he served as Research Director at CNRS in Paris and held roles at Université Paris Sud. He earned his PhD in Physics from École Normale Supérieure in Paris in 1984. His research focuses on statistical physics of disordered systems, with applications to machine learning, information theory, computer science, and biophysics. His work bridges theoretical physics and interdisciplinary fields, including neural networks and deep learning, where he explores the impact of data structure on learning strategies. He teaches undergraduate courses in statistical and quantum physics and a doctoral course on complex systems. Key research themes include emergent phenomena in complex systems, with contributions to spin glass theory, compressed sensing, and algorithmic solutions for random satisfiability problems. His publications span foundational topics in statistical mechanics and modern applications in data science. Marc Mezard has collaborated extensively with institutions and researchers globally, contributing to the theoretical foundations of computational and physical sciences. His academic leadership includes directing École Normale Supérieure from 2012 to 2022, fostering interdisciplinary research initiatives.

Gianna Del CorsoView profile

Associate Professor

• Quantum Computing
• Numerical Linear Algebra
• Spectral Analysis
• +3 more

Gianna Del Corso is an Associate Professor at the Department of Computer Science, University of Pisa. Her research interests span Quantum Computing, Numerical Linear Algebra, and Spectral Analysis. She has advised PhD students in quantum computing topics such as quantum algorithms and machine learning. Her teaching includes courses on Numerical Calculus, Parallel Scientific Computing, and Introduction to Quantum Computing, delivered across multiple academic years at the University of Pisa. She has also contributed to advanced courses in the PhD program in Computer Science. Her research focuses on quantum algorithms for machine learning, quantum walks, eigenvalue computation of structured matrices, and spectral techniques for web analysis. Recent work includes applications of quantum k-means clustering and variance estimation subroutines. Her publications span quantum computing, numerical methods, and scientific citation models. Her articles highlight contributions to PageRank computation, matrix factorization for recommendation systems, and analysis of citation-based research evaluation models. She has actively engaged in international conferences, presenting on topics such as orthogonal iterations for nonlinear eigenvalue problems and quantum hitting time algorithms. Labs/Teams: Research conducted within the Department of Computer Science at the University of Pisa, focusing on quantum computing and numerical methods.

Valentina PresuttiView profile

Assistant Professor

• AI
• Semantic Web
• Linked Data
• +17 more

Valentina Presutti is an Assistant Professor at the University of Bologna and an Associate Researcher at the Institute of Cognitive Science and Technologies (CNR). She coordinates the STLab (Semantic Technology Laboratory) and leads the EU H2020 Polifonia project (2021–2024), following previous roles in projects like MARIO , IKS , and NeOn . She is the co-founder of ontologydesignpatterns.org and the Ontology Patterns (WOP) workshop series. PhD : Computer Science, University of Bologna (2006) Key Collaborations : LIPN (University of Paris 13 and CNRS), CNRS Her research focuses on Semantic Web , Linked Data , Ontology Design , and Social Robotics , with a strong emphasis on Knowledge Engineering , Empirical Semantics , and Collaborative Content Management . Recent publications highlight trends in LOD analysis , Ontology Applications , and Human-Robot Interaction . She serves on the editorial boards of Journal of Web Semantics , Data Intelligence , JASIST , and Intelligenza Artificiale , and co-directs the International Semantic Web Research Summer School . Her work bridges semantic technologies with ICT for eHealth and cognitive computing .

Achille GIACOMETTIView profile

Professor

• Theoretical Physics
• Soft Matter Physics
• Polymer Physics
• +3 more

Achille GIACOMETTI is a Full Professor at Ca' Foscari University of Venice, affiliated with the Department of Molecular Sciences and Nanosystems and the European Center for Living Technology (ECLT) , where he serves as Director. His research focuses on theoretical physics, soft matter, and biophysics, with a strong emphasis on polymer physics, protein structures, and self-assembly processes. Key roles include leadership at ECLT, a multidisciplinary research center exploring living technology and complex systems. His work bridges physics and biology, addressing topics like phase transitions in colloids, solvent effects on polymers, and computational modeling of protein interactions. Recent projects include studies on crystalline order in charged rods, embodied intelligence in soft materials, and solvent-driven oligomer folding. Publications highlight contributions to understanding polymeric systems, phase behavior, and nanoscale self-assembly. Collaborative efforts span international partners, reflecting his commitment to interdisciplinary research. No awards explicitly listed, but his extensive publication record underscores academic impact.

• Fluid Dynamics
• Turbulence
• Wind Energy
• +5 more

Stefania Cherubini is a Full Professor in the Department of Mechanics, Mathematics & Management at Politecnico di Bari, Italy. Her academic work focuses on fluid dynamics, turbulence, and wind energy, with a particular emphasis on stability analysis, computational fluid dynamics (CFD), and data assimilation techniques. Research areas: Fluid Dynamics, Turbulence, Wind Energy, Stability Analysis, Computational Fluid Dynamics, Data Assimilation, Aeroacoustics, Nonlinear Optimization Recent publications highlight her work on wind turbine simulations using Large Eddy Simulation (LES) and Fluid-Structure Interaction (FSI) models, dynamic mode decomposition (DMD) for wake analysis, and graph neural networks (GNNs) for CFD closure modeling. She investigates superhydrophobic surfaces, boundary-layer instabilities, and nonlinear optimization in transitional and turbulent flows. Key article trends include: (1) Wind turbine aeroacoustics and wake dynamics; (2) Machine learning integration in fluid flow simulations; (3) Nonlinear stability analysis of complex flows; (4) Superhydrophobic drag reduction mechanisms; (5) Turbulent transition modeling in channel and boundary-layer flows.

• Complex networks
• Multi-agent systems
• Nonlinear control
• +5 more

Anton Proskurnikov is an Associate Professor in the Department of Electronics and Telecommunications at Politecnico di Torino, Italy. His academic appointment spans the College of Computer, Film and Mechatronics Engineering and the College of Mechanical, Aerospace and Automotive Engineering. Based in office L.240, he maintains an active research program focused on control theory with applications to complex networked systems. Dr. Proskurnikov's research centers on complex networks, multi-agent systems, nonlinear control, and social network analysis, with significant contributions to understanding opinion dynamics and consensus mechanisms. His work bridges theoretical control engineering with practical applications in social dynamics, earning recognition through prestigious awards including the O. Hugo Schuck Best Paper Award (2023). His expertise spans control theory, optimization, and network analysis with implications for sustainable infrastructure and smart cities. His publication trajectory reveals a sophisticated evolution from foundational control theory toward increasingly complex applications in social dynamics and networked systems, with recent emphasis on bounded confidence models, higher-order interactions in social dynamics, and quantum optimization for complex system design. This interdisciplinary approach connects traditional control engineering with emerging challenges in social network analysis. Dr. Proskurnikov has received multiple significant awards: O. Hugo Schuck Best Paper Award (2023) from the American Automatic Control Council EPEPS Best Paper Award (2020) from EPEPS Conference Annual Reviews in Control Paper Prize (2020) from IFAC As an academic advisor, Dr. Proskurnikov currently supervises PhD student Jinze Wu in Electrical, Electronics, and Communications Engineering. His research is supported by the National Research PRIN project "Higher-order interactions in social dynamics with application to monetary networks" (2023-2025), for which he serves as Scientific Manager. He contributes to editorial boards of leading journals including IEEE TRANSACTIONS ON AUTOMATIC CONTROL and INTERNATIONAL JOURNAL OF CONTROL, reflecting his standing in the control theory community. Dr. Proskurnikov is an active member of the Automatica research group within the Department of Electronics and Telecommunications, focusing on systems, automation, and control. His collaborative work extends internationally to institutions including TU Delft, St. Petersburg National Research University, and the University of Groningen, demonstrating his strong international research presence and interdisciplinary approach to complex networked systems.

• Multivariate Analysis
• Fuzzy Clustering
• Probabilistic Graphical Models
• +3 more

Vincenzina Vitale serves as a Tenure-Track Assistant Professor of Statistics within the Department of Social and Economic Sciences at Sapienza University of Rome. Her academic profile centers on advanced statistical methodologies with applications spanning economics, public policy, and sustainability initiatives. She teaches core courses including Statistics and Data Science for Sustainability and Statistical Methods and Models for Economics and Public Policy, maintaining regular office hours on Tuesdays from 12:30 to 14:30 by email appointment. Her research program focuses on multivariate analysis, specializing in innovative fuzzy clustering techniques for complex data structures such as time series, spatial data, and mixed data types. She extensively employs probabilistic graphical models, particularly Bayesian networks, for data integration and modeling challenges. This work bridges theoretical statistics with practical applications in electoral analysis, financial volatility, sports analytics, and public health domains including COVID-19 pandemic response. Analysis of her 15 most recent publications reveals a dominant trend toward developing spatially-aware and robust fuzzy clustering algorithms. These methods increasingly incorporate regularization techniques, entropy principles, and copula models to handle interval-valued data, count data, and tail dependencies. Key application areas include regional competitiveness measurement (NUTS2/NUTS3 frameworks), electoral studies, sports performance analytics, and pandemic modeling, demonstrating consistent contributions to top-tier statistical journals. No scientific awards or fellowships were documented in the available materials. While her publication record indicates significant research productivity, specific details regarding graduate student advising, research grants, or collaborative projects were not explicitly mentioned in the provided texts. Similarly, information about laboratory facilities or dedicated research teams remains undocumented in the current sources.

• Algorithms on strings
• Formal language theory
• Bioinformatics
• +3 more

Chiara Epifanio is a researcher (INFO-01/A) at the University of Palermo , based in the Department of Mathematics and Computer Science . She holds regular office hours on Tuesdays 14:30–17:00 in Room 104, first floor, Via Archirafi 34, and can be reached at chiara.epifanio@unipa.it . Over the past fifteen years she has designed and taught a diverse portfolio of courses spanning Programming , Bioinformatics , Advanced Programming , Teaching Methodologies and Techniques for Computer Science and Pattern Discovery for Life Sciences . These offerings serve degree programmes in Mathematics, Computer Science, Statistics & Data Science, and the recently launched curricula in Data, Algorithms & Machine Intelligence and Computer Science & Artificial Intelligence . Her research lies at the intersection of combinatorics on words , string algorithms , and bioinformatics . She has made sustained contributions to the design of alignment-free distances for biological data, the theory of Sturmian words and their associated graphs, suffix automata tolerant to mismatches, and compact data structures such as linear-size suffix tries. The work repeatedly draws on deep results from formal language theory, automata theory, and discrete mathematics to solve practical problems in sequence analysis. Publications trend: From 2004 onward she has produced a steady stream of peer-reviewed articles that move from foundational combinatorial results on Sturmian words and critical factorization theorems toward application-driven studies on approximate string matching and genomic data mining. A marked acceleration is visible in the 2023 publications addressing k-Hamming and k-edit distances, reflecting current demands in large-scale biological data analytics. Scientific awards: None explicitly mentioned in the provided material. Advising & grants: No PhD or Master’s students are listed in the supplied pages, and no funded project descriptions are available. Laboratories & teams: While no specific lab is named, her teaching and research are embedded within the Department of Mathematics and Computer Science, which hosts groups in algorithms, discrete mathematics, and bioinformatics, and provides access to the university’s ATeN Center and other research infrastructures.

Werner NuttView profile

Professor

• Data Management
• Knowledge Representation
• Intelligent Information Extraction
• +3 more

Werner Nutt is a Professor at the Free University of Bozen-Bolzano , Italy, affiliated with the Faculty of Computer Science since 2005. He previously held academic positions as a Reader at Heriot-Watt University (2000-2005), Visiting Professor at Hebrew University of Jerusalem, and Research Scientist at DFKI (1992-2000). Current Role: Professor, Free University of Bozen-Bolzano Past Roles: Reader (Heriot-Watt), Visiting Professor (Hebrew University), Research Scientist (DFKI) Research Interests focus on Data Management , Knowledge Representation , and Intelligent Information Extraction , with emphasis on modeling Construction Processes and ensuring Data Quality . His work bridges Semantic Web technologies with Business Process Management , notably through the COCkPiT project (2017-present) for construction process optimization. Key Contributions include foundational work on Query Completeness in databases, SPARQL Reasoning , and Semantic Diagnostics . He has published extensively in venues like ISWC , BPM , and CIKM , with an h-index of 35 on Google Scholar. His 154+ publications span topics from Probabilistic XML to Construction Process Modeling .