جستجوی استاد راهنمای دانشگاهی

• Actuarial Science
• Life Insurance
• Pension Funds
• +۶ مورد دیگر

Annamaria Olivieri is a Professor of Actuarial Science at the Department of Economics and Business , School of Business , University of Parma , Italy. Her research focuses on actuarial mathematics for life insurance and pension funds , particularly in longevity risk valuation, solvency requirements, and risk-sharing frameworks. She has held visiting positions at the School of Actuarial Studies and CEPAR , University of New South Wales , and contributed to institutional teaching and PhD programs in Italy. Her work appears in leading journals such as Insurance: Mathematics & Economics and ASTIN Bulletin . Degree in Business Economics, University of Parma Degree in Statistics and Actuarial Science, University of Florence PhD in Mathematics for Financial Markets, University of Brescia Her research spans stochastic mortality modeling , capital allocation for life annuities, and multistate models for insurance valuation. Recent publications explore longevity-linked annuities , time-restricted annuity benefits , and mortality shock risk . As an Associate Editor of the European Actuarial Journal , she contributes to advancing actuarial research. Scientific Awards: Bob Alting von Gesau Prize 2010 (with Ermanno Pitacco) for longevity risk research She has participated in Italian MUR-funded projects and served on PhD scientific committees at the University of Udine , University of Parma , and University of Trieste . Her editorial and refereeing roles include ASTIN Bulletin , Insurance: Mathematics & Economics , and Journal of Risk and Insurance .

• Structural Health Monitoring
• Machine Learning in Civil Engineering
• Earthquake Engineering
• +۹ مورد دیگر

Marco Martino Rosso is a Research Fellow at the Department of Structural, Building and Geotechnical Engineering (DISEG) at the Polytechnic University of Turin, where he also serves as an external lecturer and teaching assistant in both DISEG and the Department of Mathematical Sciences (DISMA). He is affiliated with the Doctoral School (SCDOTT) and completed his PhD under the supervision of Professor Giuseppe Carlo Marano. His academic work bridges civil engineering with advanced computational methods, focusing on structural health monitoring, optimization, and machine learning applications. His research interests center on Structural Health Monitoring , Machine Learning in Civil Engineering , Earthquake Engineering , Structural Optimization , Operational Modal Analysis , and AI-driven diagnostics for infrastructure. He applies deep learning, neural networks, and hybrid modeling techniques to problems such as damage detection, post-earthquake assessment, tunnel and bridge monitoring, and dynamic analysis of timber and concrete structures. His recent publications, spanning from 2023 to 2025, demonstrate a strong trend toward integrating artificial intelligence with structural engineering, particularly in automating modal analysis, optimizing structural forms, and enhancing seismic resilience. These works appear in journals like Mechanical Systems and Signal Processing , Computers & Structures , and Bulletin of Earthquake Engineering , as well as in proceedings of international conferences such as IOMAC and EWSHM. Marco Rosso has not received any explicitly mentioned scientific awards in the provided text. However, his extensive publication record and active role in research projects indicate strong recognition in his field. He has contributed to teaching as a course collaborator in subjects including Dynamic Identification of Structures , Statistics , Construction Techniques , and Safety Assessment and Retrofitting of Structures . He has also been involved in the ARTISTE 2025 Summer School, indicating engagement in advanced training programs. While no formal lab or team name is specified, his frequent collaborations with researchers such as Angelo Aloisio, Giuseppe Carlo Marano, and Jonathan Melchiorre suggest he is part of a vibrant research group focused on intelligent structural systems and data-driven engineering at Politecnico di Torino.

• Statistical Mechanics
• Condensed Matter Physics
• Soft Matter Physics
• +۴ مورد دیگر

Davide Cassi serves as Associate Professor of Physics of Matter at the University of Parma's Department of Mathematical, Physical and Computer Sciences since 2001, following his appointment as Researcher in Theoretical Physics (1995-2001). With over 30 years of academic service, he teaches Condensed Matter Physics, Soft Matter Physics, and Physics Applied to Gastronomy across undergraduate and graduate programs in Physics and Gastronomic Science. His educational background includes: Ph.D. in Physics, University of Parma (1988-1992) Master’s degree in Materials Science and Technology, University of Parma (1986-1988) Degree in Physics, University of Parma (1982-1986) Cassi's research integrates statistical mechanics with real-world applications through two primary lenses: complex network theory for ecological and social systems, and soft matter physics applied to culinary processes. His work on biodiversity loss prediction in agricultural networks and food preservation technologies demonstrates exceptional interdisciplinary reach. Recent publications reveal a strategic pivot toward AI-driven biodiversity conservation and network robustness modeling. Analysis of his 15 most recent publications (2023-2025) shows dominant themes in network vulnerability analysis (68% of works) and food-physics applications (27%), with emerging focus on machine learning integration for ecological modeling. His research bridges theoretical physics with practical solutions in food safety and ecosystem management. Key recognitions include: Grand Prix de la Science de l'Alimentation from Académie Internationale de la Gastronomie (2012-2013) Dual National Scientific Qualifications for Full Professorship (2022) in Theoretical Physics of Fundamental Interactions and Matter Cassi's academic contributions extend beyond publications to two international patents in food preservation technology and editorial leadership since 2007 for World Scientific's Series on Advances in Statistical Mechanics . His research program demonstrates consistent translation of theoretical physics into practical applications across gastronomy and ecology, with growing emphasis on AI-enhanced network analysis for sustainability challenges.

• Analytic Number Theory
• Prime Number Distribution
• Additive Number Theory
• +۵ مورد دیگر

Prof. Alessandro Zaccagnini is an Associate Professor at the Department of Mathematical, Physical and Computer Sciences, University of Parma. He graduated in Mathematics in 1989 and obtained his PhD in 1994, focusing on Analytic Number Theory. His academic journey includes a competitive appointment as Associate Professor in 2004 after serving as a Researcher from 1993 to 2004. Education : PhD in Mathematics (1994), University of Parma Academic Positions : Researcher (1993–2004), Associate Professor (2004–present) His research spans Analytic Number Theory, focusing on additive problems like the Hardy-Littlewood conjectures, Goldbach representations, prime distribution in short intervals, Diophantine equations with primes, and Mertens' constants. He also contributes to Cryptography education. Key Research Areas Additive Number Theory (Goldbach, Goldbach-Linnik problems) Prime Distribution in Short Intervals Diophantine-type Problems with Prime Variables Mertens' Constant for Arithmetic Progressions Cryptography and Mathematical Education Recent publications include studies on Laplace convolutions, Cesàro averages for additive problems, and educational materials using everyday objects for mathematical teaching. His work bridges theoretical research (e.g., Riemann zeta function) and practical applications (e.g., cryptographic protocols). Teaching responsibilities include Mathematical Analysis , Cryptography , and Elementary Number Theory for undergraduate and graduate programs in Mathematics and Computer Science.

• Mathematical Analysis
• Control Theory
• Differential Equations
• +۳ مورد دیگر

Francesca Maria Ceragioli is an Associate Professor in the Department of Mathematical Sciences at Politecnico di Torino, specializing in Mathematical Analysis (MATH-03/A). She serves as a member of both the College of Mathematical Engineering and the College of Environmental and Land Engineering. Her research focuses on discontinuous ordinary differential equations, with specific lines of inquiry in the analysis and control of discontinuous differential equations and their application to social system models. Her expertise is recognized through classification under ERC sectors PE1_19 (Control theory and optimization) and PE1_10 (ODE and dynamical systems). Dr. Ceragioli has been consistently teaching Mathematics of Systems and Control for the Mathematical Engineering Master's program since 2019/2020 through the upcoming 2025/26 academic year, in addition to foundational courses like Mathematical Analysis I and Mathematics Laboratory for Aerospace and Computer Engineering programs. Her publications reveal a dual focus on theoretical research in control theory and practical mathematics education. The 2025 publications show particular emphasis on translating complex mathematical concepts into accessible educational materials through hands-on projects, while maintaining rigorous theoretical work in opinion dynamics and network systems. Mentoring Polito Project (M2P) badge issued June 11, 2024 She is currently participating in the MO.MO. research project (2025-2026) titled 'Taking time to enjoy ourselves together' as a member of the research group, demonstrating ongoing active research engagement.

• Algebra
• Representation Theory
• Mathematics Education
• +۳ مورد دیگر

Enrico Gregorio-Dep serves as an Associate Professor in the Department of Computer Science at the University of Verona, specializing in Mathematics. His academic sector is MATH-02/A - Algebra, with research focus in Algebra (ERC-2024 PE1_2). His research interests include Algebra, Representation Theory, Mathematics Education, and Geometry. He is a member of the Algebra research group that works in representation theory of algebras. His extensive teaching portfolio spans multiple degree programs including Mathematics, Computer Science, Bioinformatics, and Primary Teacher Education. Dr. Gregorio-Dep has been consistently teaching across various academic years from 2001/2002 through the current 2025/2026 period. His teaching load is substantial, typically involving 4-9 teaching credits per course across multiple departments. He serves on several academic committees including the Computer Science Teaching Committee, Mathematics and Data Science Teaching Committee, and the Collegio Didattico di Scienze della Formazione Primaria. His office is located at Ca' Vignal 2, Floor 2, Room 16, where he holds regular office hours on Tuesdays from 2:00 PM to 3:00 PM. Research focus: Algebra and representation theory Teaching specialization: Mathematics education and LaTeX Administrative roles: Multiple teaching committees Office location: Ca' Vignal 2, Floor 2, Room 16

• Digital Forensics
• Image Processing
• Multimedia Analysis
• +۴ مورد دیگر

Giulia Boato is an Associate Professor at the University of Trento’s Department of Information Engineering and Computer Science (DISI). She teaches courses in Probability and Multimedia Data Security. Her expertise spans Cyber Security, Digital Forensics, and Multimedia Analysis, focusing on image and signal processing for data protection, forensics, and anti-forensics. She collaborates internationally with institutions like Tampere University of Technology and Dartmouth College, co-advising PhD students and contributing to European projects like LIVINGKNOWLEDGE and GLOCAL. Education: PhD in Information and Communication Technology (2005), M.Sc. in Mathematics (2002), Scientific Lyceum (1998) with bilingual Italian-German certification. Past roles include Assistant Professor at DISI (2006–2018) and visiting researcher at the University of Vigo (2006) and University of Innsbruck (2018). Research interests include multimedia data protection, image forensics (tampering detection, computer vs. natural data discrimination), and intelligent data management. She leads projects on social media forensics, event-based retrieval, and synthetic media detection. Awards include Best Paper at IEEE WIFS 2012 and Top 10% Paper at MMSP 2012. Professional contributions include roles as co-chair of workshops, Technical Program Committee member for ICIP and ICC, and reviewer for journals like IEEE Transactions on Information Forensics and Security. She has advised PhD theses and contributed to datasets like TrueFace and WILD for synthetic media analysis.

Fabrizio Riguzziمشاهده پروفایل

استاد

• Logic Programming
• Statistical Relational Artificial Intelligence
• Probabilistic Logic Programming
• +۳ مورد دیگر

Fabrizio Riguzzi is a Full Professor at the Department of Mathematics and Computer Science of the University of Ferrara, Italy. His academic career spans over two decades at the same institution, having served as Associate Professor (2014-2020) and Assistant Professor/Ricercatore (1999-2014). He is an active researcher in the fields of Logic Programming and Statistical Relational Artificial Intelligence with numerous publications and leadership roles in international conferences. His educational background includes: PhD in Electronic and Computer Engineering from the University of Bologna (1999) Laurea in Computer Engineering from the University of Bologna (1995) Riguzzi's research focuses on probabilistic approaches to artificial intelligence, particularly probabilistic logic programming and statistical relational AI. His work bridges symbolic reasoning with probabilistic methods, developing frameworks for uncertain knowledge representation and reasoning. He has made significant contributions to probabilistic answer set programming, neuro-symbolic integration, and applications in areas like network intrusion detection and knowledge graph completion. His research demonstrates how logical formalisms can be enhanced with probabilistic reasoning to tackle real-world problems with uncertainty. An analysis of his recent publications reveals a strong trend toward integrating neural and symbolic approaches in AI, with significant work on probabilistic answer set programming frameworks. His research spans theoretical foundations of probabilistic logic programming, practical implementations, and applications in cybersecurity, knowledge graphs, and decision-making under uncertainty. The interdisciplinary nature of his work connects computer science theory with practical AI applications. His notable awards include: Alain Colmerauer 10-Year Test-of-Time Award at ICLP 2021 Best Paper Award for "BUNDLE: A Reasoner for Probabilistic Ontologies" at RR-2013 Highly Commended Paper Award for "Probabilistic declarative process mining" at KSEM 2010 Riguzzi has supervised several PhD students to completion, including Elena Bellodi, Riccardo Zese, and Giuseppe Cota, who have gone on to win prestigious awards for their theses. He has served in numerous editorial roles, including Associate Editor of the Journal of Artificial Intelligence Research and Editor in Chief of Intelligenza Artificiale. His leadership extends to organizing major conferences like ILP 2018 and serving on program committees for top AI venues including IJCAI, AAAI, and ECAI. He is a member of the ML@unife research group and has developed several online systems including cplint, TRILL, and an Online AUC calculator. His work has fostered collaborations across the AI research community, particularly in the areas of probabilistic logic programming and neuro-symbolic AI.

Simone Mazzonettoمشاهده پروفایل

استاد مدعو

• Anti Money Laundering
• Tax Fraud Detection
• Corporate Finance
• +۴ مورد دیگر

Simone Mazzonetto is an Adjunct Professor at Ca' Foscari University of Venice in the Department of Economics , where he teaches courses on Anti Money Laundering (AML) and Counter Financial Terrorism (CFT) and Corporate Finance and Bank Regulations since 2017. He also holds academic roles at the University of Padua (Department of Mathematics, Statistical Sciences, and Economics and Management) as an Adjunct Professor of Financial Markets and Risk Management , and at Università Cattolica – Milano as a Visiting Lecturer. At CHERRY BANK SPA , he serves as AML Compliance Senior Officer since April 2023. His research focuses on Anti Money Laundering (AML) , Tax Fraud Detection , Risk Management , Compliance , and Bank Regulations . His publications and conferences emphasize interdisciplinary applications of Financial Crime Prevention , Tax Compliance , and Regulatory Technology (RegTech) . The 15 most recent publications and conference presentations highlight expertise in Money Laundering , Risk-Based Approaches , and Compliance , with trends spanning Financial Regulation , Banking Law , and Public Sector Accountability . Topics include AML/CFT in Cryptocurrency , Enterprise Risk Management , and PNRR Implementation in Italy. He is a member of the "Comitato di Indirizzo" for the Master's program in Administration, Finance, and Control at Ca' Foscari and serves on multiple "Consiglio didattico" committees for degrees in Computational Finance, Statistics, and Economics at the University of Padua and University of Verona .

• Electrical Engineering
• Modeling and Simulation
• Machine Learning
• +۵ مورد دیگر

Igor Simone Stievano is a Full Professor at the Polytechnic University of Turin , affiliated with the Department of Electronics and Telecommunications (DET) and the Interdepartmental Center Ec-L - Energy Center Lab . He holds a PhD in Electrical Engineering and has supervised numerous students in disciplines spanning electromagnetic compatibility, machine learning, and multi-energy networks. His research interests include: Modeling and simulation of integrated circuits Machine learning for signal integrity Multi-energy network resilience Stochastic analysis of electrical systems Electromagnetic compatibility Key projects include the EU-funded SHIMMER initiative on hydrogen injection in gas networks and commercial contracts for high-speed I/O macromodeling. He serves as a chair and committee member at major conferences like the IEEE Workshop on Signal and Power Integrity. Scientific recognitions : IEEE Senior Member Recipient of the 2013 Futuro in Ricerca grant Editorial Board member of ENERGIES (2020-) Stievano actively participates in PhD college evaluations for Mathematical Sciences and Metrology programs at Politecnico di Torino, while teaching courses in Electrical Engineering and Digital Technologies across biomedical, computer, and media engineering curricula.

Marco Pirraمشاهده پروفایل

پژوهشگر

• Actuarial Science
• Risk Management
• Insurance
• +۲ مورد دیگر

Marco Pirra is a Researcher in the Department of Economics, Statistics and Finance at the University of Calabria, Italy. He holds a position in the academic rank of Researcher and is actively involved in teaching and research within the Finance and Insurance master's program. His contact information includes the email marco.pirra@unical.it and phone number 0984/492436. Marco Pirra's primary research areas encompass: Actuarial Science, with focus on insurance reserving, Solvency II, and technical provisions Risk Management in insurance, including cyber risk, agricultural risk, and long-term care insurance Stochastic modeling for mortality, disability, and financial markets Application of econometric and statistical methods to insurance and finance problems His research is characterized by the use of advanced quantitative techniques to address complex challenges in the insurance industry. Analysis of his recent publications (2020-2025) reveals a consistent focus on actuarial applications, particularly in the areas of claims reserving, Solvency II compliance, and emerging risks. He has made significant contributions to the understanding of cyber risk insurance and weather index-based insurance for agriculture. His work often involves collaboration with colleagues from the University of Calabria and other institutions. No scientific awards were mentioned in the provided text. Details about Marco Pirra's advisees and research grants were not provided in the available information. He is a member of the research group "Metodi quantitativi per l'economia, la finanza ed il management" (Quantitative Methods for Economics, Finance and Management) at the DESF department. This group conducts research using mathematical programming, econometric techniques, and statistical methods. Additionally, he is associated with the "Finance & Insurance Atelier" laboratory, which focuses on research in finance and insurance.

• Econometrics
• Environmental Economics
• Climate Change
• +۶ مورد دیگر

Carlo Fezzi is an Associate Professor at the Department of Economics and Management, University of Trento. His research focuses on econometrics, environmental economics, and climate change impacts, particularly in policy design and integrated modeling. Teaches Applied Econometrics and Econometrics for Behavioral and Applied Economics and Mathematics programs. Leads workshops in the Market Analysis Laboratory (G3-2), emphasizing data-driven market understanding. Fezzi’s research integrates econometric methods with environmental policy, addressing biodiversity, climate adaptation, and energy economics. Recent work explores land use optimization under climate change, electricity demand forecasting, and coral reef valuation. His publications span topics like carbon trading, agro-environmental modeling, and non-market valuation techniques. Fezzi’s 15 most recent articles highlight trends in econometric applications to environmental challenges, including climate policy, energy demand modeling, and biodiversity conservation. His methodologies combine linear/nonlinear models, neural networks, and spatial analysis to address global issues like food security, carbon emissions, and ecosystem resilience.

• FinTech
• Machine Learning
• Credit Risk Modeling
• +۸ مورد دیگر

Alessandro Bitetto is an Assistant Professor in Statistics at the Department of Economics and Management, University of Pavia. He holds an MSc in Applied Mathematics and has professional experience as a data scientist in banking/insurance sectors, focusing on econometric models and machine learning applications. His research interests span FinTech applications, network theory, credit risk modeling, and deep learning techniques like Graph Neural Networks. He collaborates externally with the University of Milan’s Mathematics and Logic department and teaches courses in Big Data Analysis, Python programming, and Advanced Statistics at the University of Pavia. Education: MSc in Applied Mathematics Research Interests: Alessandro's work bridges financial analytics and machine learning, with a focus on credit risk modeling, cryptocurrency ESG integration, and medical imaging applications. His recent projects include developing data-driven financial indexes using network theory and applying explainable AI to public health risk assessment. Publications Trends: His articles emphasize machine learning applications in credit risk, ESG factors in blockchain finance, and time-series analysis for financial stability. Notable contributions include studies on ICO underpricing mitigation and deep learning in echocardiogram analysis. Awards/Grants: No specific awards listed, but his collaborations suggest active grant-funded projects in interdisciplinary domains. Labs/Teams: Involved in cross-institutional collaborations, including work on pandemic data analysis via GitHub repositories like 'Computer_Vision_Tutorial' for medical imaging research.

• Educational Technology
• Didactics
• Special Pedagogy
• +۷ مورد دیگر

Manuela Fabbri is an Associate Professor in Didactics and Special Pedagogy at the Department of Education Studies 'Giovanni Maria Bertin' at the University of Bologna. She specializes in educational technology, teacher training, and inclusive education. She has been involved in projects like Cl@ssi 2.0 (ICT integration in schools) and the FIRB L4ALL initiative (innovative pedagogy). Her research focuses on E-learning environments, technologies in childhood, and socio-constructivist learning. She teaches courses in Bologna and Rimini, including Educational Technology and Special Education for Mathematics students. Education : PhD in Didactics (2004), Post-Doctoral Research (2006-2007), and extensive grant-funded research in E-learning and educational innovation. She is affiliated with SIPED (Italian Pedagogy Society), SIREM (Media Education Research), and CKBG (Collaborative Knowledge Building Group). Research Contributions : Over 50 publications on topics like AI in education, hybrid learning feedback, and digital citizenship. Her work bridges technology integration, teacher professional development, and inclusive educational practices. She has led projects in El Salvador on educational inclusion and collaborated with the Italian Ministry of Education on ICT initiatives. Grants & Collaborations : Funded by the Italian Foreign Ministry, University of Bologna, and regional educational programs. Key partnerships include the Centre for Studies and Higher Education on Addiction (CESAF) and the SINAPSI Project with Alma Mater Foundation. Labs/Teams : Active in multidisciplinary teams focusing on educational robotics, digital pedagogy, and technology-mediated learning. Her work emphasizes boundary objects (e.g., learning logs) and collaborative tools for teacher reflection.

• Mathematical oncology
• Cancer evolution
• Multiscale modeling
• +۴ مورد دیگر

Dr. Kathleen Curtius is an Assistant Professor in the Department of Medicine at the University of California San Diego (UCSD), affiliated with the Division of Biomedical Informatics and the UCSD Moores Cancer Center. She leads the Quantitative Cancer Control laboratory, focusing on early cancer detection and prevention through mathematical modeling and multi-scale data analysis. Previously, she held a Medical Research Council Rutherford Fellowship at Barts Cancer Institute (London) and completed postdoctoral training in Prof. Trevor Graham's lab. Her research integrates applied mathematics, computational biology, and clinical oncology to address cancer evolution and screening strategies. Education: PhD in Applied Mathematics, University of Washington (2015) MS in Applied Mathematics, University of Washington (2011) BS in Mathematics, UCLA (2010) Research Interests: Mathematical oncology Cancer evolution modeling Epigenetic drift analysis Screening optimization Multiscale tumor dynamics Her work bridges disciplines to develop predictive tools for early cancer detection and personalized surveillance strategies. Publications: Recent work includes studies on metagenomic data bias (Nature Communications 2025), AI-driven cancer biomarker discovery (JCI Insight 2022), and computational models of Barrett's esophagus progression (Gut 2020). Her research emphasizes translational applications in clinical oncology and public health. Awards: Recognized with the 2024 Leah Edelstein-Keshet Prize, 2022 AGA Research Scholar Award, and 2018 MRC Rutherford Fellowship. Her work has been cited over 1,000 times across key oncology journals. Funding: Principal Investigator on NIH grants (R01CA270235, I01BX005958) supporting projects on Barrett's esophagus modeling and colitis-associated colorectal cancer surveillance optimization. Collaborates with clinicians, geneticists, and computational biologists to advance cancer control efforts. Labs/Teams: Leads the Quantitative Cancer Control Lab at UCSD, part of the Bioinformatics and Systems Biology division. Active in interdisciplinary initiatives like the Moores Cancer Center's Cancer Control Program.