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Marco D'AnnaView profile

Professor

• Commutative Algebra
• Numerical Semigroups
• Good Semigroups
• +6 more

Marco D'Anna is a Full Professor of Algebra at the Department of Mathematics and Computer Science, University of Catania, where he has worked since 1997. His academic career includes significant institutional roles including Head of the Master's Degree Course in Mathematics (2012-2015, 2018-2020) and Vice-director of the Department of Mathematics and Computer Science (2015-16). Dr. D'Anna earned his Mathematics degree with honors (110/110) from the University of Rome 'La Sapienza' in 1991, completed his PhD there in 1996 with a thesis on 'Canonical module of reduced rings of dimension one and their associated semigroups,' and conducted research visits at Purdue University under Professor William J. Heinzer. His research focuses on Commutative Algebra, particularly numerical semigroups, good semigroups (including value semigroups of curve singularities), one-dimensional rings, and ideal theory. He has published 43 scientific papers and a monograph, and has been scientific organizer of multiple international meetings including INdAM workshops in Cortona and Rome. As an educator, Professor D'Anna teaches Algebra and Commutative Algebra courses for both undergraduate and graduate Mathematics programs. He has supervised numerous bachelor's and master's theses (with four winning the Anile Prize in 2009, 2012, 2016, and 2022), advised eight PhD students to successful completion, and currently mentors one PhD student. Premio di Laurea 'Angelo Marcello Anile' for student theses (2009, 2012, 2016, 2022) Socio corrispondente residente of Acccademia Gioenia di Catania (2022) Professor D'Anna serves as coordinator of the Laboratory in Commutative Algebra and Algebraic Geometry and has been Principal Investigator for the local research project 'Proprietà locali e globali di anelli e varietà algebriche' (PIACERI 2020-22), while also participating in the national PRIN 2020 project 'Squarefree Gröbner degenerations, special varieties and related topics.' Since 2015, he has organized the Algebra and Algebraic Geometry seminar series at the University of Catania.

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.

Riccardo FelicettiView profile

Research Fellow

• Fault Detection and Diagnosis
• Fault Tolerant Control
• Optimization
• +3 more

Riccardo Felicetti is a Research Fellow at the Department of Information Engineering, Università Politecnica delle Marche, within the Faculty of Engineering. He holds a Master's Degree (cum laude) in Computer and Automation Engineering (2016) and a Ph.D. (cum laude) in Information Engineering (2021) from the same university, with a thesis on “Active fault tolerant control for overactuated unmanned vehicles.” He also serves as Senior Tutor, coordinating tutor activities in the Faculty of Engineering. His research focuses on fault detection and diagnosis, fault-tolerant control, and optimization, with applications to unmanned vehicles (e.g., drones, ROVs) and energy management systems. He has contributed to advancements in systems like actuator fault tolerance, vibration-based fault detection, and energy optimization in smart grids. Key technical areas include disturbance observer-based control, adaptive Kalman filtering, and machine learning integration for system identification. His work bridges theoretical control frameworks with practical implementations in aerospace and marine robotics.

Antonio ServettiView profile

Assistant Professor

• Speech and Audio Processing
• Multimedia Communications
• Real-Time Multimedia Network Protocols
• +7 more

Antonio Servetti is an Assistant Professor at the Department of Control and Computer Engineering (DAUIN) at Politecnico di Torino, Italy, where he has been a faculty member since 2007. He is affiliated with the Internet Media Group (IMG) and the Interdepartmental Center PIC4SeR for Service Robotics. His work bridges multimedia processing, network communications, and web technologies. MS in Computer Engineering, Politecnico di Torino, 1999 PhD in Computer Engineering, Politecnico di Torino, 2004 Visiting Scholar, University of California, Santa Barbara, 2003 His research focuses on speech and audio processing , multimedia communications over wired and wireless networks , and real-time web-based multimedia applications . Key interests include WebRTC, Web Audio, HTTP adaptive streaming, and perceptual quality assessment. He has contributed to the development of secure multimedia transmission techniques, including selective encryption of speech and audio. The recent publications highlight a strong trend toward AI-driven modeling of subjective quality in multimedia, especially through deep learning for image and video quality prediction, understanding observer behavior, and remote music performance systems. His work often involves collaboration with researchers in the VQEG JEG-Hybrid group and the NEXA Center. Best Paper Award, Web Audio Conference 2021 Dr. Servetti has led and contributed to several research projects, including BRIC-2024 (acoustics in educational settings), PNRR HiFiReM (remote music education), and INAR (artistic research). He teaches courses such as 'Web Applications', 'Machine Learning for Vision and Multimedia', and 'Digital Audio Processing' across various engineering programs. He is also involved in educational governance as a member of academic councils for multiple degree programs. He is a core member of the Internet Media Group (IMG) , which focuses on multimedia processing and transmission, and contributes to the VQEG JEG-Hybrid working group on video quality assessment, where he develops frameworks for reproducible research and modeling of human perception.

Francesca VocaturoView profile

Associate Professor

• Operations Research
• Logistics
• Optimization
• +4 more

Francesca Vocaturo serves as Associate Professor of Operations Research at the University of Calabria's Department of Economics, Statistics and Finance (DESF), where she has maintained continuous academic affiliation since 2003. Her teaching portfolio includes Operations Research for Master's programs in Business Administration and Management, and Mathematical Methods for Economics for undergraduate Economics students, with documented teaching loads of 63+ hours annually through the 2024/25 academic year. Her research expertise centers on Logistics Optimization with specialized focus on stochastic vehicle routing, urban transportation systems, and crowdshipping applications. Key methodological contributions span combinatorial optimization, dynamic programming, and simulation-based approaches to solve complex logistics challenges under uncertainty. Current projects integrate machine learning with optimization frameworks for sustainable mobility solutions. Recent publication trends (2021-2025) reveal concentrated advancement in dynamic logistics systems , particularly crowdshipping models, real-time inventory routing, and risk-aware transportation planning. Her work bridges theoretical algorithm development with practical applications in postal services, hazardous material transport, and public transit optimization. Notable recognition includes: Editors' Choice Article selection by the European Journal of Operational Research (2020) She has supervised 26 Master's theses in Business Administration covering topics from inventory management to green logistics, plus the PhD dissertation of Sara Stoia on crowdshipping. As Local Coordinator for the national PRIN2020 project ULTRA OPTYMAL , she leads research on optimization under uncertainty for urban logistics, while previously contributing to projects like SOLIDO (industrial logistics) and GREENPLAN (workforce optimization). Vocaturo actively collaborates with the TESEO laboratory (Tecnologie di Simulazione e Ottimizzazione) and the Quantitative Methods for Economics, Finance and Management research group within DESF, maintaining international partnerships through research stays at the University of Montreal, University of Valencia, and teaching engagements in Portugal.

Anna Chiara LaiView profile

Researcher

• Control Systems
• Fractional Calculus
• Optimal Control
• +3 more

Anna Chiara Lai is a Researcher at the Department of Basic and Applied Sciences for Engineering at Sapienza University of Rome. Her academic work focuses on control systems, fractional calculus, and robotics modeling. She teaches courses in Mathematical Analysis and Mathematical Methods for Engineering students. Her research explores topics such as optimal control strategies for soft manipulators, fractional differential equations in epidemic modeling, and stability analysis of unbounded control systems. Her research interests include control theory applications (e.g., robotic arms, hyper-redundant systems), fractional calculus (e.g., generalized binomials, SIS models), and mathematical modeling in epidemiology and mechanics. Recent work emphasizes bio-inspired robotics, such as octopus tentacle mechanics and soft manipulator optimization. Her publications span journals like Acta Mathematica Hungarica , Journal of Optimization Theory and Applications , and SIAM Journal on Control and Optimization . She contributes to projects like Mathematical control models and applications , aiming to bridge theoretical control systems with practical engineering solutions. Dr. Lai’s advising and grants are not explicitly detailed, but her teaching and research reflect a strong commitment to both academic instruction and applied scientific exploration. She maintains an institutional email (annachiara.lai@uniroma1.it) and actively engages with students via Google Classroom for course materials and office hours (Mondays 1:30–3:30 PM).

• Operational Research
• Optimization Methods
• Logistics and Supply Chain Management
• +7 more

Manuel Iori is a Full Professor at the Department of Engineering Sciences and Methods, University of Modena and Reggio Emilia (UNIMORE), Italy. His primary research focuses on operational research, optimization methods, and logistics systems. He specializes in vehicle routing problems, scheduling algorithms, and decision support systems with applications in industrial automation, healthcare, and service industries. Iori is actively involved in teaching advanced optimization courses for engineering students, emphasizing practical applications in data-driven decision-making and simulation. Research Interests: His work addresses complex optimization challenges such as multi-trip vehicle routing with time windows, scheduling under resource constraints, and tool switching in manufacturing systems. He integrates machine learning and metaheuristics to develop innovative solutions for logistics, production planning, and healthcare operations. Collaborations with industry partners (e.g., pharmaceutical distributors, printing companies) ensure practical relevance of his research. Teaching: Iori teaches courses like Optimization Methods for Data-Driven Engineering Processes , Models for Logistics and Production Optimization , and Methods and Algorithms for Optimization in Digital Industries . These courses combine theoretical foundations with hands-on labs using tools like Python, Xpress, and Anylogic. Key Contributions: He developed decision support systems for multi-trip routing in pharmaceutical distribution and supplier selection in facility management. His research on satellite scheduling and attended home delivery systems advances both theoretical and applied domains. As a member of CIRRELT (Canada), he collaborates on logistics optimization projects. Professional Activities: Iori’s work is reflected in over 80 peer-reviewed publications and contributions to conferences. He advises graduate students on optimization challenges and serves as a reviewer for top journals in operations research.

Renato BruniView profile

Associate Professor

• Optimization
• Machine Learning
• Bioinformatics
• +10 more

Renato Bruni is Associate Professor at the Department of Computer, Control and Management Engineering of Sapienza University of Rome , Italy. He teaches in the Management Engineering and Bioinformatics study programs. His research focuses on Optimization, Machine Learning, and Bioinformatics , with applications spanning spacecraft control, biomedical engineering, and financial portfolio management. Research Interests His scientific activity is centered on: Combinatorial Optimization Data Mining and Classification Derivative-free Optimization Computational Molecular Biology Information Reconstruction Recent Research Trends The analysis of his publications reveals a strong focus on: Power distribution network optimization Spacecraft attitude control via mathematical programming Higher education data quality and institutional heterogeneity Robust classification with limited training data Stochastic dominance in portfolio selection Physician scheduling optimization Grants and Collaborations Principal Investigator in Sapienza-funded projects (2013–2019) Member of EU H2020 RISIS 2 project (2019–2022) Collaboration with international experts: Peter L. Hammer (Rutgers), Fabio Tardella (Sapienza), and Istat (Italian National Statistical Institute)

• Game Theory
• Control Systems
• Multi-agent Systems
• +4 more

Paolo Scarabaggio is an Assistant Professor (RTDA) at the Decision and Control Laboratory of Polytechnic University of Bari, Italy. He received his Ph.D. in Electrical and Information Engineering from the same institution and completed a research visit at the Delft Center for Systems and Control, Technical University of Delft in 2019. His academic work spans multiple high-impact publications across IEEE journals and conferences, with a focus on interdisciplinary applications of control theory. His research interests center around modeling, optimization, game theory, and control of complex multi-agent systems , with practical applications in energy distribution systems, social networks, warehouse automation, and collaborative robotics. His work demonstrates strong interdisciplinary connections between theoretical control concepts and real-world industrial applications, particularly in Industry 4.0 contexts. Dr. Scarabaggio's publications reveal a consistent trajectory of increasingly sophisticated applications of game theory and optimization techniques to emerging challenges in energy systems, logistics automation, and human-robot interaction. His research shows particular strength in developing mathematically rigorous frameworks that address practical constraints in real-world systems. 2022 IEEE CSS Italy Best Young Author Journal Paper Award As an educator, Dr. Scarabaggio teaches courses including Analisi e Simulazione dei Sistemi, Fondamenti di Automatica, and Game Theory for Controlling Autonomous Systems. His research collaborations span multiple institutions and industries, with frequent co-authorship with researchers from Polytechnic University of Bari and international partners. His work often addresses practical implementation challenges while maintaining theoretical rigor, making significant contributions to both academic knowledge and industrial applications.

Fabio D'agostinoView profile

Researcher

• Electrical Engineering
• Power Systems
• Naval Engineering
• +3 more

Fabio D'agostino is a Researcher at the University of Genoa , affiliated with the Department of Naval, Electrical, Electronic and Telecommunications Engineering (DITEN). He teaches courses such as Shipboard Power System Control , Naval Electric Propulsion , and Elements of Electrical Protection and Safety for undergraduate and graduate programs in Electrical and Naval Engineering. Research Interests : Shipboard Power Systems DC Microgrids Hybrid Energy Storage Smart Grids Optimization Algorithms Maritime Decarbonization Publications focus on real-time co-simulation, power quality analysis, and optimal control strategies for naval and port energy systems. His work addresses stability, efficiency, and sustainability in electrical grids for marine applications. Labs : Involved in the ENET-RT lab and ShIL Project infrastructure for multi-domain marine co-simulation.

FRANCESCO FERRACUTIView profile

Researcher

• Control Systems
• Robotics
• Brain-Computer Interfaces
• +6 more

Prof. Francesco Ferracuti is a Researcher at the Department of Information Engineering (Università Politecnica delle Marche, Ancona, Italy). His work focuses on advanced control systems, robotics, brain-computer interfaces, and energy management. Key research themes include fault-tolerant control, autonomous navigation, and human-machine interaction through wearable sensors. Research interests span across: Control Engineering (MIMO systems, PID control, Model Predictive Control) Robotics (mobile robotics, UAVs, smart wheelchairs) Neuroengineering (EEG-based BCI, cognitive workload assessment) Energy Systems (renewable integration, home energy management) Data-Driven Methods (machine learning, system identification) Publications emphasize innovative solutions like EEG-driven obstacle avoidance and thermal stress monitoring for smart wheelchairs, demonstrating interdisciplinary approaches combining robotics with biometrics. His work on fault detection in multirotors and energy optimization algorithms highlights practical applications in both industrial and healthcare domains. Current projects include the E-MOTIVE initiative for mobility solutions via affective computing and BCI. His lab develops cutting-edge algorithms for cyber-physical systems security and predictive maintenance in industrial equipment.

• Performance Engineering
• Cloud Computing
• Machine Learning
• +3 more

Emilio Incerto is an Assistant Professor at the IMT School for Advanced Studies Lucca, Italy. His research focuses on performance engineering, cloud computing, and formal methods applied to systems optimization. He specializes in developing frameworks for performance prediction, autoscaling solutions for microservices, and integrating machine learning techniques into performance modeling. Key research areas include: Performance modeling and optimization of distributed systems Autoscaling algorithms for dynamic cloud workloads Formal verification of real-time software systems AI-driven performance control mechanisms He has organized international workshops such as AIPerf (Artificial Intelligence for Performance Modeling), showcasing leadership in bridging AI and performance engineering. His work frequently explores reproducibility in performance studies and quantitative evaluation of complex systems like flocking behaviors in biological simulations. Notable contributions include μOpt (an efficient autoscaler for microservices) and μP (a performance prediction framework). His research emphasizes practical implementation of theoretical models through frameworks like SystemC-based environments for HW/SW co-design.

Mirco TribastoneView profile

Professor

• Stochastic Processes
• Dynamical Systems
• Performance Engineering
• +4 more

Dr. Mirco Tribastone is Full Professor of Computer Science at IMT School for Advanced Studies in Lucca, Italy, where he leads the SySMA research unit and serves as Deputy Rector. His research focuses on quantitative modeling of concurrent and distributed systems using stochastic processes and differential equations. Primary research streams: Algorithms for aggregation of dynamical systems Performance self-adaption of software systems Inference methods for probabilistic programs Formal methods for biological systems Professor Tribastone has supervised numerous PhD students and leads research projects on cyber-physical systems and adaptive software. His tool development includes ERODE for differential equation analysis and DiffLQN for layered queuing networks. Recent publications demonstrate advanced work in model reduction techniques for chemical reaction networks, optimal autoscaling for microservices, and novel approaches to quantum circuit verification.

• Machine Learning
• Optimization
• Data Mining
• +2 more

Dr. Annabella Astorino is a researcher at ICAR-CNR (Italian National Research Council) in Rende, Italy, with expertise in machine learning, optimization, and computational biology. Her work focuses on classification algorithms using nonsmooth optimization, spherical separation, and multiple instance learning (MIL) approaches. Key Research Themes Geometric separation techniques (polyhedral, spherical) Multiple instance learning for biomedical applications Nonsmooth optimization in semisupervised learning Clustering methods for edge detection in images Recent publications highlight her development of Lagrangian relaxation for MIL, kernel-enhanced spherical separation algorithms, and DC optimization for computer vision tasks. Her collaborations include researchers like A. Fuduli, M. Gaudioso, and P. Veltri.

Silvia ColabianchiView profile

Research Fellow

• Industry 4.0 / 5.0
• Human-machine collaboration
• Cyber-resilience of socio-technical systems
• +4 more

Silvia Colabianchi is a researcher and assistant professor („Ricercatore“) at the Department of Computer, Control and Management Engineering „Antonio Ruberti“ of Sapienza University of Rome, where she teaches the Smart Factory course in the Master’s programmes in Management and Mechanical Engineering. Born in Rome in 1994, she obtained her PhD in Industrial and Management Engineering from the same university in 2023 with a dissertation on human-centred cyber-resilience of socio-technical systems. Education: PhD in Industrial and Management Engineering, Sapienza University of Rome, 2023 MSc in Management Engineering, Sapienza University of Rome, 2019 Scientific high-school diploma, Liceo Scientifico “PNI”, Rome Research interests revolve around the integration of cutting-edge digital technologies into manufacturing from a human-centric, Industry 5.0 perspective. She combines computer vision, large language models and immersive virtual reality to improve quality inspection, operator assistance and occupational safety, while investigating cyber-resilience, organisational learning and sustainable/circular product design. Her 2023-2025 publications show a clear trend toward AI-enabled manufacturing support (digital assistants, LLMs, conversational agents), advanced training technologies (VR, Safety-II, ergonomic pose detection) and resilience assessment (fuzzy maturity models, storytelling-based studies, warehouse and supply-chain disruptions). Interdisciplinary work spans from industrial engineering and operations management to behavioural cybersecurity and space manufacturing logistics. She is member of the scientific sector ING-IND/17 “Industrial Mechanical Systems” and actively collaborates on national and international projects that apply machine-learning models, data-analysis dashboards and immersive tools to real industrial environments. Office: Room A125, Via Ariosto 25, 00185 Rome, Italy Phone: +39 06 7727 4036 (int. 35036) Email: silvia.colabianchi@uniroma1.it