Find Academic Supervisors

Laura SanitàView profile

Associate Professor

• Combinatorial Optimization
• Approximation Algorithms
• Network Design
• +3 more

Laura Sanità is an Associate Professor in the Department of Computing Sciences at Bocconi University, Milano, Italy. She previously held academic positions at TU Eindhoven (Netherlands) and the University of Waterloo (Canada). Education: Bachelor's in Management Engineering (2003), Università di Roma Tor Vergata Master's in Management Engineering (2005), Università di Roma Tor Vergata PhD in Operations Research (2009), Università Sapienza di Roma Postdoctoral Fellow at EPFL (Switzerland, 2009-2011) Laura's research focuses on discrete mathematics, theoretical computer science, and operations research, with particular emphasis on algorithmic solutions for combinatorial optimization problems. Her work spans approximation algorithms, network design, polyhedral combinatorics, and algorithmic game theory, advancing methodologies for solving complex optimization challenges in theoretical and applied contexts. Her publications demonstrate expertise in network design problems, spanning from fundamental polyhedral characterizations to game-theoretic applications. Key contributions include iterative randomized rounding techniques for Steiner trees, circuit augmentation algorithms, and stabilization approaches for network games. Scientific Awards: NWO-VIDI Award (Netherlands) Discovery Accelerator Supplements Award (NSERC, Canada) Golden Jubilee Research Excellence Award (University of Waterloo) Early Researcher Award (Ontario) Best Paper Award at STOC 2010 Advising & Collaborations: Laura advises PhD students Dylan Hyatt-Denesik and Lucy Verbeck, and collaborates with postdoctoral researchers like Afrouz Jabal Ameli. She has served on program committees and as Associate Editor for top journals including Mathematical Programming, Mathematics of Operations Research, and Operations Research Letters.

Fabio FuriniView profile

Associate Professor

• Combinatorial Optimization
• Operations Research
• Integer Linear Programming
• +3 more

Fabio Furini is an Associate Professor at the Department of Computer Science, Automatics, and Management (DIAG) at Sapienza University of Rome since September 2021. Prior to this position, he served as a CNR researcher at IASI-CNR in Rome (2020-2021), Maître de Conférences at Université Paris-Dauphine, France (2013-2019), postdoctoral researcher at Université Paris-13, France (2012-2013), and research fellow at the University of Bologna (2011-2012). His educational background includes a Ph.D. in Control Engineering and Operations Research from the University of Bologna in 2011. He further obtained the Habilitation à Diriger des Recherches (HDR) in France in 2017 and the National Scientific Qualification for Full Professor in Operations Research in Italy in 2019. Fabio Furini conducts theoretical and methodological research on Combinatorial Optimization and Operations Research. His primary focus is on developing exact algorithms based on decomposition and reformulation techniques for integer linear programming problems. His research spans various applications including network optimization, graph theory, and combinatorial problems such as the maximum clique problem, bin packing problem, and vertex separator problem. His work often bridges theoretical developments with practical applications in transportation, logistics, and network security. His recent publications demonstrate a strong focus on exact algorithms for combinatorial optimization problems, particularly in network interdiction, bin packing with temporal constraints, and graph-based problems. His work consistently combines integer programming techniques with combinatorial search methods to develop novel formulations and efficient solution approaches that advance the state-of-the-art in these domains. Among his notable scientific awards are the Prime d'encadrement doctoral et de recherche (PEDR), which he received annually from 2014 to 2020, recognizing him among the top 15% of researchers in the French university system. He also holds the prestigious Habilitation à Diriger des Recherches from France (2017) and the National Scientific Qualification for Full Professor in Operations Research from Italy (2019). Fabio Furini has been actively involved in supervising PhD students and has served as principal investigator for numerous national and international research projects. His extensive network includes over 60 co-authors across European and American universities. He is also a member of the editorial boards for three prestigious international journals: Omega, Annals of Operations Research, and Discrete Applied Mathematics. His research activities include collaborations with various institutions across Europe and the United States, including Imperial College London and the University of Colorado. These collaborations have resulted in a robust research program focused on advancing the theoretical foundations and practical applications of combinatorial optimization.

Ciriaco D'AmbrosioView profile

Researcher

• Combinatorial Optimization
• Heuristics
• Metaheuristics
• +4 more

Ciriaco D'Ambrosio is a Research Fellow at the Department of Mathematics, University of Salerno, specializing in combinatorial optimization and its applications to wireless sensor networks. He teaches courses in operations research and maintains regular reception hours for students on Tuesdays (3:00-5:00 PM) and Wednesdays (4:00-5:00 PM), conducted both in-person and via Microsoft Teams. Education: PhD in Computer Science, University of Salerno (2015) - Thesis: models and algorithms for coverage in Wireless Sensor Network Laurea cum laude in Computer Science, University of Salerno (2011) Research Focus: D'Ambrosio specializes in combinatorial optimization, developing heuristics, metaheuristics, and math-heuristics for mixed integer linear programming problems. His work addresses challenging optimization problems in wireless sensor networks, particularly network lifetime maximization under coverage, connectivity, and interference constraints. His research bridges theoretical computer science with practical applications in sensor network design, seismic monitoring systems, and resource allocation problems. His methodology often combines exact approaches with sophisticated heuristic techniques to solve computationally difficult problems. Publication Trends: Analysis of D'Ambrosio's publications (2017-2025) reveals a progression from foundational work on sensor network lifetime problems toward increasingly sophisticated algorithmic approaches for combinatorial optimization. His recent work shows expansion into seismic monitoring applications while maintaining strong focus on knapsack problem variants and network optimization. His publications appear in high-quality journals including Soft Computing, Computers & Operations Research, and Networks, demonstrating both theoretical rigor and practical relevance of his research. Professional Activities: Member of the Italian Operations Research Society (AIRO) Associate Editor for Soft Computing, A Fusion of Foundations, Methodologies and Applications Active collaborator with researchers including Andrea Raiconi, Raffaele Cerulli, and Francesco Carrabs Research Infrastructure: D'Ambrosio works within the Department of Mathematics at University of Salerno's Fisciano Campus (Building F2, Room 040). His research contributes to the university's growing expertise in computational optimization and has practical applications in environmental monitoring systems like SEISMONOISY.

Gabriele BernardiniView profile

Researcher

• Urban Risk Assessment
• Built Environment Safety
• Disaster Management
• +4 more

Gabriele Bernardini is a Researcher at the Department of Civil, Building and Architectural Engineering within the Faculty of Engineering at Università Politecnica delle Marche (UNIVPM) in Ancona, Italy. His office is located at via brecce bianche 12, Ancona in the DICEA, Construction Section (quota 150), where he holds office hours on Wednesdays from 9-11 AM. His work focuses on the intersection of built environment safety, risk assessment, and innovative technological applications for urban resilience. Dr. Bernardini's research interests center on multi-risk assessment and mitigation in urban built environments, particularly addressing flood risks, terrorist threats, and heatwave vulnerabilities in historical contexts. His work employs innovative methodologies including virtual reality simulations, behavioral design approaches, and data-driven predictive models. He has developed frameworks for measuring user exposure and vulnerability, optimizing evacuation paths, and creating integrated wayfinding systems for emergency situations. His research bridges the gap between theoretical risk assessment and practical implementation in real-world urban settings, with a special focus on preserving historical character while enhancing safety. Analysis of his recent publications (2021-2025) reveals a consistent focus on multi-risk scenarios in urban environments, particularly examining how different hazards interact in historical settings. His work demonstrates increasing sophistication in methodology, moving from basic risk assessment to integrated multi-risk frameworks that consider user behavior, environmental factors, and technological solutions. A significant portion of his research applies virtual reality and extended reality technologies to safety training and evacuation planning, showing the evolution from theoretical models to practical applications with real-world testing. His research has practical applications across multiple domains including urban planning, emergency management, and building maintenance. Through his work on automatic detection systems using maintenance requests and predictive management approaches, he's contributing to more responsive building management practices. His case studies on specific locations like Matera demonstrate the translation of theoretical frameworks into context-specific solutions for historic urban environments.

Stefano BraccoView profile

Associate Professor

• Power Systems
• Microgrids
• Renewable Energy Integration
• +3 more

Stefano Bracco is an Associate Professor in the Department of Naval, Electrical, Electronic, and Telecommunications Engineering (DITEN) at the University of Genoa, Italy, serving on both the Department Board and the School Council of the Polytechnic School. He teaches advanced courses including Energy Transition and Power Systems Management for Master's programs in Energy Engineering, Management for Energy and Environmental Transition (MEET), and Engineering for Natural Risk Management, covering critical topics in sustainable power systems and infrastructure modeling. His research focuses on power systems engineering with emphasis on microgrid optimization, renewable energy integration, and electric vehicle infrastructure. Key contributions include energy management systems (EMS) for active/reactive power control in microgrids, vehicle-to-grid/home technologies, and sustainable energy community design. His work addresses grid stability challenges, economic optimization of distributed energy resources, and resilience enhancement in critical facilities through advanced mathematical modeling and real-world case studies. Analysis of his 15 most recent publications (2024-2025) reveals consistent application of mixed-integer linear programming (MILP) for microgrid optimization across diverse contexts including university campuses, industrial sites, and Italian municipalities. Dominant trends include integration of electric vehicle charging infrastructure with renewables, uncertainty handling in renewable communities, and multi-scale control frameworks for automated transportation. His research bridges theoretical optimization with practical implementation, frequently using the Savona University Campus as a living laboratory for sustainable energy solutions. No scientific awards were mentioned in the provided information. The available text did not specify any advised students or research grants, though his extensive publication record suggests active research supervision and project leadership. While no dedicated laboratories are explicitly attributed to him, his work frequently involves the Savona University Campus infrastructure, including the CN MOST Laboratory and microgrid test facilities, indicating collaboration with existing university energy research platforms.

• Fracture Mechanics
• Solid Mechanics
• Finite Fracture Mechanics
• +14 more

Pietro Cornetti is an Associate Professor in the Department of Structural, Building and Geotechnical Engineering (DISEG) at the Politecnico di Torino, where he also serves as Coordinator of the Doctoral School in Civil and Environmental Engineering. He is a member of the SISCON Interdepartmental Center for the Safety of Infrastructures and Constructions and the Doctoral School Council. His academic career has been deeply rooted at Politecnico di Torino, where he completed his education and has held continuous academic positions since 1999. His research interests span a broad spectrum of solid and fracture mechanics, with a focus on finite fracture mechanics , fractional calculus , fractal geometry , non-local elasticity , size effects in concrete and granular materials, and structural retrofitting using FRP/FRCM systems . His work bridges theoretical mechanics with practical applications in civil engineering and structural integrity. The 15 most recent publications highlight a strong trend toward integrating advanced mathematical frameworks—particularly fractional calculus and phase-field modeling—with classical and finite fracture mechanics. These works address brittle fracture, dynamic crack propagation, fatigue in composites, and debonding phenomena, demonstrating a consistent focus on improving predictive models for structural failure across scales. He actively mentors PhD students and leads major research initiatives, including the H2020-funded NEWFRAC project and the nationally funded REHARZE project on retrofitting historic architecture for zero emissions. His teaching portfolio includes Solid Mechanics, Structural Mechanics, Fracture and Plasticity, and advanced topics in computational mechanics across undergraduate, master's, and doctoral levels. He is affiliated with several professional organizations: Italian Group of Fracture (IGF) Italian Association of Applied and Theoretical Mechanics (AIMETA) European Structural Integrity Society (ESIS), Technical Committee TC16 He has served on the program committee of the International Conference on Fracture (ICF14) and participated in the organizing committee of AIMETA XXI. His research is supported by competitive grants from national (PRIN) and EU (H2020) funding programs. He supervises a research group focused on fracture mechanics and leads the Laboratorio di Meccanica della Frattura (DISEG) , which supports experimental and computational research in structural integrity. His team works on both theoretical developments and practical applications in civil and environmental engineering.

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.

Stefan WeltgeView profile

Professor

• Combinatorial Optimization
• Linear Programming
• Integer Programming
• +3 more

Stefan Weltge is a Professor of Discrete Mathematics at the Technical University of Munich (TUM). His research focuses on combinatorial optimization, linear and integer programming, and polyhedral combinatorics. He has received multiple teaching awards at TUM, including the Best Lecturer in Electrical and Computer Engineering (2019) and Best Advanced Course awards in Mathematics (2020/21, 2019). He also earned the Best Dissertation Award from the University of Magdeburg (2016). Education: PhD in Mathematics (University of Magdeburg), Postdoc (ETH Zurich) Research Grants: Funded by the German Research Foundation (DFG) via an Individual Grant (NextGen) and the PhD Program AdONE Professional Roles: Program Committee member for IPCO 2023, MIP 2022, ISCO 2022, ISCO 2020, ISCO 2018; Organizer of OR 2024, MIP 2022, and Cargese Workshops on Combinatorial Optimization (2024, 2022)

Giampaolo LiuzziView profile

Associate Professor

• Nonlinear Optimization
• Global Optimization
• Mixed Integer Nonlinear Programming
• +3 more

Giampaolo Liuzzi is an Associate Professor at the Department of Computer, Automation, and Management Engineering 'Antonio Ruberti' (DIAG) at Sapienza University of Rome since July 2023. Previously, he was a fixed-term researcher at the same department (July 2020-June 2023) and a Senior Researcher at the Institute of Systems Analysis and Computer Science 'A. Ruberti' of the CNR until July 2020. He teaches Mathematical Programming, Complements of Mathematics, and Mathematical Analysis 2 for various engineering programs at Sapienza University. Dr. Liuzzi's research focuses on Nonlinear Optimization , particularly derivative-free methods for constrained and unconstrained optimization, global optimization, mixed integer nonlinear programming, and applications in operations research and machine learning. His work spans theoretical developments in optimization algorithms as well as practical applications in engineering design, simulation-based optimization, and biomedical systems. He has made significant contributions to derivative-free optimization techniques that don't require gradient information, which is particularly valuable for black-box optimization problems where derivatives are unavailable or expensive to compute. His recent publications (2022-2025) demonstrate a strong focus on advancing derivative-free optimization methods, with particular attention to complexity analysis, convergence properties, and practical implementations for challenging problem classes including nonsmooth, constrained, multi-objective, and mixed-integer optimization problems. His work bridges theoretical computer science with practical engineering applications, with publications appearing in top optimization journals like Optimization Methods & Software, Computational Optimization and Applications, and Journal of Optimization Theory and Applications. Dr. Liuzzi has received significant professional recognition through National Scientific Habilitations for both Associate Professor (2014) and Full Professor (2018) positions in Italy. He is actively involved in the academic community as an administrator of the Derivative-Free Library (DFL), a collection of algorithms and methods for derivative-free optimization developed through collaboration among several prestigious Italian research institutions. As an educator, Dr. Liuzzi has developed comprehensive teaching materials for courses in Mathematical Programming, Complements of Mathematics, and Mathematical Analysis. He is also engaged in academic entrepreneurship as a co-founder of DEIX s.r.l., a Sapienza startup focused on algorithms and industrial software for planning and control of complex systems. Additionally, he organized the 2nd Derivative-Free Optimization Symposium (DFOS'24) in June 2024 in Padua, highlighting his leadership role in this specialized optimization community.

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.

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.

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)

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.