Find Academic Supervisors

• Building automation and control systems
• Building energy performance modeling
• Data-driven energy modeling
• +7 more

Marco Savino Piscitelli is a Fixed-Term Researcher at the Polytechnic University of Turin within the Department of Energy (DENERG) and member of the Interdepartmental Center SmartData@PoliTO. He actively contributes to the BAEDA Lab (Building Automation and Energy Data Analytics) since 2021. His academic activities span two schools: College of Architecture and Design (as member), and College of Electrical and Energy Engineering (as invited member). Research Interests focus on: Adaptive control strategies for smart buildings Data-driven energy management systems Knowledge graphs and LLMs for building interoperability Fault detection in HVAC and district heating systems Energy benchmarking frameworks Grid-interactive efficient buildings Commercial research projects with generative AI applications Recent Publications (2023-2025) demonstrate expertise in: AI-enhanced energy planning Brick-compliant semantic models Deep learning for power demand forecasting Multi-zone HVAC optimization Experimental building diagnostics Collective self-consumption strategies Teaching Roles include: Lecturer for Energy Management and Automation in Buildings (2023-2025) Collaborator for Energy Transition and Low-Carbon Architecture (2021-2025) Lecturer for Models and Scenarios for Energy Planning (2024) Titolare (lead instructor) for Building Physics and Air Conditioning (2024) Research Projects : 2024-2025 : Scientific Manager for "Data-Driven Performance Analysis through Generative AI" 2023-2024 : Scientific Head for "Advanced data-driven smart reporting systems" Labs & Teams : BAEDA Lab - Building Automation and Energy Data Analytics SmartData@PoliTO - Big Data and Data Science Laboratory Collaboration with CityLearn v2 development team

Alessandro AgnetisView profile

Professor

• Combinatorial Optimization
• Scheduling Algorithms
• Operations Research
• +3 more

Alessandro Agnetis is a Full Professor at the Department of Information Engineering and Mathematical Sciences, University of Siena, with expertise in combinatorial optimization and scheduling theory. His research spans operations research, multi-agent systems, and lean management applications, with recent publications focusing on adversarial bilevel scheduling, drone emergency logistics, and fairness-utility trade-offs in two-agent systems. Current Courses: Optimization Methods, Combinatorial Optimization, Production Planning (Master's in Engineering Management) Contact: alessandro.agnetis@unisi.it Research Trends: His work addresses complex scheduling problems across manufacturing, healthcare, and logistics, particularly emphasizing: Multi-agent coordination and Nash equilibrium models Parallel machine scheduling with unreliable jobs Emergency delivery optimization using drones Time-critical testing and cross-docking systems Lean management integration in healthcare operations

Giulia De PasqualeView profile

Assistant Professor

• Control Systems
• Social Network Analysis
• Optimization Algorithms
• +3 more

Giulia De Pasquale is an Assistant Professor at the Department of Electrical Engineering, Eindhoven University of Technology, specializing in Control Systems. Her research focuses on social network interventions, optimization algorithms, and fairness in AI systems. She leads the Control Systems Group, addressing challenges in distributed control, hypergraph reconstruction, and ethical algorithm design. Her work integrates machine learning, network science, and control theory to develop fair and safe recommendation systems. Recent projects include hypergradient-based optimization for social network interventions and optimal transport approaches to fairness in influence maximization. She actively collaborates with institutions like Santa Fe Institute and UC San Diego. Giulia organizes interdisciplinary workshops on algorithmic fairness and has presented at NeurIPS, CDC, and NetSci. She advises PhD students like Alessandro Casu and hosts visiting scholars such as Camilla Quaresmini. Her research has been published in prestigious venues including Nature Communications and ICML.

• Cybersecurity
• Software Security
• Formal Methods
• +5 more

Mila Dalla Preda is an Associate Professor at the University of Verona's Department of Computer Science, affiliated with the College of Science and Engineering. She holds multiple institutional roles including membership in the Faculty Board of PhD in Computer Science, Computer Science Teaching Committee, and Commissione AQ Ricerca. Her work focuses on software security, code protection, and formal methods. Research interests include static program analysis, formal software security, and semantic-based obfuscation techniques. She leads projects like 'Securing sOFTWARE Platforms' (2024) and 'BinTrace: Binary Similarity Analysis' (2020). Key contributions involve malware detection, program similarity analysis, and blockchain security through tools like Ethersolve. Active in teaching, she instructs courses on Compilers, Software Security, and Data Privacy across undergraduate and graduate programs. Her lab affiliations include the SPY Laboratory (Formal Methods) and collaborates with spin-off companies like 3Dflow s.r.l. and eVS embedded Vision Systems s.r.l.

• Operations Research
• Combinatorial Optimization
• Healthcare Logistics
• +3 more

Paola Cappanera is an Associate Professor of Operations Research at the Department of Information Engineering (Università di Firenze), affiliated with the School of Engineering. She is a member of the IBIS Lab. Her expertise spans combinatorial optimization, healthcare logistics, telecommunication networks, and scheduling problems. She teaches courses such as Fondamenti di Ricerca Operativa , Combinatorial Optimization , and Ottimizzazione su Reti di Flusso at both undergraduate and graduate levels. Her research focuses on optimizing healthcare delivery systems, including home care services, surgical scheduling, and resource allocation. She also addresses challenges in telecommunication networks, such as latency-aware scheduling and routing. Recent work emphasizes robustness in home care planning, equitable resource distribution, and mitigating risks in hazardous material transportation. Her articles highlight advancements in decomposition methods for scheduling, genetic algorithms for network functions, and integration of healthcare service models. Key contributions include models for emergency department physician rostering and optimizing tele-assistance systems.

Omiros PapaspiliopoulosView profile

Professor

• Computational Statistics
• Machine Learning
• Probability
• +5 more

Omiros Papaspiliopoulos is a Full Professor at Bocconi University’s Department of Decision Sciences. He joined Bocconi in 2021, previously serving as an ICREA Research Professor at Universitat Pompeu Fabra in Barcelona. His academic career includes roles at Warwick, Oxford, Lancaster, Berlin, Osaka, Paris, Madrid, and Lima. He has been awarded the Royal Statistical Society’s Guy Medal (2010) and the DeGroot Prize for his influential work with Nicolas Chopin. His research focuses on computational statistics, spanning Bayesian inference, machine learning, probability, and applied mathematics. Notably, he founded Europe’s first Master in Data Science at the Barcelona Graduate School of Economics (2013) and directed the Data Science Center until 2021. Since 2022, he has been Director of Bocconi’s Bachelor of Science in Economics, Management, and Computer Science (BEMACS). Papaspiliopoulos is co-Editor of Biometrika (top-4 in Statistics) and Associate Editor of the Journal of Uncertainty Quantification . He has delivered keynote talks at institutions like Chicago Booth, Duke, and LSE, emphasizing the societal impact of data science. His teaching spans courses on data science, statistics, machine learning, and quantitative methods in social sciences. Education & Academic Leadership PhD in Statistics (Implied by career trajectory) Founded Bocconi’s BEMACS program (2022) Directed the Master in Data Science (2013–2021) Executive course design for SDA Bocconi and Barcelona School of Economics Research Interests Computational Statistics & Bayesian Methods Machine Learning & Applied Mathematics Data Science in Social Sciences Hidden Markov Models & State-Space Systems High-Dimensional Inference & Scalable Algorithms Recent Work Trends His publications emphasize scalable Bayesian computation, treatment effect inference, and applications in social sciences. Recent topics include confounder importance learning, particle filtering, and computational efficiency in hierarchical models. Collaborations bridge theory and practice, addressing challenges in policy, finance, and public administration. Awards & Recognition 2010: Royal Statistical Society’s Guy Medal DeGroot Prize for Nonparametric Hidden Markov Models Onassis Foundation Scholar Grants & Outreach Directed the Barcelona Data Science Center (2016–2021) Outreach activities: Talks for high-school students, policymakers, and the European Commission Editorial roles in top journals: Biometrika , Journal of Uncertainty Quantification Labs & Teams Current affiliation with Bocconi’s Department of Decision Sciences and involvement in interdisciplinary data science initiatives.

Caterina SgangaView profile

Professor

• Intellectual Property Law
• European Copyright Law
• Digital Exhaustion
• +5 more

Caterina Sganga is a Full Professor of Comparative Private Law at Scuola Superiore Sant'Anna (since 2024), previously serving as Associate Professor (2018–2024). Her expertise lies in comparative intellectual property law, particularly European copyright law and its intersections with new technologies like AI. She leads major EU-funded projects, including reCreating Europe (2020–2022), OpenMusE , and REBOOT , focusing on digital copyright reform and cultural diversity. She chairs the European Policy for Intellectual Property Association (EPIP) and serves as Italian Representative in the European Copyright Society (ECS) . Her research spans copyright exceptions, data governance, and the balance between IP rights and fundamental rights. Key publications include Propertizing European Copyright (2018) and edited volumes on NFTs, Creativity and the Law (2024). She holds a PhD (Scuola Superiore Sant'Anna, 2011), LL.M. (Yale, 2009), and degrees from the University of Pisa (2004–2006). Awards include the H2020 Success Story recognition for reCreating Europe . Current projects include mapping legal frameworks for European music ecosystems ( OpenMusE ) and film competitiveness ( REBOOT ). She advises on EU policy reforms and frequently collaborates with institutions like KU Leuven and McGill University. Professional roles include: President of EPIP (since 2022) WP Leader in Horizon Europe projects ( OpenMusE , REBOOT ) Principal Investigator, PRIN Copy-IT (2023–2024) Her work emphasizes interdisciplinary approaches, combining legal, economic, and cultural perspectives to address modern IP challenges in digital and creative industries.

• Solvency II
• Insurance Contract Valuation
• Monte Carlo Simulation
• +7 more

Anna Maria Gambaro is an Associate Professor at the Department of Economics and Business Studies of Università degli Studi del Piemonte Orientale "Amedeo Avogadro". Her research focuses on actuarial science, financial engineering, and stochastic modeling with applications to insurance regulation (Solvency II), healthcare operations, and commodity markets. She has contributed to developing methodologies for risk margin calculation, capacity expansion under uncertainty, and Monte Carlo simulation techniques. Her recent projects include measuring climate-transition risks (funded by MUR) and studying insurance capital requirements (collaboration with Prof. Fusai). She has published extensively in journals like European Actuarial Journal, Production and Operations Management, and The Journal of Derivatives. Expertise: Solvency II compliance, stochastic optimization, Monte Carlo methods, pandemic planning Notable Works: ICU capacity expansion under uncertainty (2023), Risk margin capital-on-capital cost (2025), Pricing on Trees using new risk-free rates (2024) Awards: No specific prizes mentioned, but her work aligns with UN Sustainable Development Goals related to resilient infrastructure and financial inclusion. Grants/Projects: Led or co-led 2 major research projects (2023-2025) totaling €1.2M in funding. Her work on climate-transition risk integrates supply chain and risk management frameworks.

• Continual Learning
• Deep Learning
• Distributed Learning
• +3 more

Vincenzo Lomonaco is a Researcher at the University of Pisa's Department of Computer Science, specializing in Continual Learning. He leads the Pervasive AI Lab and holds roles such as Co-Founding President of ContinualAI, a non-profit advancing AI research. His work focuses on deep learning, distributed systems, and AI sustainability, with key contributions including the Avalanche library (winner of the W&B Best Library Award) and foundational research in Continual Learning. Education: PhD in AI from the University of Bologna (2019), recognized as one of Italy's top-5 AI dissertations. Postdoctoral research and visiting roles at institutions like Numenta, Purdue University, and ENSTA ParisTech. Research Interests: Continual Learning dynamics, practical applications, and AI sustainability. Active in industrial collaborations (e.g., Meta, Intel), European projects, and initiatives like FAIR (Future Artificial Intelligence Research). Notable Achievements: Organized the 1st Continual Learning workshop at CVPR 2020, authored an open-access Continual Learning course (430+ students), and co-founded ContinualIST, a University of Pisa spin-off.

• Anesthesiology
• Intensive Care Medicine
• Sepsis Management
• +4 more

Prof. Maurizio Cecconi is a Full Professor of Anesthesia and Intensive Care at Humanitas University, leading the MEDTEC School and directing the Department of Anesthesia and Intensive Care at Humanitas Research Hospital. He previously served as Past President of the European Society of Intensive Care Medicine (ESICM) during the pandemic, receiving the Gastein Health Forum European Health Leadership Award (2021). His academic roles include Deputy Scientific Director for Clinical Research and residency program leadership. Education highlights include a Medical Degree from the University of Udine (2002), a PhD/MD from the University of London (2006), and participation in Harvard Medical School’s Global Clinical Scholar Program (2015). Certifications include FRCA (UK Royal College of Anaesthetists) and FFICM (Faculty of Intensive Care Medicine). Research focuses on perioperative optimization, sepsis, shock physiology, and AI applications in critical care. Key contributions include global guidelines for sepsis (Surviving Sepsis Campaign) and WHO pandemic protocols. His work is highly cited (h-index 83 as of 2023). Awards include knighthood in the Order of Merit of Italy (2020), Silver Griffin Career Award (2018), and NHS Clinical Excellence Award (2017). Notable achievements include designing the EU-funded C19_SPACE training program for 20,000 healthcare workers and leading the UNITE-COVID study on ICU strain impacts. Teaching spans anesthesia and critical care across Humanitas’ medical, nursing, and residency programs. He has authored over 490 peer-reviewed articles, edited books, and contributed to international conferences (~400 invitations).

• Work and Organizational Psychology
• Human Factors
• AI and Robotics in Human Systems
• +4 more

Luca Pietrantoni is a Full Professor of Work and Organizational Psychology at the Department of Psychology 'Renzo Canestrari', University of Bologna. He coordinates the 'Human Factors, Risk and Safety' research group and actively participates in EU Horizon projects like SESTOSENSO and TUPLES, focusing on AI and robotics in human systems. His research spans mental health promotion in workplaces, cognitive ergonomics, and sustainable commuting. Education: PhD in Health Psychology (University of Florence, 2000) Postdoctoral fellowship in Social Psychology (University of Parma) Psychology Degree (University of Padua, 1995 with top honors) Research Interests: Human factors in AI/robotics integration Workplace mental health interventions Climate change adaptation strategies Cognitive ergonomics in manufacturing Grants & Projects: Principal Investigator in Horizon Europe projects (SESTOSENSO, TUPLES) Coordinator of H-WORK (mental health in SMEs/public workplaces) EU-funded studies on exoskeletons, coastal safety, and cyclist safety Labs/Teams: Human Factors, Risk and Safety research group.

• Data Security
• Privacy Protection
• Blockchain Security
• +2 more

Elena Ferrari is Professor of Computer Science at the University of Insubria and research leader at STRICT SociaLab, recognized for significant contributions to data security and privacy. She received the 2021 SIGSAC Outstanding Contributions Award for her pioneering work in security technologies. Her research develops privacy-preserving frameworks for emerging technologies including blockchain systems, edge computing environments, human digital twins, and IoT networks. Current projects address malware detection, metadata leakage prevention, decentralized learning security, and privacy-aware access control. Publications demonstrate consistent innovation in security mechanisms for complex systems. Recent work features blockchain-based malware containment, context-aware privacy enforcement, and edge computing security solutions. Ferrari has chaired major security conferences and contributes to advancing privacy-preserving computation. No student advising details or laboratory affiliations are documented in available sources.

Alessandro FarinelliView profile

Professor

• Artificial Intelligence
• Robotics
• Multi-Agent Systems
• +4 more

Alessandro Farinelli is a Full Professor at the University of Verona's Department of Computer Science. His research focuses on Artificial Intelligence, Robotics, and Cyber-Physical Systems, with a strong emphasis on multi-agent coordination, decentralized optimization, and reinforcement learning. He has led numerous national and international projects in AI and robotics, contributing to high-impact journals and conferences like AAMAS, IJCAI, and IROS. His work bridges theoretical advancements with practical applications in logistics, environmental monitoring, and disaster response. Farinelli's teaching spans Foundations of Artificial Intelligence, Programming Lab II, and specialized courses in Robotics and Autonomous Systems. He has been a key contributor to benchmarking frameworks like RMASBench for urban search and rescue scenarios. His research integrates formal verification methods with reinforcement learning to ensure safety in autonomous systems, particularly in challenging environments like aquatic navigation and medical robotics. His projects include leading the EU-funded INTCATCH for catchment management and collaborating on energy-saving solutions for wastewater systems. Farinelli's contributions also extend to anomaly detection in industrial robots and safe policy synthesis using inductive logic programming.

Marek EliasView profile

Assistant Professor

• Algorithms
• Online Algorithms
• Differential Privacy
• +9 more

Marek Elias is an Assistant Professor at Bocconi University in Milan, where he is affiliated with the Theory Group . Prior to joining Bocconi, he held postdoctoral positions at CWI (Amsterdam) and EPFL (Lausanne), following a PhD at TU Eindhoven under the supervision of Nikhil Bansal. Earlier, he studied at Charles University in Prague with advisor Jiří Matoušek. His research focuses on algorithms for optimization under uncertainty , bridging online algorithms , differential privacy , and machine learning-augmented systems . Key areas include Learning-Augmented Algorithms Online Metric Algorithms Combinatorial Optimization Privacy-Preserving Mechanisms The trends in his recent publications highlight advancements in online optimization with applications in machine learning and data structures , particularly in problems like the k-server system , Steiner tree approximation , and differentially private clustering . Papers often explore the interplay between algorithmic robustness and predictive modeling to enhance efficiency in uncertain environments. He has contributed to major conferences including ICML, NeurIPS, SODA, and FOCS, with a consistent emphasis on theoretical guarantees and practical applications . While specific awards or grants are not detailed in the provided texts, his work is supported through institutional affiliations and collaborative research networks. Marek actively engages students in research, particularly in Bocconi's Theory Group , encouraging thesis projects on learning-augmented algorithms and prediction-based optimization . His laboratory environment fosters interdisciplinary collaboration between theoretical computer science and machine learning communities.

Giancarlo BigiView profile

Associate Professor

• Operations Research
• Optimization
• Equilibrium Problems
• +7 more

Giancarlo Bigi is an Associate Professor of Operations Research in the Department of Computer Science at the University of Pisa, Italy. He has been a faculty member since 2000, advancing from Assistant Professor to Associate Professor in 2017. He holds a Ph.D. in Mathematics from the University of Pisa and has achieved national habilitations for both full and associate professorship in Operations Research and Mathematical Methods of Economics. His research is centered on optimization and equilibrium problems, with a strong focus on variational inequalities, game theory, multiobjective optimization, and nonlinear programming. He develops theoretical frameworks and algorithmic solutions for complex equilibrium models, including applications in economics and energy markets. The recent publications highlight a consistent trend in developing and analyzing gap functions, descent algorithms, and penalization techniques for equilibrium and hierarchical programming problems. His work bridges theoretical optimization with practical applications, particularly in modeling oligopolistic markets and decentralized energy systems. Associate Professor, Department of Computer Science, University of Pisa (2017–present) Assistant Professor, Department of Computer Science, University of Pisa (2000–2017) Ph.D. in Mathematics, University of Pisa (1997–2003) Bigi has no explicitly listed scientific awards in the provided material. He has not published any acknowledgments of grants, but his sustained research output suggests ongoing funding support. He collaborates extensively with researchers such as Mauro Passacantando, Marco Castellani, and Massimo Pappalardo. He is affiliated with the Operations Research Group within the Department of Computer Science at the University of Pisa, contributing to a collaborative research environment focused on optimization and decision-making models.