Find Academic Supervisors

Giorgio VinciguerraView profile

Research Fellow

• Data Compression
• Algorithm Engineering
• Learned Data Structures
• +3 more

Giorgio Vinciguerra is a Research Fellow (RTD-A) at the Department of Computer Science of the University of Pisa since January 2023, and a member of the A³ Lab. His research focuses on compact data structures, data compression, and algorithm engineering, with a specialization in learned data structures that leverage machine learning to improve space-time trade-offs. He holds a PhD from the University of Pisa (2022), awarded the Best PhD thesis in Theoretical Computer Science by the Italian Chapter of EATCS. His academic journey includes postdoc research (2022), a visiting researcher role at KTH Royal Institute of Technology (2024), and Harvard University (2020). He has contributed to EU-funded projects like SoBigData.it and owns patents for innovations in data structure design. Key research interests include: Learned compression techniques for time series and string dictionaries Space-efficient indexing for massive datasets Algorithmic integration of machine learning into traditional data structures His work has been published in top venues including ICDE, Inf. Syst., and ACM Trans. Algorithms. Awards include the 2025 WSDM Outstanding Reviewer Award. He has co-supervised multiple theses on topics like adversarial query optimization and compressed indexing. Teaching roles include courses on programming, algorithms, and information retrieval at the University of Pisa. His software libraries (e.g., LeMonHash, PGM-index) are widely used in database systems and bioinformatics.

Andrea VinciView profile

Researcher

• Quantum Computing
• Edge-Cloud Computing
• Internet of Things (IoT)
• +5 more

Andrea Vinci is an accomplished researcher with 66 publications and 1,261 citations, specializing in the intersection of quantum computing, edge-cloud architectures, and Internet of Things (IoT) systems. His work demonstrates significant contributions to solving complex computational problems through innovative approaches that bridge theoretical quantum algorithms with practical distributed computing applications. His research interests span quantum computing applications for resource management, multi-density clustering techniques for urban analytics, and platform-independent IoT application development. Vinci has pioneered work in variational quantum algorithms for cloud/edge resource allocation, quantum kernels for IoT data classification, and distributed AI for cognitive building systems. His research demonstrates a consistent focus on addressing NP-hard problems through quantum-classical hybrid approaches. Analysis of Vinci's publication trends reveals a strategic research trajectory moving from foundational work in smart city analytics and crime prediction toward cutting-edge quantum computing applications for IoT and edge-cloud systems. His recent publications (2023-2025) show increasing focus on quantum machine learning techniques specifically tailored for IoT data processing, with significant attention to practical implementation challenges. Vinci maintains an extensive collaborative network, frequently publishing with researchers including Fabrizio Marozzo, C. Mastroianni, J. Settino, and Antonio Guerrieri across multiple high-impact venues including IEEE Transactions, ACM conferences, and specialized journals in quantum computing and distributed systems. His technical contributions include the development of the COGITO platform for cognitive buildings, novel approaches to multi-density crime prediction, and significant advancements in quantum kernel methods for IoT data analysis. Vinci's tutorial publications indicate his role in educating the broader research community about emerging quantum computing applications for distributed systems.

• Numerical Linear Algebra
• Matrix Theory
• Numerical Analysis
• +6 more

Davide Palitta is an Assistant Professor (tenure track) at the Department of Mathematics of the University of Bologna. His research focuses on numerical linear algebra, matrix equations, and their applications in fields like data assimilation, deep learning, and parallel computing. He holds a PhD in Mathematics from the University of Bologna (2018) and has held postdoctoral positions at the Max Planck Institute in Magdeburg (2018–2021) and a visiting fellowship at Brown University (2020). His work emphasizes the development of efficient numerical algorithms for large-scale matrix equations, including Sylvester, Lyapunov, and Riccati equations. Key contributions include Krylov subspace methods, randomized techniques, and time-parallel integration strategies. His recent publications span topics such as sketched Krylov methods, tensor-based solvers, and preconditioning strategies for weak-constraint data assimilation. Palitta collaborates actively with international institutions and organizes seminars like the Scube series on numerical linear algebra. He is involved in upcoming conferences on matrix equations, data assimilation, and parallel computing. No scientific awards are explicitly mentioned in the provided materials.

Francesco VenezianoView profile

Associate Professor

• Geometry
• Number Theory
• Algebra
• +3 more

Francesco Veneziano serves as an Associate Professor in the Department of Mathematics (DIMA) at the University of Genoa, Italy, holding academic rank MATH-02/B in Geometry. His teaching portfolio spans multiple engineering and mathematics programs, including Geometry for Computer Engineering and Naval Engineering undergraduates, and advanced graduate courses such as Galois Theory and Higher Geometry in Institutions for Mathematics Master's students. Office hours are maintained via the university's Aulaweb platform. His research program centers on pure mathematics with emphases on geometric structures and number-theoretic phenomena. Primary investigations explore continued fractions over algebraic number fields, rational angle classification in lattice geometries, and nonlinear recurrence relations. Recent work demonstrates interdisciplinary expansion into computational mathematics, notably applying reinforcement learning to game theory problems. The geometric perspective permeates all research strands, connecting abstract algebraic frameworks with concrete discrete structures. Analysis of his 2022-2024 publications reveals consistent focus on classical number theory problems with geometric interpretations. Key trends include periodicity properties in continued fraction expansions, Diophantine constraints in lattice configurations, and algorithmic approaches to strategic game analysis. The 2024 publication on 7 Wonders Duel represents a methodological evolution, merging dynamical systems theory with artificial intelligence techniques while maintaining core mathematical rigor. No scientific awards or honors were documented in the source material. No information regarding doctoral advisees, master's students, or externally funded research grants was provided. His academic contributions appear concentrated in theoretical research and advanced mathematical education within the university's mathematics department.

Maria Grazia ScutellaView profile

Professor

• Combinatorial Optimization
• Robust Optimization
• Network design and routing
• +5 more

Roles & Affiliations: Full Professor at the Department of Computer Science, University of Pisa. Served as Vice Director of the Department (2020–2024). Active in editorial roles for journals like Networks and Computers & Operations Research . Education: Laurea in Information Science (University of Pisa, 1985, cum laude), PhD in Computer Science (University of Pisa, 1990). Qualified as Full Professor in Operations Research (2013). Research Focus: Specializes in Combinatorial Optimization, Robust Optimization, Network Design, and Logistics. Key contributions include green wireless networks, home care optimization, and vehicle routing. Awarded the Best Paper in Omega (2018) and recognized for seminal work in Discrete Applied Mathematics (1998). Teaching: Teaches courses in Operations Research, Logistics, and Network Optimization at both undergraduate and graduate levels, including international programs. Grants & Projects: Led national and international projects, including PNRR initiatives on sustainable mobility and IREAD-4.0 for warehouse optimization. Collaborated with industries like Softec S.r.l. and Siemens. Professional Activities: Organized major conferences (e.g., INOC 2009). Served on editorial boards and scientific committees for AIRO, INOC, and other networks. Active in mentoring doctoral students and fostering academic-industrial partnerships.

Mirco RaffettoView profile

Professor

• Electromagnetic Fields
• Computational Electromagnetics
• Metamaterials
• +7 more

Mirco Raffetto is a Full Professor in the Department of Naval, Electrical, Electronic, and Telecommunications Engineering (DITEN) at the University of Genoa under the Polytechnic School. He actively participates in academic governance as a member of the Department Board, Scientific Council of the Interuniversity Center for Electromagnetic Fields and Biosystems (ICEMB), and School Council. Research Focus: His work spans Electromagnetic field analysis for moving media Computational electromagnetics with finite element methods Metamaterial modeling and inverse scattering Photobiomodulation effects on mitochondrial function Microwave imaging for biomedical applications Waveguide and cavity analysis for industrial systems His research combines theoretical rigor with numerical simulations to solve complex problems in electromagnetics and interdisciplinary biosystems. Teaching: He teaches graduate courses on Electromagnetic Fields in multiple degree programs including Computer Engineering, Electronics Engineering, and Biomedical Engineering. His teaching emphasizes both fundamental theory and practical applications.

• Naval Engineering
• Marine Propulsion
• Hybrid Propulsion Systems
• +6 more

Raphael Zaccone serves as an Associate Professor in the Department of Naval, Electrical, Electronic and Telecommunications Engineering at the University of Genoa, where he is an active member of the department board. He teaches core courses including Military Ships (NAVI MILITARI), Naval Propulsion (PROPULSIONE NAVALE), and Naval Plants (IMPIANTI NAVALI) for the Naval Engineering degree program, as well as Ship Plants and System Safety for Maritime Science and Technology students. His research centers on sustainable maritime innovation, with primary focus areas in hybrid propulsion systems, alternative fuels (particularly methanol conversions), ship safety protocols, and autonomous navigation technologies. Key specialties include energy management strategies for reducing environmental impact, structural solutions for yacht refits, and collision avoidance algorithms compliant with international maritime regulations. His work bridges theoretical modeling with practical engineering applications to address critical challenges in modern naval architecture. Recent publications (2023-2025) reveal a pronounced trend toward maritime cybersecurity and AI-driven safety systems, with significant emphasis on LiDAR-based situational awareness, battery storage optimization for naval vessels, and evaluation frameworks for alternative marine fuels. Approximately 40% of his current work addresses autonomous ship navigation challenges, while 30% focuses on decarbonization through methanol propulsion and waste heat recovery systems, demonstrating strategic alignment with global maritime sustainability initiatives.

Salvatore BarbagalloView profile

Professor

• Water Management
• Irrigation
• Wastewater Reuse
• +4 more

Salvatore Barbagallo is a Full Professor of Agricultural Hydraulics at the Faculty of Agriculture, University of Catania, where he has been teaching since 2001. He holds office in the Engineering Area at Via Santa Sofia, 100, Room 23, and maintains regular office hours on Mondays and Fridays from 9:00 to 11:00. His academic career spans over three decades, beginning with his graduation in Hydraulic Engineering from the University of Catania in 1981. His educational background includes: Graduated in Hydraulic Engineering from the University of Catania (1981) Professor Barbagallo's research focuses on critical water management issues, particularly in Mediterranean agricultural contexts. His work addresses the sustainable use of water resources through innovative approaches to wastewater treatment and reuse. He has pioneered research on phytoremediation systems using constructed wetlands for treating urban and agro-industrial wastewater. His investigations extend to understanding the effects of wastewater reuse on crop production, agricultural product quality, and potential health implications. Professor Barbagallo also contributes significantly to water resources planning frameworks that balance agricultural needs with environmental protection requirements, particularly in water-scarce regions like Sicily. Through his extensive publication record of approximately 180 scientific papers, Professor Barbagallo has established himself as a leading expert in agricultural water management. His research demonstrates a consistent trajectory toward developing practical, sustainable solutions for water reuse in agriculture, with particular attention to Mediterranean cropping systems. The breadth of his work spans from fundamental studies on treatment processes to applied research on implementation strategies and policy frameworks. His scientific recognition includes: Membership in the prestigious Academy of Georgofili of Florence Membership in the Academy of Zelanti and Dafnici of Acireale Professor Barbagallo has supervised numerous research projects and doctoral students throughout his career, though specific student names are not documented in the available materials. He has coordinated multiple national and international research initiatives, including his current role as scientific director of a Ministry of Economic Development project focused on sustainable use of citrus processing by-products. His leadership extends to significant administrative roles, having served as Dean of the Faculty of Agriculture at the University of Catania (2002-2008) and President of the Evaluation Committee of the University of Catania (2017-2021). His laboratory and research team, operating under the Center for Studies in Economics Applied to Engineering in Catania (CSEI-Catania), which he directs, focuses on practical applications of water management technologies. The team works closely with regional authorities and agricultural stakeholders to implement and monitor wastewater reuse systems throughout Sicily, with particular attention to the Ragusa province where citrus production is prominent.

Giuseppe FRANZE'View profile

Professor

• Constrained Predictive Control
• Networked Control Systems
• Cyber-Physical Systems
• +7 more

Giuseppe FRANZE' is a Full Professor at the Department of Mechanical, Energy and Management Engineering (DIMEG) of the University of Calabria since 2022. He has over 200 publications in archival journals, book chapters, and conference proceedings, with a focus on constrained predictive control, networked control systems, and resilient control for cyber-physical systems. His research includes theoretical and applied projects funded by MIUR/MUR, European Union, and international institutions. IEEE Senior Member (2019) Associate Editor for IEEE/CAA Journal of Automatica Sinica Guest Editor for Special Issue on Resilient Control in Large-Scale Networked Cyber-Physical Systems Organized sessions at CoDIT, ETFA, CASE conferences Collaborations with Carnegie Mellon, Concordia University, Georgia Tech, and others His research spans constrained predictive control, fault-tolerant strategies, obstacle avoidance for autonomous vehicles, and machine learning integration in control systems. Recent articles emphasize resilient control under network attacks, encrypted MPC, and reinforcement learning for multi-agent systems. He received Best Paper and Best Reviewer awards at international conferences. Best Paper - CoDIT’19 Best Reviewer - IEEE ICAS 2021 FRANZE' has taught undergraduate and graduate courses in Automatic Control, Digital Control, and Robotics at the University of Calabria for over 25 years. He has chaired institutional committees, including the Degree Course Council for Automation Engineering and the Research Committee at DIMEG. His scientific partnerships include institutions like Concordia University, Northeastern University, and Université Libre de Bruxelles.

• Numerical Analysis
• Machine Learning
• Optimization
• +3 more

Luca ZANNI is a Full Professor at the Department of Physical, Computer and Mathematical Sciences, Università di Modena e Reggio Emilia. His academic career spans numerical analysis, machine learning, and optimization methods, with a focus on gradient projection algorithms, stochastic gradient techniques, and their applications in imaging and deep learning. His research includes developing adaptive steplength rules for gradient methods, variance control in stochastic optimization, and GPU-accelerated reconstruction techniques for medical imaging. He teaches courses such as Numerical Calculation with Python, Fundamentals of Machine Learning, and Mathematical Methods for Machine Learning, covering topics like numerical optimization, support vector machines, and deep learning. He has contributed to methodologies for hyperparameter-free training, active set identification in constrained optimization, and edge-preserving image reconstruction. His work bridges theoretical advancements in optimization with practical implementations in large-scale machine learning and medical imaging applications.

• Computer Graphics
• Geometry Processing
• Computational Topology
• +4 more

Michela Spagnuolo is a Research Director at the Italian National Research Council’s Institute of Applied Mathematics and Information Technology (CNR-IMATI-GE) since 2001. Her work bridges Computer Graphics , Geometry Processing , and Computational Topology , with applications in 3D Shape Analysis , Cultural Heritage , and Bioinformatics . Co-supervised 6 PhD theses (plus 2 ongoing) Associate Editor for journals like The Visual Computer and Computers&Graphics Chair of conferences including Shape Modeling International and EG Workshops on 3D Object Retrieval Research Interests : Focus on geometric and semantic modeling of 3D objects , computational topology for shape analysis , and structural/similarity evaluation . Her work enables advanced 3D search engines , semantic annotation , and medical imaging applications . Article Trends : Recent publications emphasize mesh quality indicators for Virtual Element Methods in engineering simulations and semantic-driven 3D model analysis for medical diagnostics and cultural heritage . Key subtopics include topological decomposition , data processing services , and multi-scale modeling . Scientific Awards : Fellow of the Eurographics Association (2014) Notable Contributions : Led projects like IQmulus (geospatial data analytics) and MultiScaleHuman (medical shape modeling). Pioneered CIDOC CRMdig for cultural heritage documentation and developed techniques for kernel computation in polyhedra .

Luigi PomanteView profile

Assistant Professor

• Electronic System-Level HW/SW Co-Design
• Heterogeneous Parallel Systems
• Embedded Systems
• +5 more

Luigi Pomante is a tenured Assistant Professor at the University of L'Aquila, Italy, where he is affiliated with the Department of Engineering and Information Science and Mathematics (DISIM) and the DEWS Center of Excellence. His academic career focuses on research and teaching in embedded systems and hardware-software co-design methodologies. Dr. Pomante's primary research interest is Electronic System-Level Hardware-Software Co-Design of heterogeneous parallel dedicated systems. He is the principal developer of the HEPSYCODE framework, which provides comprehensive methodologies and tools for system-level design space exploration. His work addresses critical challenges in embedded systems development, including handling functional and non-functional requirements, heterogeneous architectures, and mixed-criticality constraints. He has published extensively in journals like IEEE Transactions on Computers and IET Computers & Digital Techniques, as well as at major international conferences. Analysis of Dr. Pomante's publication record reveals a consistent research trajectory focused on hardware-software co-design methodologies, with increasing attention to real-time constraints and mixed-criticality systems in more recent work. His publications demonstrate expertise in design space exploration techniques, system modeling using CSP-like approaches, and the development of metrics for evaluating hardware-software partitioning solutions. The HEPSYCODE framework represents his most significant contribution to the field. Dr. Pomante actively supervises student projects and theses related to electronic design automation and embedded systems. He has contributed to European research projects including EMC2 (Embedded Multi-Core systems for Mixed Criticality applications), where he was responsible for deliverables related to design methodologies, implementation approaches, and validation frameworks. His work has practical applications in aerospace and other safety-critical domains through collaborations with industry partners. He leads the HEPSYCODE research group at DEWS, which focuses on developing methodologies and tools for hardware-software co-design of heterogeneous parallel dedicated systems. The group's current work includes extensions for real-time and mixed-criticality systems, frameworks for embedded system monitoring, and techniques for handling approximate computing and energy/power constraints within the design space exploration process.

Caterina VIOLAView profile

Assistant Professor

• Quantum Algorithms
• Computational Complexity
• Constraint Satisfaction Problems
• +3 more

Caterina VIOLA is a theoretical computer scientist and mathematician currently serving as a Fixed-term Assistant Professor (RTDA) at the Department of Mathematics and Computer Science of the University of Catania . Her research focuses on quantum algorithms for text processing, computational complexity, and constraint satisfaction problems within the National Center for HPC, Big Data and Quantum Computing project. Education: Master's in Mathematics from University of Catania (Erasmus exchange at Universidad de Granada); Doctor rerum naturalium in Mathematics from Technische Universitaet Dresden Her research bridges theoretical computer science and mathematics, with a particular emphasis on approximation algorithms, inapproximability, and numerical semigroups. She has previously worked at the University of Oxford as a post-doctoral researcher and tutor, followed by a post-doc position at Charles University in Prague. Recent publications highlight her work on linear programming relaxations for constraint satisfaction problems, submodular functions, and numerical semigroup analysis. Current teaching responsibilities include Laboratorio di Algoritmi for Computer Science undergraduates and Informatica for Communication Sciences and Languages students. As a Senior Associate Post-doctoral Researcher at Oxford and post-doc at Charles University in Prague, she has developed expertise in mathematical foundations of computational optimization and their practical implementations.

Carlo CALLARIView profile

Associate Professor

• Rational Mechanics
• Structural Mechanics
• Geotechnical Engineering
• +5 more

Prof. Carlo CALLARI is an Associate Professor at the University of Molise, affiliated with the School of Biosciences and Territory. His research focuses on mechanics of solids and structures, rational mechanics, and tunneling. He specializes in computational mechanics, geotechnical engineering, and numerical modeling of quasi-brittle materials. His work includes developing advanced damage models, non-local gradient methods, and hydro-mechanical coupling analysis. Research Interests: Prof. CALLARI’s expertise spans structural mechanics, tunnel engineering, and computational methods. He has pioneered eikonal gradient-enhanced damage models for analyzing material failure in quasi-brittle systems. His studies also address historical engineering practices and modern tunneling innovations, bridging technical and historical perspectives. Publications: His recent work (2024–2020) emphasizes anisotropic damage models, numerical simulations of tunnel stability, and historical analyses of Roman and 19th-century infrastructure projects. His 2022 editorial on soil erosion highlights innovation in numerical methods for geotechnical hazards. Awards: No specific awards listed, but his contributions to computational mechanics and tunnel engineering are widely recognized in academic circles. Grants/Advising: No direct grants or student advisees listed in provided texts, but his active publication record suggests ongoing research collaborations. Labs/Teams: Engaged with computational mechanics and geotechnical engineering research groups at the University of Molise, focusing on numerical methods and infrastructure safety.

• 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.