Find Academic Supervisors

Sonia PetroneView profile

Professor

• Bayesian Statistics
• Predictive Modeling
• Bayesian Nonparametrics
• +1 more

Dr. Sonia Petrone is a Full Professor of Statistics at Bocconi University's Department of Decision Sciences. She earned her PhD in Statistics from Bocconi University and has held academic positions at the University of Pavia and University of Insubria before joining Bocconi. Her extensive international experience includes research visits across North America, Latin America, Europe, India, and Russia. Her research specializes in Bayesian statistics, with contributions to foundational theory, predictive modeling, Bayesian nonparametrics, and stochastic processes. She currently directs the Bocconi Summer School in Advanced Statistics and Probability and previously led the PhD program in Statistics (2011-2018). Her research portfolio demonstrates consistent focus on Bayesian nonparametric methods, predictive modeling, and applications to complex data structures. Recent work explores urn processes, time series analysis, and network modeling using innovative Bayesian approaches. Awards & Honors: IMS Medallion Lecture Award (2018) ISBA Foundational Lecture Award (2016) Fellow of International Society for Bayesian Analysis Fellow of Institute of Mathematical Statistics Fellow of European Laboratory for Intelligent Systems Fellow of Bocconi Institute of Data Science She has held editorial leadership positions as Editor of Statistical Science (2020-2022) and Bayesian Analysis (2010-2014), and served as President of the International Society for Bayesian Analysis (2014).

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.

Marc MezardView profile

Professor

• Statistical Physics
• Machine Learning
• Information Theory
• +5 more

Marc Mezard is a Professor of Theoretical Physics at Bocconi University, where he leads the newly established Department of Computational Sciences. Previously, he served as Research Director at CNRS in Paris and held roles at Université Paris Sud. He earned his PhD in Physics from École Normale Supérieure in Paris in 1984. His research focuses on statistical physics of disordered systems, with applications to machine learning, information theory, computer science, and biophysics. His work bridges theoretical physics and interdisciplinary fields, including neural networks and deep learning, where he explores the impact of data structure on learning strategies. He teaches undergraduate courses in statistical and quantum physics and a doctoral course on complex systems. Key research themes include emergent phenomena in complex systems, with contributions to spin glass theory, compressed sensing, and algorithmic solutions for random satisfiability problems. His publications span foundational topics in statistical mechanics and modern applications in data science. Marc Mezard has collaborated extensively with institutions and researchers globally, contributing to the theoretical foundations of computational and physical sciences. His academic leadership includes directing École Normale Supérieure from 2012 to 2022, fostering interdisciplinary research initiatives.

Antonela TommaselView profile

Adjunct Professor

• Social Computing
• Recommender Systems
• Machine Learning
• +5 more

Dr. Antonela Tommasel is a Researcher at CONICET and an Adjunct Professor at National University of the Center of the Province of Buenos Aires (UNICEN) , working at the intersection of social computing, machine learning, and misinformation mitigation. Her work combines computational techniques to address challenges in social media analysis, bias detection, and recommender system design. PhD in Computer Sciences (2017), UNICEN Bachelor in Software Engineering (2012), UNICEN Her research focuses on recommender systems with applications to social media trustworthiness , including projects like Faking It! (fake news dataset creation) and OHARS (harm-aware recommendation frameworks). Key themes include misinformation spread analysis , gender bias detection , and machine learning applications for social good. She has led 11+ years of teaching in courses like Advanced Java Programming, Recommender Systems, and Natural Language Processing for AI specializations. Her technical certifications include NVIDIA Deep Learning Institute programs on GPU-accelerated data science and Coursera specializations in machine learning and visualization. Currently based at ISISTAN Research Institute in Tandil, Argentina, she advocates for responsible AI through tools like graphoW (graph-of-words library) and Sen4Smells (technical debt prioritization). Her work emphasizes bridging social media analysis with practical implementation frameworks.

Francesca VocaturoView profile

Associate Professor

• Operations Research
• Logistics
• Optimization
• +4 more

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

• Deep Learning
• Artificial Intelligence
• Machine Learning
• +4 more

Stefano Coniglio is an Associate Professor of Computer Science and Artificial Intelligence at the University of Bergamo (UniBg), where he joined in 2022 after earning his PhD in Information Technology from the Polytechnic University of Milan in 2011 and conducting research abroad in Germany and the United Kingdom for ten years. His research focuses on deep learning models, machine learning using neural networks, algorithm design and analysis, and mathematical optimization. With over 50 scientific publications in international journals and conference proceedings, his work spans multiple domains including energy systems, medical applications, and theoretical computer science. Coniglio has made significant contributions to graph neural networks, as evidenced by his highly cited papers on quaternion-valued Laplacians and directional hypergraph neural networks. His research trends show a strong interdisciplinary approach, with publications bridging computer science with energy systems, cardiology, and mathematical optimization. His work on S-ICD screening demonstrates practical medical applications of deep learning, while his theoretical contributions to graph neural networks have advanced the field of geometric deep learning. Since November 2023, Coniglio has been a member of the UniBg Interdepartmental Working Group on Artificial Intelligence, collaborating on the design of an interdepartmental doctoral program in AI. He serves as the unit leader for the PRIN-PNRR project HEXAGON: Highly specialized EXact Algorithms for Grid Operations at the National level since 2023. Coniglio teaches Computer Science, Artificial Intelligence, and Deep Learning courses across multiple departments at UniBg, including the Department of Economics and the Department of Letters, Philosophy, and Communication. He has collaborated with major organizations including National Grid Plc, UK MetOffice, Airbus, Babcock International, British Telecom, CESI, and CISL, demonstrating strong industry connections and practical application of his research.

Mirco TribastoneView profile

Professor

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

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

Veronica PiccialliView profile

Professor

• Nonlinear Optimization
• Semidefinite Programming
• Game Theory
• +6 more

Veronica Piccialli is a Full Professor at the Department of Computer, Control and Management Engineering "Antonio Ruberti" (DIAG) at Sapienza University of Rome. She teaches Geometry I for Management Engineering and Optimization Methods for Machine Learning for Data Science. Previously, she was Associate Professor at the University of Rome Tor Vergata (2020-2021) and Researcher there from 2008 to 2020. She serves as Associate Editor for INFORMS Journal on Computing (since 2019) and EURO Journal on Computational Optimization (since 2021). Dr. Piccialli earned her degree in Computer Engineering (summa cum laude) and PhD in Operations Research from Sapienza University of Rome in 2000 and 2004 respectively. In 2006, she completed a postdoc at the Combinatorics & Optimization department of the University of Waterloo, Canada. She obtained Italian national scientific qualifications as Associate Professor in 2013 and as Full Professor in 2017. Her research focuses on the intersection of optimization and machine learning, with particular expertise in nonlinear optimization, semidefinite programming, and mixed integer nonlinear programming. She applies these methods to diverse areas including Brain Computer Interfaces, electric consumption disaggregation, and process engineering for membrane systems. Her work demonstrates how advanced optimization techniques can enhance machine learning algorithms and solve complex engineering problems. Her recent publications show a strong trend toward integrating optimization with machine learning, particularly in clustering algorithms, support vector machines, and neural networks. She has developed exact algorithms for semi-supervised learning problems and applied optimization techniques to real-world challenges in logistics, energy systems, and process engineering. Her interdisciplinary approach bridges theoretical advances in optimization with practical applications across multiple domains. Dr. Piccialli has authored or co-authored over 40 articles in prestigious journals including Mathematical Programming, SIAM Journal on Optimization, IEEE Transactions on Neural Networks and Learning Systems, and Computational Optimization and Applications. She has also contributed 3 refereed book chapters to international publications. As an educator, she supervises student research and teaches advanced courses in optimization methods and geometry. Her teaching materials demonstrate a commitment to connecting theoretical concepts with practical applications, particularly in data science and machine learning contexts. Her current research involves collaborations with Université de Lorraine on membrane systems for gas filtration and with RFI (Rete Ferroviaria Italiana) on optimizing last-mile facilities for freight trains, demonstrating the real-world impact of her optimization expertise.

Raffaele CerulliView profile

Professor

• Operations Research
• Combinatorial Optimization
• Graph Theory
• +5 more

Raffaele Cerulli is a Full Professor of Operations Research at the Department of Mathematics of the University of Salerno, Italy, where he also serves as Head of Department. He is a Member of the Scientific Committee of UMI (Unione Matematica Italiana) and Director of the Laboratory "Model and Applications of Mathematical Methods." His office is located at the Fisciano Campus, Building F2, First Floor, Room 026, with reception hours on Tuesdays from 3:00 PM to 5:00 PM and Wednesdays from 3:00 PM to 4:00 PM. Dr. Cerulli's research focuses on Operations Research, Combinatorial Optimization, and Network Theory . His work spans multiple application areas including wireless sensor networks, vehicle routing, spanning tree problems, and graph optimization. He has made significant contributions to problems involving labeled graphs, minimum branch vertices spanning trees, and maximum lifetime problems in sensor networks. His research combines theoretical developments with practical applications, particularly in transportation and network systems. Analysis of his recent publications (2022-2025) reveals continued strong activity in combinatorial optimization, with particular emphasis on flow problems, spanning tree variants, and sensor network optimization. His work demonstrates consistent methodological innovation, frequently employing exact algorithms, metaheuristics, and mathematical programming approaches to solve complex combinatorial problems. Many of his recent papers represent extensions or novel variants of classical optimization problems with practical constraints. Throughout his career, Dr. Cerulli has maintained extensive collaborations, particularly with researchers Carrabs, Gentili, and Raiconi, resulting in numerous joint publications across top-tier operations research journals. His work has contributed significantly to both theoretical developments and practical applications of optimization techniques in network systems.

Enrico Maria MalatestaView profile

Assistant Professor

• Statistical Physics
• Disordered Systems
• Spin Glasses
• +4 more

Enrico Maria Malatesta is an Assistant Professor in the Department of Computing Sciences at Bocconi University. He received his PhD in Physics from the University of Milan in 2018, supervised jointly by Sergio Caracciolo and Giorgio Parisi, following a BSc in Theoretical Physics at Sapienza University of Rome under Giorgio Parisi. His research focuses on the statistical physics of disordered systems, particularly spin glasses, with applications to constrained optimization, machine learning, and high-dimensional statistics. His work explores phase transitions, solution geometry, and capacity in neural networks and related models. His recent publications analyze star-shaped solution spaces in negative perceptrons, atypical solutions in nonconvex networks, and phase transitions in Hopfield models. Earlier works include exact solutions for optimization problems and perturbative expansions in quantum field theory.

Simone FaroView profile

Associate Professor

• Algorithmic solutions for text-processing
• Natural language processing
• Algorithmics in quantum domain
• +12 more

Simone Faro is an Associate Professor at the University of Catania , affiliated with the Department of Mathematics and Computer Science . He has held this position since 2015, after serving as a University Researcher from 2006 to 2015. Teaches Algorithms and Laboratory (Bachelor's L31) and Quantum Computer Programming (Master's LM18) Also teaches Computer Science (Bachelor's L20) and previously held Computational Linguistics (Master's LM49) at the Department of Humanities Research Focus : Algorithmic solutions for text-processing and natural language processing Combinatorial algorithms on graphs and networks Privacy-preserving text processing Bit-parallel automata simulations Quantum domain algorithm design Research Projects : Co-Principal Investigator for STORAGE (2020), University of Catania Responsible for Scientific Degrees Plan (PLS 2019/21) Component in Godscapes project (2020) and COMPACT project (2015) Principal Investigator for multiple string matching and secure text processing projects Editorial Roles : Guest Editor for Algorithms journal (MDPI) special issues Editor for String Processing and Combinatorial Algorithms (Springer Nature) Member of Le Matematiche editorial team Contact: faro@dmi.unict.it | simone.faro@unict.it

• Algorithms
• Optimization
• Mathematical Programming
• +2 more

Federico Della Croce Di Dojola is a Full Professor at the Department of Management and Production Engineering (DIGEP) of Politecnico di Torino. He is also a member of the Interdepartmental Center Ec-L - Energy Center Lab. His academic career spans over two decades with international collaborations including a Visiting Researcher position at Université Paris Dauphine (2004-2005). Research Interests focus on algorithm development and optimization techniques, particularly in combinatorial optimization. His work applies to diverse areas including operations research, production scheduling, and mathematical programming, with connections to sustainable cities and communities (SDG Goal 11). Publications demonstrate expertise in exact algorithms, heuristic methods, and scheduling problems across multiple domains. Key contributions include advancements in transportation optimization, bilevel scheduling, and fuel treatment planning. Scientific Recognition : Member of Editorial Board, European Journal of Operational Research (2016-) Member of Editorial Board, Computers & Operations Research (2016-) Principal investigator in multiple research projects Academic Leadership includes: Director of Department of Control and Computer Science (2012-2015) Doctoral College Member (2003-2025) Course Lecturer at multiple degree levels PhD Supervision includes Quentin Schau (2024-in progress) focusing on Industry 4.0 scheduling problems.

• Algebraic Geometry
• Optimization and Control
• Symbolic Computation
• +3 more

Simone Naldi is a Lecturer (Maître de conférences) in Applied Mathematics at the University of Limoges, France, since 2017. His research focuses on algebraic geometry, optimization, and symbolic computation, with applications to semidefinite programming and linear matrix inequalities. He holds a PhD from CNRS-LAAS in Toulouse and has held postdoctoral positions at the University of Dortmund and the Fields Institute in Toronto. His work includes developing algorithms for solving polynomial systems and creating the SPECTRA library for exact LMI solutions. He has collaborated on projects involving geometric configurations, hyperbolic curves, and infeasibility certificates for optimization problems. Key research areas include semidefinite programming, algebraic certificates for moment problems, and computational tools for polynomial equations. He actively contributes to conferences like Structured Matrix Days and has been supported by institutions like the Simons Foundation. His recent work addresses degenerate systems and geometric configurations of spheres in tetrahedrons, reflecting his interdisciplinary approach combining pure mathematics with algorithmic development.

• Dynamical Systems
• Ergodic Theory
• Stochastic Processes
• +9 more

Marco Lenci is a Full Professor at the Department of Physics and Astronomy 'Augusto Righi' of the University of Bologna. His academic discipline is Mathematical Physics. Lenci's research focuses on dynamical systems, ergodic theory, and stochastic processes, with applications to physical systems, climate sciences, and biological systems. His work investigates infinite-measure dynamics, billiards (e.g., Lorentz gases), random walks in heterogeneous environments, and quantum large deviations. Key themes include anomalous diffusion, transport phenomena, and large deviations in quantum lattice systems. Recent studies explore limit theorems for human mobility models and applications of dynamics to epidemiology. His publications span topics like ergodic properties of quenched random systems, quantum computing, and post-quantum cryptography. No scientific awards are explicitly mentioned in the provided texts. Lenci's advising and grants activities are not detailed here, but his role as a professor suggests active mentorship. His interdisciplinary research bridges mathematics, physics, and applied sciences, contributing to both theoretical and applied domains.