Find Academic Supervisors

• Complex Systems
• Network Theory
• Financial Networks
• +4 more

Guido Caldarelli is a Full Professor of Theoretical Physics at Ca' Foscari University of Venice, leading roles in the Department of Molecular Sciences and Nanosystems and the European Center for Living Technology. His career includes positions at IMT Lucca, CNR, and international visiting roles. He specializes in complex systems, network theory, and financial networks, with interdisciplinary applications in urban planning and epidemiology. Caldarelli has published ~200 articles and three books, including influential works on scale-free networks. Recognitions include APS Fellowship (2020), Academia Europaea membership, and leadership roles in global scientific societies. His research integrates statistical physics with modern data-driven approaches, addressing challenges in finance, healthcare, and environmental science. Education : PhD in Condensed Matter Theory (SISSA, 1996), MPhil (1994), and Degree in Physics (Sapienza, 1992), all with top honors. Research Interests : Caldarelli’s work focuses on network theory’s applications to complex systems, including financial risk, urban topology, and biological networks. He develops methods to quantify systemic risk in financial systems and uses network science to analyze social media dynamics, election discourse, and ecological systems. His team employs machine learning and statistical physics to uncover hidden patterns in large datasets. Key Achievements : Over 16,000 citations, h-index 64 (Google Scholar). He founded the Italian Society of Statistical Physics and co-founded Catchy s.r.l. for AI solutions. His work on scale-free networks resolved debates about network structure validity, impacting fields from epidemiology to urban planning. Awards : APS Fellowship (2020), Academia Europaea (2020), Honorary ISI Fellow, and Network Science Society’s Outstanding Service Prize (2020).

Stefano CALZAVARAView profile

Associate Professor

• Web Security
• Machine Learning
• Formal Methods
• +4 more

Stefano CALZAVARA is an Associate Professor at the Department of Environmental Sciences, Computer Science and Statistics, Ca' Foscari University of Venice. His expertise spans web security, machine learning, and formal methods. He holds a Ph.D. in Computer Science from his alma mater, following a B.A. and M.A. in the same field. His research focuses on secure web protocols, vulnerability detection, and adversarial machine learning. He teaches courses like Web Security and Computability, and contributes to the Research Institute for Complexity Communications. Notable work includes verifying tree ensembles against evasion attacks and analyzing web session security at scale. Education: Ph.D. Computer Science, Ca' Foscari University of Venice (2010-2012) M.A. Computer Science, Ca' Foscari University of Venice (2007-2009) B.A. Computer Science, Ca' Foscari University of Venice (2004-2007) Research Interests: Web security, including session integrity and content policies Machine learning robustness and certification Formal methods for protocol verification Adversarial attacks and defenses Recent Articles Trends: His recent work emphasizes securing machine learning models against adversarial attacks, formal verification of web protocols, and empirical analysis of web storage vulnerabilities. Publications appear in top venues like ACM CCS and IEEE Security Symposiums. Awards: None explicitly listed. Advising & Grants: Postdoctoral research at Ca' Foscari (2013-2015) and Saarland University (2015). Active in teaching and ethical research governance as an Ethics Commission member. Labs/Teams: Part of the Research Institute for Complexity Communications, focusing on interdisciplinary security challenges.

Roberto CASARINView profile

Professor

• Econometrics
• Computational models
• Macroeconomics
• +6 more

Roberto CASARIN is a Full Professor at the Department of Economics, Ca' Foscari University of Venice. His roles include Member of the Board of the Department of Economics, Erasmus Delegate, and Deputy Director of the International Master in Economics, Finance and Data Science. He is affiliated with the European Center for Living Technology and the Research Institute for Complexity. His research focuses on computational econometrics, dynamic models for economic analysis, stochastic volatility, and Bayesian methods applied to finance and energy markets. Key projects include Discrete Random Structures for Bayesian Learning (MUR Grant 2023-2025), EeDaPP Energy Efficiency Data Portal (EU H2020 2018-2020), and GRINS Sustainable Finance (MIUR 2022-2024). His work spans over 150 publications, with recent contributions on tensor regression, Markov switching models, and antithetic sampling techniques. He serves as Associate Editor for Bayesian Analysis , Econometrics , and Econometrics and Statistics . Awards and recognitions are not explicitly listed in the text, but his extensive editorial roles and funding indicate significant academic impact.

Salvatore ORLANDOView profile

Professor

• Computer Science
• Machine Learning
• Data Mining
• +4 more

Salvatore Orlando is a Full Professor and Director of the Department of Environmental Sciences, Computer Science and Statistics at Ca' Foscari University of Venice. He holds academic roles including membership in the University Scientific Instrumentation Service Center (CSA) Management Committee and the Academic Senate. His research focuses on machine learning, information retrieval, and data mining, with notable contributions to learning-to-rank algorithms, decision tree ensembles, and adversarial machine learning. Key areas include efficient algorithms for large-scale systems, model interpretability, and fairness in AI. Orlando’s work bridges theoretical advancements with practical applications in database technology and cybersecurity. His recent publications emphasize optimizing ranking models, enhancing algorithm resilience, and addressing ethical considerations in AI systems. He is actively involved in organizing international conferences and serves on program committees, further contributing to the academic community.

Claudio SILVESTRIView profile

Associate Professor

• Data Mining
• Privacy in Location-Based Services
• Spatio-Temporal Data Analysis
• +3 more

Claudio SILVESTRI is an Associate Professor at Ca' Foscari University of Venice, affiliated with the Department of Environmental Sciences, Computer Science and Statistics. He specializes in Computer Science (INFO-01/A), with a focus on data mining, privacy in location-based services, and spatio-temporal data analysis. His research integrates computer science with environmental and biomedical applications. Teaching Responsibilities include courses on Advanced Data Management (Computer Science) and Geographic Information Systems (Environmental Sciences) at the Master's level across multiple academic years. Research Interests span: Algorithms for privacy protection in location-based services Spatio-Temporal Data Warehouses and trajectory analysis Parallel computing on GPU and cloud platforms Applications in fisheries monitoring and diabetic kidney disease modeling Funding Projects include EU initiatives like H2020 (e.g., DC-ren for kidney disease research) and regional grants (e.g., ADMIN4D on Industry 4.0). Key collaborations involve researchers like Salvatore ORLANDO and Debora SLANZI. He is affiliated with the European Center for Living Technology (ECLT) and the Research Institute for Social Innovation. Office hours are held Wednesdays 2-4 PM by email appointment.

Marco Salvatore NOBILEView profile

Associate Professor

• Artificial Intelligence in Biomedicine
• Computational Intelligence
• High-Performance Computing
• +3 more

Marco Salvatore NOBILE is an Associate Professor at Ca' Foscari University of Venice in the Department of Environmental Sciences, Computer Science and Statistics. He serves as Rector's Delegate for Digital Innovation and Research Integrity. His academic journey includes a PhD in Computer Science from the University of Milano-Bicocca (2015), postdoctoral research there, and a position as Assistant Professor at Eindhoven University of Technology (2019) before joining Ca' Foscari in 2021. Research focuses on applying Computational Intelligence (e.g., evolutionary algorithms, neural networks) to biomedical challenges, including drug discovery, clinical decision support, and ethical AI in medicine. Key areas include medical image analysis, proteomics, and high-performance computing leveraging GPU clusters. He collaborates with institutions like CINECA and surfSARA. Teaching responsibilities include courses on Computational Intelligence for Computer Science, Digital Technologies for E-Tourism, and Informatics for Physical Engineering. He also supervises doctoral students and leads the PhD course "Knowledge, Interaction and Intelligent Systems-1". Awards: IEEE CIBCB Best Paper (2019/2022), Shark Tank Award (CMR2024), SIC Best Abstract (2022) Grants: Leading the PNRR-funded ALLIANCE project (2024-2025) on nucleic acid-based therapeutics Labs/Teams: Member of Bicocca Bioinformatics Center (B4), IEEE BBTC Co-Chair, COST Action DYNALIFE

Irene PoliView profile

Research Professor

• Statistics
• Machine Learning
• Predictive Modeling
• +5 more

Irene Poli is a Research Professor of Statistics at the European Center for Living Technology (ECLT) and the Department of Environmental Sciences, Computer Science and Statistics at Ca' Foscari University of Venice. She is a founding member and current Chair of the Science Board of ECLT, leading the Complexity and Data Analysis group. Her research focuses on statistical models for high-dimensional data, nonlinear time series, predictive neural networks, and evolutionary design optimization. Research Interests : Statistical methodologies for small data analysis Predictive analytics in healthcare and bioinformatics Machine learning applications in complex systems Optimization of molecular systems and drug discovery Awards : Fellow of the New York Academy of Science Fellow of the Bernoulli Society Fellow of the Italian Statistical Society Fellow of the Royal Statistical Society Grants & Projects : Coordinated major interdisciplinary projects including the EU-funded PACE (2004-2008), DICE (2006-2010), and MEDIUM-EU-CHINA (2015-2018). Current work includes drug development collaborations with GlaxoSmithKline and urban sustainability studies in China. Labs/Teams : Leads the ECLT Complexity and Data Analysis group and collaborates with international institutions such as the Santa Fe Institute and Los Alamos National Laboratory.

• Computer Science
• Programming Languages
• Blockchain Technology
• +3 more

Alvise SPANO' is a Researcher at Ca' Foscari University of Venice, affiliated with the Department of Environmental Sciences, Computer Science and Statistics. He is also part of the Research Institute for Complexity. His academic focus includes Blockchain Programming Languages, Programming Languages, and Information Systems. Research projects include ALGOMOVE for Algorand and the RINmaker bioinformatics tool. He has taught courses like Object-Oriented Programming and Introduction to Programming at both undergraduate and doctoral levels. Research interests span smart contract analysis, type systems, and cybersecurity in distributed systems. He contributed to projects like secure RPL for mobile networks and Android-LEGO interoperability. Funding includes the CEVID 2016 project (Role: LD), collaboratively managed with researchers like Agostino Cortesi and Salvatore Orlando. His work bridges theoretical foundations (e.g., COBOL code typing) with practical applications in wearable systems and bioinformatics. Collaborations include the Blockchain Programming Languages research group with Lorenzo Benetollo and Sabina Rossi.

• Biometrics
• Fingerprint Recognition
• Security Systems
• +3 more

Raffaele Cappelli is an Associate Professor at the Department of Computer Science and Engineering, University of Bologna. His research focuses on fingerprint biometrics, emphasizing anti-spoofing, segmentation, and synthetic data generation. He contributes to the Fingerprint Verification Competition (FVC) and has pioneered tools like SFinGe for synthetic fingerprint databases. His work addresses security vulnerabilities in biometric systems and forensic applications. Education and affiliations include roles at the University of Bologna, with expertise in computer science and engineering. His research integrates machine learning, pattern recognition, and hardware acceleration to enhance biometric system performance and reliability. Key areas of study include presentation attack detection, fingerprint orientation estimation, and large-scale database management. He has authored over 70 publications, with notable contributions to forensic science and secure authentication protocols.

• Machine Learning
• Big Data
• Artificial Intelligence in Biomedicine
• +3 more

Gastone Castellani is a Full Professor of Applied Physics and Biophysics at the University of Bologna's Department of Medical and Surgical Sciences. He holds a PhD in Physics and directs the Galvani Center for Bioinformatics, Biophysics, and Biocomplexity. His research focuses on Machine Learning, Big Data, and AI applied to biomedical data, with a particular interest in statistical interpretation of AI methods. Education: Graduate in Biology and Physics PhD in Physics Research Collaborations: Associate Professor (Research) at Brown University (since 2000), collaborating with Prof. Leon N Cooper on neural networks and gene expression analysis. Active in EU projects: GenoMed4All, SYNTHEMA, METASTRA, SYNTHIA. Awards and Recognition: Chaos and Complexity Prize (1993) Vice President Award, Brown University (2003) Grants and Projects: Lead researcher on the SYSAGEOMICS project (Brazilian visitor grant, 2025) and a Brown University grant for collaboration with Brazilian universities on circulating nucleic acids. Labs/Teams: Director of the Galvani Center, involved in interdisciplinary teams integrating computational and experimental methods for aging and age-related diseases.

• Artificial Intelligence
• Machine Learning
• Explainable AI
• +7 more

Stefano Teso is an Assistant Professor at the Interdepartmental Center for Mind/Brain Sciences (CIMeC) and the Department of Information Engineering and Computer Science, University of Trento. His research focuses on enhancing the reliability of machine learning models in high-stakes human-centric contexts through neurosymbolic integration, interactive learning, and constraint-based approaches. Master's in Computer Science, University of Trento Ph.D. in Information Engineering and Computer Science, University of Trento Teso's work combines conceptual modeling , novel neural architectures , and human-AI interaction via explanations and communication. He contributes to academic programs in Artificial Intelligence Systems (LM) and Data Science (LM) , teaching courses like Advanced Topics in Machine Learning and Machine Learning for NLP . He is affiliated with the Interdepartmental Center for Mind/Brain Sciences (CIMeC) , where he explores neurocognitive architectures and statistical relational learning frameworks.

Markus ZankerView profile

Professor

• Information Systems
• Knowledge-based Decision Support Systems
• Personalization
• +3 more

Markus Zanker is a full professor at the Faculty of Computer Science , Free University of Bozen-Bolzano (Italy), where he previously served as vice dean for studies and director for study programmes. He held associate professorship at Alpen-Adria-Universitaet Klagenfurt, Austria (2011-2016). Research Focus : Knowledge-based decision support systems, personalized information filtering/retrieval, product recommendation, conversational sales advisor systems, and product configurators Current Projects : Causal discovery in recommender systems, medical recommendation systems (insulin dosing, drug combinations), explainable AI for tourism and news recommendation The 15 most recent publications (2016-2025) cover topics including: Deep reinforcement learning for medical applications Causal modeling in tourism and online decision-making Explainable recommendation frameworks Session-based news and video recommendations Evaluation of open-source recommendation libraries His work also explores user interaction patterns through studies on bimodal rating statistics, collaborative explanations, and proactive recommendation engagement.

Francesca PARPINELView profile

Associate Professor

• Statistics
• Machine Learning
• Econometrics
• +3 more

Francesca PARPINEL serves as an Associate Professor in the Department of Economics at Ca' Foscari University of Venice, holding additional responsibilities as Department Delegate for Language Training. Her academic work spans statistical methodology development and practical applications in economics and finance. Her educational background includes a Degree in Statistics Applied to Economics (1990) and PhD in Statistics (1994), both from the University of Padua. She progressed from Assistant Professor (1996-2002) to her current Associate Professor position (2002-present), while coordinating the Bachelor's Degree Program in International Trade and Tourism from 2011-2018. Research interests focus on advanced statistical methodologies including estimation methods for regressions on complex spaces , evolutionary algorithms for regime-changing models , and statistical measures of systemic risk . Her work bridges theoretical statistics with practical financial applications, particularly in trading systems and risk assessment. Recent publications demonstrate strong interdisciplinary connections between statistics, finance, and computational methods, with increasing emphasis on machine learning applications in financial distress prediction and climate derivatives pricing. She actively supervises undergraduate and graduate theses requiring data analysis, emphasizing proficiency in R programming. Her teaching portfolio includes Statistics, Multivariate Statistics, and specialized laboratories across multiple degree programs including International Trade and Tourism, Economics and Commerce, and Global Development. PARPINEL has organized significant academic events including SIS 2015 (Statistics and Demography: the Legacy of Corrado Gini) and multiple MAF conferences, while maintaining membership in the Italian Statistical Society (SIS).

Claudio PizziView profile

Associate Professor

• Time Series Analysis (Economic and Financial)
• Evolutionary Statistics
• Statistical Analysis with Latent Variables
• +5 more

Claudio Pizzi is an Associate Professor of Economic Statistics at the Department of Economics within Ca' Foscari University of Venice . He also participates in the Interdepartmental School of Economics, Languages and Entrepreneurship for International Exchanges at the Treviso campus. With over two decades at the institution (since 2004 as faculty), he has extensive experience in quantitative methods and their applications to economic/financial phenomena. Academic affiliation: Department of Economics & SELISI Interdepartmental Center Research locations: San Giobbe (Venice) and Palazzo San Paolo (Treviso) Office hours: Venice (Wednesdays) and Treviso (Thursdays) via in-person or virtual meetings His research integrates statistical modeling with artificial intelligence , focusing on: Financial time series analysis (parametric/non-parametric) Machine learning applications in economic and financial contexts Technical analysis trading strategies Emotional/social/cognitive competency measurement Nonlinear cointegration and hidden dependency detection Article analysis reveals consistent themes in computational finance , evolutionary algorithms , and organizational behavior . He frequently employs Particle Swarm Optimization for financial modeling, explores emotional intelligence in career development, and contributes to actuarial science through derivative pricing and risk modeling techniques. As part of his academic service, Pizzi: Participates in the SELISI Joint Commission Organizes international conferences (MAF2008, MAF2012) Collaborates across disciplines with institutions like the Department of Management Teaches computational methods to economics students

Stefano Federico TonellatoView profile

Associate Professor

• Statistical space-time models
• Statistical model choice
• Semiparametric models
• +7 more

Stefano Federico Tonellato is an Associate Professor at the Department of Economics, Ca' Foscari University of Venice. His academic responsibilities include serving as Departmental Delegate for Information Technology Infrastructure. 1992: Degree in Economics, Ca' Foscari University of Venice 1993-1994: Visiting student, Department of Statistics, Warwick University (UK) 1996: PhD in Statistics, University of Padua His research focuses on statistical modeling for economic, financial, and environmental applications, with expertise in Bayesian nonparametric clustering, space-time models, semiparametric methods, and computational statistics. He has participated in EU research networks and regionally-funded health monitoring projects. Recent publications explore Bayesian clustering as community detection in financial data, health workforce forecasting, and spatio-temporal modeling. His work emphasizes predictive analytics and complex data structures. As a referee, he evaluates research projects for institutions like the University of Padua and contributes to journals including the Journal of the Royal Statistical Society and Computational Statistics and Data Analysis. He supervises theses in applied statistics for economics, finance, and environmental studies, requiring pre-discussion agreement on topics.