جست‌وجوی استاد و پژوهشگر

• Algorithms
• Formal Verification
• Hardware Model Checking
• +۴ مورد دیگر

Paolo Pasini is a Fixed-term Assistant Professor at the Department of Electronics and Telecommunications (DET) within Politecnico di Torino. His academic roles span teaching and research, with a focus on algorithms, formal verification, and hardware optimization. Scientific Branch: IINF-01/A - Electronics (Area 0009 - Industrial and Information Engineering) ERC Sectors: Algorithms, Software Engineering, Theoretical Computer Science, Web Systems Research interests center on hardware model-checking algorithms, portfolio-based verification engines, pre-simplification steps, circuit manipulation, and interpolation-based techniques. His recent publications highlight applications in FPGA optimization, edge computing, and machine learning classification. 2025: Low-Power Subgraph Isomorphism at the Edge Using FPGAs 2025: NN2FPGA: Optimizing CNN Inference on FPGAs 2024: Bounded Model Checking with Interpolation Teaching roles include: PhD: Data Structures in Python (2022/23) Master’s: Edge Computing Systems for AI and ML (2023/24-2025/26), Modeling and Optimization of Embedded Systems (2023/24-2024/25) Bachelor’s: Digital Electronic Design (2024/25-2025/26), Algorithms and Data Structures (2019/20-2022/23)

• Combinatorial Optimization
• Meta-heuristics
• Mixed Integer Programming
• +۷ مورد دیگر

Luigi De Giovanni is an Associate Professor of Operations Research at the Department of Mathematics, University of Padua, where he has been faculty since 2007 (promoted to Associate Professor in 2018). He holds the Italian academic qualification as Full Professor since 2020. His research focuses on Combinatorial Optimization, Meta-heuristics, Mixed Integer Programming, and their applications in Transportation and Logistics, Air traffic and Airport Optimization, Telecommunication Network Design, and Production Scheduling. His work bridges theoretical optimization methods with practical industrial applications across various sectors including transportation, manufacturing, and telecommunications. Professor De Giovanni has led and participated in several significant research projects including: European Research Project 'OptiFrame - An Optimization Framework for Trajectory Based Operations' (H2020-SESAR-2015-1, 2016-2018) PRIN Project 'Nonlinear and Combinatorial Aspects of Complex Networks' (2017-2020) European Research Project 'AAS - Integrated Airport Apron Safety Fleet Management' (2008-2011) European Research Project 'SCOOP - Sheet Cutting and Process Optimization for Furniture Enterprises' (2006-2008) His extensive publication record spans from 2002 to 2024, with numerous articles in high-impact journals such as Transportation Science, IEEE Access, and European Journal of Operational Research. Recent publications show a strong emphasis on data-driven approaches to air traffic management, vehicle routing and logistics optimization, and graph theory applications, demonstrating continued research productivity and relevance. Professor De Giovanni teaches courses in Operations Research, Methods and Models for Combinatorial Optimization, and Stochastic Optimization at the University of Padua. His office hours are on Thursdays from 10:30 am to 12:30 pm by appointment.

Adam Teodor Polakمشاهده پروفایل

استادیار

• Algorithms
• Fine-Grained Complexity
• Learning-Augmented Algorithms
• +۳ مورد دیگر

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 Poirrierمشاهده پروفایل

استاد مدعو

• Discrete Optimization
• Computational Optimization
• Mathematical Programming
• +۳ مورد دیگر

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
• +۲ مورد دیگر

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
• +۳ مورد دیگر

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.

• Algorithm design and analysis
• Combinatorial optimization
• Exact algorithms
• +۶ مورد دیگر

Fabio Guido Mario Salassa serves as an Associate Professor in the Department of Management and Production Engineering (DIGEP) at the Polytechnic University of Turin. He is a member of the Interdepartmental Center Ec-L - Energy Center Lab and actively participates in the College of Management and Production Engineering as well as the College of Computer, Film, and Mechatronics Engineering as an invited member. His research focuses on algorithm design, combinatorial optimization, exact algorithms, metaheuristics, and scheduling problems. His work bridges theoretical computer science with industrial applications, particularly in operations research and mathematical optimization. He specializes in developing optimization models for real-world industrial challenges including production scheduling, transportation logistics, and resource allocation. His recent publications demonstrate a strong focus on scheduling theory with applications to manufacturing systems, parallel machine environments, and workforce management. The research shows consistent contributions to solving complex optimization problems through innovative algorithmic approaches and mathematical formulations. Professor Salassa has supervised PhD student Elena Rener, whose thesis focused on Single Machine Rescheduling for New Orders. He has secured multiple commercial research contracts with companies including Protea S.r.l. and Sandeza S.r.l., focusing on optimization algorithms for waste calculation, production scheduling, and transportation problems. He teaches Operations Research and Optimization for Problem Solving courses across multiple academic programs including Management Engineering and Computer Science Engineering. His teaching spans from Bachelor to PhD levels, with recent courses scheduled through the 2025/2026 academic year.

• Operations Research
• Combinatorial Optimization
• Exact Algorithms
• +۴ مورد دیگر

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.

Paolo Dettiمشاهده پروفایل

استاد

• Operations Research
• Combinatorial Optimization
• Scheduling
• +۷ مورد دیگر

Paolo Detti is a Full Professor of Operations Research at the Department of Information Engineering and Mathematical Sciences at the University of Siena. He currently teaches Operations Research and Production and Supply Chain Management - Logistics courses for both Bachelor's and Master's degree programs in Engineering Management. Professor Detti chairs the Management Engineering Degree Committee and maintains an active research program focused on complex optimization problems across multiple domains. Professor Detti's research spans several key areas of operations research with a strong emphasis on combinatorial optimization and scheduling. His work addresses real-world challenges in resource allocation for mobile telecommunications systems, electrical load scheduling for energy consumption minimization, healthcare planning and transportation problems, and sustainable crop planning in agriculture. His approach combines theoretical mathematical modeling with practical applications, often developing novel optimization algorithms and metaheuristics to solve complex problems. Analysis of Professor Detti's recent publications reveals a clear research trajectory focused on applying operations research methodologies to sustainability challenges. His work in agricultural optimization has grown significantly, with multiple 2025 publications on sustainable crop planning and rotation. The healthcare logistics domain remains consistently strong in his portfolio, particularly in biological sample transportation. Parallel machine scheduling with unreliable elements forms another persistent research thread, with multiple publications across different years addressing variations of this fundamental problem. Professor Detti maintains active teaching responsibilities across multiple academic levels. He currently teaches Operations Research to second-year Bachelor's students in Management Engineering and Production and Supply Chain Management - Logistics to first-year Master's students in Engineering Management for the 2025/2026 academic year. As chair of the Management Engineering Degree Committee, he plays a significant administrative role in academic governance. His educational background includes a PhD in Operations Research from Sapienza University of Rome, establishing his strong theoretical foundation in the field.

• Operations Research
• Optimization
• Mathematical Programming
• +۵ مورد دیگر

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 Bocciaمشاهده پروفایل

دانشیار

• Operations Research
• Optimization
• Logistics
• +۵ مورد دیگر

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.

• Operational Research
• Optimization
• Combinatorial Optimization
• +۳ مورد دیگر

Roberto Montemanni is a Full Professor in the Department of Engineering Sciences and Methods at the University of Modena and Reggio Emilia . He is affiliated with the Operations Research Group and specializes in the MATH-06/A Operational Research disciplinary sector. His role involves teaching and research, with office hours available by appointment via email. He focuses on advancing optimization methodologies for complex logistical, transportation, and healthcare challenges. His research interests include combinatorial optimization , algorithm design , and constraint programming . Key areas of exploration involve conflict-constrained problems (e.g., assignment, knapsack, and spanning tree), probabilistic routing scenarios, and drone-assisted delivery systems. He also investigates real-world applications in home healthcare logistics, warehouse management, and supply chain optimization, often blending heuristic methods with exact algorithms. Recent publications emphasize trends in exact algorithm development for hazardous routing, drone scheduling in heterogeneous vehicle routing, and model-based approaches for time-bomb knapsack and orienteering problems. These works highlight interdisciplinary solutions for industries and healthcare systems. While no scientific awards are listed, his contributions to optimization theory and practice are substantial. His advising and grant activities likely align with his research group’s focus on operational challenges, though specific student names or grant details are not provided. He collaborates actively through the Operations Research Group , addressing issues like network-based data interpretation and intelligent manufacturing systems.

• Operations Research
• Decision Support Systems
• Optimization Algorithms
• +۵ مورد دیگر

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
• +۳ مورد دیگر

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 Sterleمشاهده پروفایل

دانشیار

• Operations Research
• Logistics Optimization
• Operations Management
• +۶ مورد دیگر

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.