Prof. Rosario Nunzio Mantegna is a Full Professor in the Department of Physics and Chemistry - Emilio Segrè at the University of Palermo (Unipa), Italy. He has held office hours in Building 18, Viale delle Scienze, focusing on appointments via email at rosario.mantegna@unipa.it. Research Interests: Econophysics, Complex Networks, Financial Market Dynamics, Air Traffic Systems, and Statistical Physics Applications. Methodological Expertise: Network Validation, Correlation Filtering, Hierarchical Clustering, and Stochastic Modeling. His work bridges physics, finance, and data science through network-based approaches to complex systems. Key contributions include analyzing financial indices, market lead-lag relationships, and air traffic networks. Publications span interdisciplinary topics from autism spectrum disorders to volcanic impact on ATM systems.
Giovanni Peres is a Professor at the Department of Physics and Chemistry, University of Palermo (UNIPA). His office is located at the University Observatory (Room No. 15, Piazza Parlamento 1), with office hours on Mondays and Tuesdays from 3:30 PM to 5:30 PM. His research spans astrophysics, focusing on supernova remnants, exoplanetary atmospheres, star formation, and stellar activity. His recent publications highlight trends in supernova remnant dynamics , exoplanet detection , and machine learning applications to astrophysical data. A recurring emphasis is on radiation transport , plasma interactions , and X-ray observations .
Hugo Lavenant is an Assistant Professor in the Department of Decision Sciences at Bocconi University in Milan, Italy. His academic journey includes a PhD in mathematics from Université Paris-Sud under Filippo Santambrogio (2016-2019) and a postdoctoral fellowship at the University of British Columbia (2019-2020) working with Young-Heon Kim, Brendan Pass, Geoffrey Schiebinger, and Dave Schneider. Professor Lavenant's research spans theoretical and applied aspects of mathematical analysis, with a focus on optimal transport theory , calculus of variations , and Bayesian statistics . His work explores the geometry of the Wasserstein space, numerical solutions to dynamical optimal transport problems, and applications to biological data analysis. He has made significant contributions to understanding harmonic mappings in the Wasserstein space, connections between optimal transport and nonlinear elasticity, and the application of optimal transport to trajectory inference in biological systems. Analysis of Professor Lavenant's recent publications reveals a strong trend toward interdisciplinary applications of optimal transport, particularly in statistics and biology. His work bridges pure mathematical theory with practical computational methods, with increasing focus on developing tractable statistical tools based on optimal transport distances. The research spans theoretical mathematics, computational methods, and applications to real-world data analysis problems. Professor Lavenant actively supervises graduate students, currently advising PhD candidates George Kanchaveli and Francesco Mascari (both co-advised with Marta Catalano), as well as Master's students Mathis Hardion and Niccolò Bargellini. His teaching portfolio includes Mathematical Analysis 2, Real Analysis I, and Advanced Analysis and Optimization 1 at Bocconi University. His scholarly contributions demonstrate a consistent focus on advancing both the theoretical foundations and practical applications of optimal transport, with growing emphasis on statistical methodology and biological applications in recent years.
Andrea Molinari is a Contract Professor at the University of Trento since 1990 and at the Free University of Bozen since 2002. He also serves as a Visiting Professor at Lappeenranta University of Technology (2021-2025) and holds a Docent position in Decision Making at the same institution (2024-2029). Previously, he was an Adjunct Professor at Turku University/Abo Akademi in Finland (2007-2019). Education: 2022: Doctoral Degree - Doctor of Science (Technology), Engineering Science, Software Engineering research field from LUT - Lappeenranta University of Technology. Dissertation: "Integration Between eLearning platforms and Information Systems: a New Generation of Tools for Virtual Communities" 1988: Master Degree in Economics from Università degli Studi di Trento with grade 110/110. Thesis: "P.I.R.S. Personal Information Retrieval Systems" Professor Molinari's research focuses on the intersection of education technology and information systems. His primary areas include e-learning/m-learning systems, virtual communities and social media, semantic technologies and ontologies, data management with AI applications, and Enterprise Project Management. His work bridges theoretical computer science with practical applications in educational and organizational contexts, particularly examining how technology can enhance learning experiences and organizational efficiency. His recent publications reveal a strong emphasis on the evolution of Learning Management Systems in the AI era, integration of semantic technologies with educational platforms, and applications of serious games for professional training. There's a clear trajectory toward more sophisticated, AI-enhanced educational technologies that incorporate data analytics, personalized learning, and advanced user modeling. Scientific Awards: Winner of the "S. Ciancio" scholarship (1980, 1982, 1983) Outstanding Paper Award at the Ed-Media World Conference on Educational Technology (1995) Since 1994, Professor Molinari has supervised approximately 10 thesis projects annually across multiple institutions including the University of Trento (Economics, Engineering), University of Bolzano (Computer Science, Education), and Abo Akademy in Finland. His teaching spans numerous courses related to information systems, project management, and technology applications across various academic disciplines. He has coordinated numerous research projects, particularly in the areas of e-learning platforms, virtual communities, and semantic technologies for educational applications. Professor Molinari is actively involved with several research communities and has served on program committees for numerous international conferences including IEEE-STAR, SMARTGREENS, and the International Conference on Web-based Education. His work often involves interdisciplinary collaboration between computer scientists, educators, and domain specialists to develop innovative technology-enhanced learning solutions.
Christian Peukert serves as Professor of Digitization, Innovation and Intellectual Property at HEC Lausanne (Faculty of Business and Economics at University of Lausanne) and leads the Digital Markets Lab. His research examines how digitization transforms consumer behavior, firm strategies, and market dynamics, with particular focus on intellectual property frameworks and the economics of data and artificial intelligence. He actively contributes to the Digital Economy Network and teaches courses in strategy, innovation, applied econometrics, and data science. Peukert's research interests center on the economic implications of digital transformation across multiple domains. His work investigates copyright economics in the digital age, AI regulation challenges, open source software business models, and the impact of data governance frameworks like GDPR. He explores how technological changes affect market efficiency in creative industries including publishing, music, and comics, while examining the relationship between innovation incentives and intellectual property systems in digital environments. His publication portfolio demonstrates strong interdisciplinary engagement across law, economics, and computer science, with recent articles appearing in top journals like Management Science, Research Policy, and Organization Science. Notable research trends include examining AI training data economics, analyzing digital market regulation effectiveness, and studying the welfare impacts of mobile internet access policies. His work frequently employs empirical methods including field experiments, natural experiments, and large-scale data analysis. Peukert has received significant recognition for his scholarly contributions, including: Best Paper Award at Strategy Science Conference for research on startup funding and open source communities Best Paper Award at WISE for work on news recommendation algorithms Best Paper Award at INFORMS Annual Meeting 2024 for research on AI training data dynamics His research has attracted media attention from major outlets including Wall Street Journal, Washington Post, MIT Technology Review, and VoxEU, demonstrating the policy relevance of his work. Peukert maintains active collaborations with researchers across Europe and regularly contributes to policy discussions on digital markets and intellectual property through his leadership in the Digital Markets Lab and Digital Economy Network.
