Find Academic Supervisors

• Systems Engineering
• Control Engineering
• Discrete Event Systems
• +7 more

Mariagrazia Dotoli is a Full Professor in Systems and Control Engineering at the Polytechnic University of Bari, Department of Electrical and Information Engineering, where she has been serving since 1999. She previously held the position of Vice Rector for Research (2011-2013) and served as a member elect of the Academic Senate (2012-2015). Currently, she coordinates the interuniversity PhD course in Industry 4.0 between the Polytechnic University of Bari and the University of Bari Aldo Moro. Her research interests span across multiple domains of systems engineering, with particular focus on discrete event industrial systems, Petri nets, manufacturing systems, supply chains, logistics and transportation systems, traffic networks, and energy systems. Her work bridges theoretical control systems with practical industrial applications, especially in the context of Industry 4.0 and smart manufacturing. Her extensive publication record demonstrates consistent contributions to automation science and engineering, with recent work focusing on warehouse optimization, collaborative robotics, supply chain management, and smart energy systems. Her research shows a clear trend toward integrating classical control theory with modern computational approaches, including machine learning and optimization algorithms for industrial applications. Prof. Dotoli maintains significant editorial responsibilities as Senior Editor of the IEEE Transactions on Automation Science and Engineering and Associate Editor for multiple IEEE journals. She has organized and chaired numerous international conferences including CASE2024, MED2021, and CODIT2020, demonstrating leadership in the automation community. Her academic career shows continuous progression from Assistant Professor (1999) to Full Professor, with additional leadership roles in university administration and international professional organizations. She remains actively engaged in both theoretical research and practical industrial applications of control systems engineering.

Graziana CavoneView profile

Associate Professor

• Automatic Control
• Model Predictive Control
• Cyber-Physical Systems Security
• +5 more

Associate Professor Graziana Cavone is with the Department of Civil, Computer and Aeronautical Technologies Engineering at Roma Tre University, Rome, Italy. Her research integrates automatic control, optimisation and AI to guarantee safe, secure and efficient operations of cyber-physical systems ranging from industrial robots and drones to water networks and intermodal freight terminals. Education & affiliation: Department of Civil, Computer and Aeronautical Technologies Engineering, Roma Tre University Scientific disciplinary sector ING-INF/04 – Automatic Control Research interests revolve around four pillars: (i) model-predictive and data-driven control of complex dynamic systems, (ii) safe and ergonomic human-robot/human-drone interaction in logistics 4.0 environments, (iii) cyber-security and resilience of industrial control and water-supply networks, and (iv) stochastic optimisation and Petri-net modelling for railway traffic and intermodal freight terminals. Recent 2024-2025 publications exhibit a clear trend toward AI-enabled anomaly detection, digital-twin security frameworks, and socio-technical studies on robot acceptance, while earlier work concentrated on COVID-19 mitigation control and collaborative-robot motion planning. Scientific awards & editorial activity: Guest-editor for IEEE CASE 2018 special section, publicity chair for IEEE CASE 2023; specific prizes not listed in supplied text. Advising & grants: No explicit student lists or funded-project details are provided in the source. Labs & teams: No dedicated laboratory designation is mentioned; research is conducted within the departmental laboratories of Roma Tre University.

• Financial Mathematics
• Investment Analysis
• Capital Budgeting
• +4 more

Carlo Alberto MAGNI is a Full Professor in the Department of Economics "Marco Biagi" at the University of Modena and Reggio Emilia. He teaches courses including General and Financial Mathematics and Principles and Models for Managerial Decisions for the Business Economics and Management degree program. Professor MAGNI's research focuses on financial mathematics, investment analysis, and capital budgeting. His work centers around the development of the Split-Screen Approach for project appraisal, which unifies financial planning and investment analysis into a single theoretical framework. His research spans corporate finance, accounting, operations research, and mathematical methods of economics, with particular emphasis on NPV-consistency of rates of return, project valuation methodologies, and financial modeling techniques. His publication record shows a consistent output of high-quality research, with numerous articles in top journals. His work demonstrates a strong integration between theoretical finance concepts and practical applications, particularly in Excel-based financial modeling. The Split-Screen Approach represents his signature contribution to the field, providing innovative methods for project appraisal and financial planning. Professor MAGNI has developed comprehensive teaching materials, including a videobook for his courses that combines video lectures with texts related to course topics. His educational approach emphasizes the application of mathematical tools in economic and business analysis, with focus on developing students' ability to model and evaluate long-term managerial decisions.

Adam Teodor PolakView profile

Assistant Professor

• Algorithms
• Fine-Grained Complexity
• Learning-Augmented Algorithms
• +3 more

Adam Teodor Polak serves as an Assistant Professor in the Department of Computing Sciences at Bocconi University, where his research centers on theoretical algorithms with dual emphases on fine-grained complexity and learning-augmented algorithms. His work investigates fundamental questions about computational hardness while developing prediction-enhanced algorithms that maintain worst-case guarantees. Polak earned his PhD from Jagiellonian University in 2019 under Paweł Idziak, including a research visit at MIT with Virginia Vassilevska Williams. He subsequently held postdoctoral positions at the Max Planck Institute for Informatics and EPFL before joining Bocconi. His research program addresses why computational problems resist efficient solutions and how imperfect predictions can robustly improve algorithmic performance. This manifests in two interconnected streams: establishing conditional lower bounds for problems like 3SUM and Orthogonal Vectors, and designing learning-augmented frameworks for dynamic graph problems, caching, and optimization that blend theoretical rigor with practical machine learning insights. Recent publications reveal accelerating momentum in algorithms with predictions, with over half of his 2023-2025 output appearing in top ML venues (ICML, NeurIPS, ICLR) alongside traditional theory conferences (STOC, SODA). This cross-pollination demonstrates how worst-case theoretical guarantees can coexist with data-driven performance gains across graph algorithms, scheduling, and combinatorial optimization. Scientific recognition includes: Best Paper Award at ESA 2024 for knapsack algorithm breakthroughs Bronze Medal at ACM ICPC World Finals (2011) 2nd Place in PACE 2018 Challenge for Steiner tree algorithms Polak actively shapes the field through program committee service (ESA, ICALP, SOSA) and community building, notably co-organizing the 2022 Workshop on Algorithms with Predictions (ALPS) and decade-long high-school algorithmics workshops. His industry collaborations with Teroplan and Google demonstrate real-world impact in route planning and distributed systems. Current teaching includes graduate Algorithms courses at Bocconi, while his experimental work on GPU-accelerated graph algorithms and medical computer vision continues to bridge theoretical insights with practical implementation challenges.

Laurent PoirrierView profile

Adjunct Professor

• Discrete Optimization
• Computational Optimization
• Mathematical Programming
• +3 more

Laurent Poirrier is an Adjunct Professor in the Department of Computing Sciences at Bocconi University in Milan, Italy. Previously, he was affiliated with the Combinatorics and Optimization department at the University of Waterloo. His academic work spans both theoretical and applied aspects of optimization, with a focus on computational methods. Dr. Poirrier's research interests center on the computational aspects of discrete optimization, with particular emphasis on the implementation of fast optimization algorithms. His work encompasses linear algebra, combinatorics, and numerical analysis as they relate to optimization problems. He has made significant contributions to mathematical programming, particularly in areas such as cutting planes, integer programming, and polyhedral combinatorics. His publication record demonstrates consistent contributions to the field of optimization over the past two decades, with a focus on theoretical foundations of optimization algorithms and practical implementations. His work spans pure optimization theory, computational methods, and applications in areas like vehicle routing. The progression of his research shows increasing sophistication in handling multi-dimensional optimization problems and developing numerically stable algorithms. At Bocconi University, Dr. Poirrier teaches Software Engineering (course 20875) and has previously taught courses in computer science. His teaching reflects his research expertise, covering topics from low-level computing concepts to software engineering practices.

• Operations Research
• Mathematical Programming
• Management Science
• +2 more

Edoardo Fadda is a Fixed-term tenure-track Assistant Professor at the Department of Mathematical Sciences (DISMA), Politecnico di Torino . He serves as a member of the College of Mathematical Engineering and College of Electronic, Telecommunications and Physics Engineering . Specializes in Operations Research and Mathematical Programming Active in stochastic optimization , reinforcement learning , and control applications Teaching roles include Optimization Methods for Control Applications and Stochastic Programming courses His research spans supply chain optimization , logistics , and AI-integrated decision systems , focusing on uncertainty modeling and multi-stage stochastic programming. He leads the Development of Decision Support Systems and the SUPERSONIC project for ecological logistics, alongside commercial consulting for RIDIX SPA through Fondimpresa contracts. Notable collaborations include Paolo Brandimarte and Francesca Maggioni . Edoardo supervises PhD candidates Alessia De Crescenzo (39th cycle) and Lorenzo Mazza (40th cycle). His publications emphasize stochastic customer behavior , perishable product policies , and kernel-based system identification , with applications in aerospace, smart cities, and industrial manufacturing.

• Operations Research
• Optimization
• Decision Making
• +3 more

Roberto Bargetto is a Research Fellow and part-time lecturer at the Department of Management and Production Engineering (DIGEP) at Politecnico di Torino. His work focuses on optimization algorithms and decision-making systems, with applications in logistics, healthcare scheduling, and computational operations research. He has collaborated extensively on advanced algorithmic solutions for complex problems. Teaching roles (2021-2025): Course collaborator for Decision Making and AI, Quantitative Methods, and Operations Research in Engineering and Management programs. Research interests: Exact algorithms, bin packing, operating room scheduling, and time-dependent cost modeling. Email: roberto.bargetto@polito.it Recent publications highlight his expertise in Integer Programming (2025), branch-and-price-and-cut methods (2023), and iterative algorithms for transportation problems (2024). His work bridges theoretical optimization techniques with practical applications in production engineering and healthcare logistics. Collaborations include Federico Della Croce, Rosario Scatamacchia, Maria Elena Bruni, Guido Perboli, Thierry Garaix, and Xiaolan Xie. Research outputs are available via Porto@Iris.

• Operations Research
• Combinatorial Optimization
• Exact Algorithms
• +4 more

Rosario Scatamacchia serves as an Associate Professor in the Department of Management and Production Engineering (DIGEP) at the Polytechnic University of Turin, where he is also a member of the Interdepartmental Center Ec-L - Energy Center Lab. His academic profile includes teaching courses such as Operations Research and Graphs and Combinatorial Optimization across undergraduate, Master's, and PhD programs in Management Engineering, Data Science, and related fields. Contact details include email rosario.scatamacchia@polito.it and phone +39 0110907261. His research centers on Operations Research with core expertise in: Combinatorial Optimization and Exact Algorithms Game Theory and Algorithmic Game Theory Discrete Mathematics applications Knapsack and NP-hard problem solving Work spans industrial and societal contexts including transportation logistics, network security, and environmental management systems. Recent publications (2021-2025) reveal consistent innovation in exact solution methods for combinatorial problems: Transportation and baggage handling optimization Critical infrastructure network analysis Game-theoretic equilibrium computation Wildfire prevention scheduling under constraints This body of work demonstrates strong interdisciplinary collaboration bridging theoretical computer science and practical engineering applications. No scientific awards were documented in the source materials. While teaching responsibilities are extensively detailed, the provided information does not specify graduate student advising relationships or research grant acquisitions. Professor Scatamacchia maintains active involvement in the Interdepartmental Center Ec-L - Energy Center Lab, contributing optimization expertise to energy systems research initiatives at the Polytechnic University of Turin.

• Operations Research
• Optimization
• Mathematical Programming
• +5 more

Marianna De Santis is an Associate Professor in the Department of Information Engineering (Dipartimento di Ingegneria dell’Informazione) at the University of Florence, Italy. She previously held positions at Sapienza University of Rome and other institutions. Her research focuses on optimization, particularly in multiobjective programming, mixed-integer programming, and algorithm design. She has authored numerous articles in top journals and developed software tools like BBMOQIP and MOMIX for solving complex optimization problems. Education : PhD in Operations Research, Sapienza University of Rome (2012) MSc in Applied Mathematics (2007), BSc in Mathematics (2005) Research Interests : Dr. De Santis specializes in optimization theory and applications, including multiobjective optimization, integer programming, and algorithm design. Her work bridges theoretical advancements with practical implementations, addressing challenges in machine learning, bioinformatics, and operations research. Key areas include semidefinite programming, robust optimization, and exact methods for complex combinatorial problems. Articles Trends : Her recent work emphasizes multiobjective optimization, with contributions to hyperparameter optimization, robust combinatorial methods, and sustainable modeling. Publications span journals like Journal of Global Optimization and Mathematical Programming , reflecting her expertise in algorithmic innovation and mathematical rigor. Grants & Teaching : She leads projects on augmented Lagrangian methods and multiobjective integer optimization. Teaching includes courses on operations research, optimization, and data science at the undergraduate and graduate levels. She has also organized international workshops and served on conference committees. Labs/Teams : Her research group develops optimization software (e.g., BBMOQIP) and collaborates internationally on projects involving algorithm design and real-world applications.

Maurizio BocciaView profile

Associate Professor

• Operations Research
• Optimization
• Logistics
• +5 more

Maurizio Boccia is an Associate Professor at the University of Naples Federico II, affiliated with the Department of Electrical Engineering and Information Technologies. His research focuses on optimization methodologies and their applications in logistics, transportation systems, and healthcare management. He holds a Ph.D. in Operations Research and has contributed extensively to the development of exact and heuristic algorithms for complex scheduling and routing problems. Key research interests include combinatorial optimization, vehicle routing problems (e.g., TSP variants with drones), automated guided vehicle (AGV) scheduling, and optimization in healthcare settings. He has also explored educational strategies, such as the OPS4Math project, which integrates optimization techniques into mathematics education. His work frequently involves mixed-integer linear programming (MILP), branch-and-cut algorithms, and matheuristics. Notable applications include railway dispatching for the Union Pacific Railroad, operating room planning in hospitals, and logistics network design. He has collaborated on real-world projects, such as improving exam scheduling in Norway and optimizing postal collection routes in rural areas. Boccia’s publications span over two decades, with contributions to both theoretical advancements (e.g., lifted cover inequalities, Fenchel cuts) and practical implementations (e.g., web cache location models, traffic sensor placement). His research often bridges theoretical optimization frameworks with real-world operational challenges.

• Operations Research
• Decision Support Systems
• Optimization Algorithms
• +5 more

Daniele Pretolani is an Associate Professor at the Department of Engineering Sciences and Methods, University of Modena and Reggio Emilia. He specializes in Operations Research (MATH-06/A) with a focus on decision support systems, multi-objective optimization, and directed hypergraph algorithms. Teaches Methods and Algorithms for Optimization in Digital and Creative Industry (Management Engineering) Teaches Models and Methods for Decision Support (Management Engineering) His research explores: Stochastic time-dependent network routing Multi-criteria decision analysis for supplier selection Hypergraph reductions for satisfiability problems Visual decision support tools for composite indexes Recent work includes developing a decision support system for global service providers (2024) that improved supplier selection by 25% over company practices, and foundational contributions to the SDEWES sustainability index (2018-2020). No specific awards or student advising details were mentioned in the provided texts.

• Operations Research
• Optimization
• Sustainable Manufacturing
• +3 more

Giulia Caselli is a Research Fellow at the University of Modena and Reggio Emilia , affiliated with the Department of Engineering Sciences and Methods. She also holds the role of Subject Leader in the Department of Economics 'Marco Biagi'. Academic Rank : Research Fellow Primary Department : Engineering Sciences and Methods Secondary Role : Subject Leader in Economics 'Marco Biagi' Her research focuses on Operations Research , Optimization , and Sustainable Manufacturing . Key subfields include Parallel Machine Scheduling , CO2 Emissions Minimization , Demand Forecasting , Workforce Allocation , and Healthcare Facility Design . She applies Mixed Integer Linear Programming and Constraint Programming to real-world problems in manufacturing, waste management, and healthcare. Recent publications highlight her work on contiguity constraints in scheduling, CO2 emissions optimization in waste transfer facilities, and machine learning applications to demand forecasting in the food industry. Her methodologies emphasize practical implementations, such as solving resource allocation in hydraulic component testing and hospital waiting room layouts.

Claudio SterleView profile

Associate Professor

• Operations Research
• Logistics Optimization
• Operations Management
• +6 more

Claudio Sterle is an Associate Professor in Operations Research at the University of Naples Federico II, affiliated with the Department of Electrical Engineering and Information Technology (DIETI-UNINA). He also maintains an affiliation with the IASI-CNR Institute for Systems Analysis and Computer Science. His work focuses on optimization methodologies applied to logistics, transportation systems, healthcare management, and manufacturing processes. Research interests include: Combinatorial optimization and integer programming Logistics network design involving drones and multi-agent systems Healthcare operational efficiency (e.g., operating room scheduling) Transportation systems optimization (modal shift incentives, freight distribution) Algorithm development for cutting problems and facility location Recent work emphasizes practical applications like optimizing emergency room operations in Naples hospitals and developing drone-truck collaboration logistics models. His contributions to mathematical programming formulations for complex routing and coverage problems have been widely applied in both academic and industrial contexts. He leads the Optimization and Problem Solving Laboratory, focusing on bridging theoretical optimization research with real-world problem-solving. Teaching efforts include developing problem-based learning strategies for mathematics education through the OPS4Math project.

Adriano MasoneView profile

Lecturer

• Operations Research
• Logistics Optimization
• Supply Chain Management
• +4 more

Adriano Masone is a Lecturer in Operations Research at the University of Naples Federico II's Department of Electrical Engineering and Information Technology (DIETI-UNINA). His research focuses on optimization problems in logistics, healthcare operations, and smart infrastructure systems. He has developed innovative formulations and algorithms for drone routing, vehicle scheduling, and resource allocation in healthcare settings. His work integrates mathematical modeling (e.g., integer linear programming) with real-world applications like blood supply chain reorganization and operating room management. Notable research contributions include: Drone-team logistics for last-mile delivery Emergency room scheduling optimization Smart grid infrastructure optimization using ILP Feature-based approaches for customer classification in routing problems His articles frequently address combinatorial optimization challenges, with a strong emphasis on heuristic and exact algorithm development. Masone also engages in educational initiatives like the OPS4Math project, promoting problem-solving methodologies in mathematics education. He maintains a dedicated research laboratory focused on optimization and problem-solving applications, publishing extensively on topics spanning transportation, healthcare, and industrial engineering.

• Control Systems
• Game Theory
• Robotics
• +3 more

Filippo Fabiani is an Assistant Professor at the IMT School. His research focuses on control systems, game theory, and optimization, with applications to robotics, multi-agent systems, and nonlinear dynamics. He explores topics such as Nash equilibrium seeking in strategic environments, fault-tolerant control, and neural network-based system identification. His work combines theoretical advancements in distributed algorithms with practical implementations in aerospace and robotic systems. Notable areas include spacecraft proximity guidance, resilient control for nonlinear systems, and adaptive strategies in competitive multi-agent scenarios. He also investigates belief-sharing mechanisms and robust stabilization under uncertainty. Publications highlight contributions to generalized Nash games, distributed equilibrium-seeking algorithms, and model predictive control. Research spans both foundational theory and applied engineering solutions, emphasizing the interplay between strategic decision-making and control system design.