جست‌وجوی استاد و پژوهشگر

• Bayesian inference
• Machine learning
• Nonparametric methods
• +۵ مورد دیگر

Francesca Panero is an Assistant Professor (RTT) in Statistics at the Department of Methods and Models for Economy, Territory, and Finance (MEMOTEF) at Sapienza University of Rome. She also serves as a Visiting Fellow at the Department of Statistics of the London School of Economics and Political Science, where she was previously an Assistant Professor until May 2024. Additionally, she maintains an affiliation with the Grantham Research Institute on Climate Change and the Environment at LSE. Dr. Panero earned her PhD in Statistics from the University of Oxford in 2022, following undergraduate and master's studies at the Department of Mathematics of the University of Turin and Collegio Carlo Alberto. Her academic journey reflects a strong foundation in mathematical and statistical theory applied to complex real-world problems. Her research centers on Bayesian statistical methodologies with applications across multiple domains. She specializes in complex networks analysis using Bayesian nonparametric approaches, disclosure risk assessment for privacy preservation, spatio-temporal Gaussian process modeling for food insecurity prediction, and fair machine learning techniques. Her work demonstrates a consistent thread of developing rigorous statistical methods with practical societal applications, particularly in network science, privacy protection, and algorithmic fairness. Dr. Panero's publications reveal a strong trajectory in high-impact statistical research, with recent work focusing on sparse network modeling, fairness constraints in machine learning, and privacy-preserving statistical techniques. Her methodological contributions bridge theoretical statistics with applications in social sciences, public policy, and computational challenges. 2025 Visiting Lecturer at Faculty of Informatics, University of the Italian Switzerland (USI) Elected as j-ISBA Chair Elect for 2025-2026 Recipient of IMS junior research travel grant for ICSDS 2024 Awarded LSE Research and Impact Support Fund (RISF) grant for food insecurity research As an educator, Dr. Panero teaches Probability and Stochastic Processes at Sapienza University and has previously instructed Deep Learning and Artificial Intelligence courses at LSE. She actively mentors students and encourages PhD candidates interested in her research areas to contact her. She is also a core member of GENIAL, an LSE focus group examining how students utilize generative AI tools for learning. Beyond her technical work, she has been engaged in equality, diversity, and inclusion initiatives since 2020 and maintains an active academic blog discussing data visualization, research projects, and academic life.

Andrea Tancrediمشاهده پروفایل

استاد

• Bayesian Inference
• Bayesian Computational Methods
• Biostatistics
• +۹ مورد دیگر

Andrea Tancredi is a Professor at the Department of Methods and Models for Economy, Territory, and Finance, Sapienza University of Rome. His research focuses on Bayesian inference, computational statistics, and their applications in biostatistics, population size estimation, and health economics. He has coordinated multiple research projects funded by the University, including studies on record linkage, approximate Bayesian computation (ABC), and stochastic frontier models. Research Interests: Bayesian Inference Computational Methods (MCMC, ABC) Population Size Estimation Record Linkage and Data Integration Extreme Value Theory Biostatistics and Health Economics Teaching: He teaches courses such as Basic Statistics, Advanced Statistical Methods, and Extreme Value Theory at the Faculty of Economics and doctoral programs in Economics. Publications and Citations: With 47 publications (23 journal articles), his work spans Bayesian modeling for microbial diversity, climate-conflict risk forecasting, and multi-state health models. His research is cited 682 times on Google Scholar (h-index 12) and 401 times in Scopus (h-index 9).

• Public Economics
• Political Economy
• Public Policy Evaluation
• +۳ مورد دیگر

Marco Alberto De Benedetto serves as an Associate Professor in Public Economics (SECS/P03) at the Department of Economics, Statistics and Finance, University of Calabria since July 2020. His academic appointments include teaching Principles of Economics, Public Economics, and Public Economy for Political Science, International Relations, and Economics degree programs. His educational background includes: Bachelor and Master in Economics and Finance (University of Calabria) M.Sc. in Finance and Econometrics (Queen Mary University of London) PhD in Applied Economics (University of Calabria) PhD in Political Economy (Birkbeck College, London) De Benedetto's research centers on three interconnected pillars: the determinants of electoral participation, efficiency of public administration, and rigorous public policy evaluation. His methodological approach combines advanced econometric techniques with institutional analysis, primarily focusing on Italian and European contexts. He investigates how political institutions shape bureaucratic performance, how citizen engagement affects policy outcomes, and how regulatory frameworks influence economic behavior. His recent publications (2021-2025) reveal consistent thematic evolution toward empirical analysis of institutional design impacts. Key trends include examination of electoral systems' effects on public sector efficiency, tax compliance dynamics linked to public goods provision, and migration's socioeconomic consequences. His work frequently employs quasi-experimental methods like regression discontinuity and frontier analysis across diverse contexts from municipal budget manipulation to anti-Mafia interventions. De Benedetto maintains active research collaboration with scholars across Europe, evidenced by co-authorships with researchers from institutions in Italy, the UK, and internationally. His work appears in high-impact journals including Economic Policy , European Journal of Political Economy , and Electoral Studies , demonstrating interdisciplinary reach across economics and political science. His teaching responsibilities include graduate and undergraduate instruction in economics and public policy, with office hours held weekly at the Department of Economics, Statistics and Finance (Cubo 1C, first floor). De Benedetto actively engages with students through Teams platform consultations and provides supplementary teaching materials including exercise sessions and recommended readings.

Fabio Previdiمشاهده پروفایل

استاد

• Control Systems
• Mechatronics
• Aerospace Engineering
• +۵ مورد دیگر

Fabio Previdi is a Full Professor in Control Systems at the Department of Management, Computer and Industrial Engineering, University of Bergamo. His career spans roles from Research Assistant at the University of Glasgow (1999-2000) to Associate Professor (2006-2017) before assuming his current position. He holds a PhD in Control Systems from Politecnico di Milano (1999), MSc in Electronic Engineering (1993) and Physics (2008) from Politecnico di Milano and University of Milan. Research focuses on control systems, mechatronics, and aerospace applications. Key areas include electromechanical actuators, fault detection, system identification, and biomedical engineering. Over 150 peer-reviewed papers highlight contributions to topics like robust control, machine learning for industrial systems, and pandemic modeling. Publications (2023-2020) address cutting-edge topics such as jamming detection filters for aircraft actuators, agent-based pandemic simulations, and kernel-based system identification. Awards: Not explicitly mentioned but notable contributions recognized through extensive publication record.

• Spatial Sampling Methods
• Quantitative Criminology
• Econometrics
• +۴ مورد دیگر

Maria Michela Dickson is an Associate Professor of Economic Statistics at the University of Trento’s Department of Economics and Management. She holds a PhD in Economic Statistics from Sapienza University of Rome (2014) and has undertaken visiting research at the Institut de Statistique, University of Neuchâtel (2014–2016). Her research focuses on spatial sampling methods, quantitative criminology, and econometric modeling of spatially distributed phenomena. She has contributed to major EU-funded projects like the 'Private Corruption Barometer' and has organized international workshops on sampling techniques and spatial statistics. Education: PhD in Economic Statistics, Sapienza University of Rome (2011–2014) Master’s in Law and Economics, LUISS Guido Carli (2009–2011) Bachelor’s in Political Sciences, LUISS Guido Carli (2006–2009) Research interests include spatial sampling design , business corruption analysis , and urban security metrics . She has published extensively on methodological advancements in spatial econometrics and the impact of locational errors in data collection. Her work bridges statistical theory with practical applications in crime prevention and economic policy. Notable contributions include the Private Corruption Barometer project (EU-funded), and leadership in international conferences such as the 2022 ITACOSM conference. She is a member of the Spatial Econometric Association (SEA) and the Italian Statistical Society (SIS).

• Calculus of Variations
• Partial Differential Equations
• Mathematical Analysis
• +۳ مورد دیگر

Edoardo Mainini is an Associate Professor at the University of Genova, specializing in mathematical analysis and applied mathematics. His research focuses on calculus of variations, partial differential equations, elasticity theory, optimal transport, and nonlinear dynamics. He has contributed to studies on fractional equations, material science, and stochastic processes. His work often bridges pure and applied mathematics, addressing problems in mechanics, probability, and geometric analysis. Mainini has collaborated extensively with researchers such as M. Kružík, D. Percivale, and U. Stefanelli, producing influential papers in journals like Calc. Var. Partial Differential Equations and Arch. Ration. Mech. Anal. . His recent articles (2020–2025) address topics ranging from fractional linear equations to Bayesian nonparametric models. Education includes a PhD in Mathematical Analysis from the University of Genova (2010) and a thesis on Infinite-dimensional porous media equations and optimal transportation . He has organized international conferences and seminars on variational methods and geometric structures. His research emphasizes rigorous mathematical frameworks for physical phenomena, including the linearization of elasticity models and the study of ground states in diffusion-dominated systems. Mainini’s contributions to carbon nanotube geometries and optimal transport theory have been recognized through invited talks at major events, such as the International School of Mathematics “Guido Stampacchia” . His work often explores the interplay between discrete and continuous models, with applications to materials science and geometric optimization.

• Bayesian Statistics
• Statistical Modeling
• Applied Mathematics
• +۳ مورد دیگر

Luca LA ROCCA is an Associate Professor in the Department of Education and Humanities at the University of Modena and Reggio Emilia. His research focuses on Bayesian statistics, graphical models, complex systems analysis, and statistical applications in education and social sciences. He teaches courses such as Applied Mathematics and Social Statistics for engineering and pedagogy programs. His research spans topics including Bayesian inference for directed acyclic graphs, non-local priors, and statistical methods for analyzing complex systems. Notable contributions include work on detecting pairwise interactions in biological networks and assessing skewness in financial markets. He has also developed methodologies for structural learning in heterogeneous data and seismic hazard assessment. LA ROCCA has published extensively in top journals and conferences, with recent works emphasizing the interplay between statistical theory and real-world applications. His teaching responsibilities include courses on applied statistics, probability, and regression analysis.

• Political Economy
• Public Finance
• Fiscal Federalism
• +۶ مورد دیگر

Michele Giuseppe Giuranno is an Associate Professor (II Fascia) at the University of Salento, affiliated with the Department of Economic Sciences located at the Ecotekne Center in Lecce. His research focuses on Political Economy and Public Finance, particularly fiscal federalism, inter-jurisdictional cooperation, and the impact of institutional quality on public policy outcomes. He holds a permanent faculty position and oversees administrative duties requiring appointments via email. Education details are not explicitly provided in the text, but his academic role and publications suggest advanced training in economics or related fields. His research interests emphasize understanding how political structures influence fiscal decisions, including studies on municipal mergers, public procurement efficiency, and the effects of crises on subsidy policies. He has contributed to debates on vertical integration in taxation, managerial accountability under competition, and mafia infiltration's consequences in public sectors. While no formal awards or grants are listed, his work is part of the broader institutional framework at UniSalento, collaborating with university initiatives like the Ecotekne Center and contributing to events such as Career Days and ICT Day. Reception hours are scheduled, with the next in-person session on June 12, 2025, at 3:00 p.m.

• Machine Learning
• Cyber-Physical Systems
• Intelligent Embedded Systems
• +۵ مورد دیگر

Cesare Alippi is a Professor at Politecnico di Milano, Italy, and Università della Svizzera italiana, Switzerland, with visiting appointments at the University of Kobe (Japan) and Guangzhou (China). His research focuses on machine learning in nonstationary environments, intelligent embedded systems, and cyber-physical systems. Alippi holds IEEE Fellow status and has received notable awards, including the 2016 Gabor Award and the 2018 IEEE CIS Outstanding Computational Intelligence Magazine Award. He has authored a monograph, 6 edited books, and over 200 papers. Alippi's academic roles include Vice-President for Education of the IEEE Computational Intelligence Society and Distinguished Lecturer (2014-2016). He has organized major conferences like IJCNN and IEEE SSCI and contributed to initiatives promoting education in computational intelligence. His research addresses challenges in adaptive systems, embedded intelligence, and fault diagnosis. Key projects include deploying wireless sensor networks for environmental monitoring and developing machine learning algorithms for real-world applications like landslide prediction and network security. Alippi's awards reflect his contributions to neural networks and adaptive learning, including the IBM Faculty Award (2013) and IEEE Young Engineer Award (2004).

• Bayesian Inference
• Spatial Statistics
• Biostatistics
• +۵ مورد دیگر

Maura Mezzetti is a Full Professor of Statistics at the Department of Economics and Finance, Università degli Studi di Roma II (Tor Vergata), Rome, Italy. Her career spans institutions such as Harvard School of Public Health, Università Bocconi, and European Institute of Oncology. She holds a PhD in Methodological Statistics from Università di Trento (1997) and a Laurea in Mathematics from Università di Milano (1992). Current Position: Full Professor (2021–Present) Former Roles: Associate Professor (2010–2021), Assistant Professor (2004–2010, Tor Vergata; 2000–2005, Bocconi) Research Interests: She specializes in Bayesian statistical methods for spatially correlated data, hierarchical modeling, survival analysis, and biostatistics. Her work addresses public health challenges like cancer incidence modeling, socioeconomic disparities in disease burden, and psychometric/motor behavior analysis. She has developed Bayesian compartmental models for chemical exposure studies and contributed to epidemiological research on breast and colorectal cancer risk factors. Scientific Awards: Yamagiwa-Yoshida Fellowship (2014) ICRETT Fellowships (2012) Excellence in Research (2005) from Bocconi AIRC Fellowships (1998, 1993) Teaching Contributions: She has taught Statistics at undergraduate and graduate levels across Tor Vergata and Bocconi, including specialized courses in medicine, European economy, and data analysis. Her pedagogical efforts include authoring educational materials like "Statistica Descrittiva: Esercizi risolti e guida alla soluzione usando Excel" (2002).

• Bayesian Statistics
• Probability Theory
• Mathematical Physics
• +۳ مورد دیگر

Emanuele Dolera is an Associate Professor at the University of Pavia, affiliated with the Probability and Statistics research group. His work focuses on Bayesian nonparametric methods, probability theory, and mathematical physics, with a particular emphasis on statistical mechanics and optimal transport frameworks. He has contributed to foundational research in posterior contraction rates, stochastic processes, and the analysis of complex models like the Boltzmann equation and Ewens-Pitman sampling schemes. His research interests span Bayesian predictive inference, asymptotic theory, and the interplay between probability and partial differential equations. Notable contributions include studies on credible intervals in nonparametric estimation, exponential convergence in kinetic equations, and counterexamples in stochastic operator theory. Dolera has also edited special issues honoring prominent statisticians like Eugenio Regazzini. His publications reflect a strong theoretical orientation, addressing topics such as optimal transport applications, count-min sketches in data streams, and the asymptotic behavior of statistical estimators. While no specific grants, awards, or advisees are listed, his extensive bibliography underscores his role as a leading figure in advanced statistical methodology and mathematical analysis.

• Statistical Modeling
• Robust Statistics
• Graphical Models
• +۴ مورد دیگر

Simona Pacillo is a Researcher in Statistics at the University of Sannio, affiliated with the Department of Law, Economics, Management and Quantitative Methods. Her office is located in the De Simone building, and she can be contacted via phone or institutional email. Research Focus: Dr. Pacillo specializes in developing robust statistical methodologies with particular expertise in: Flexible probability models including Skew Normal and Skew t distributions Graphical model theory and conditional independence testing Robust statistical procedures resistant to data contamination Algorithms for Generalized Linear Models with convex penalties Model selection techniques in high-dimensional settings Publication Trends: Her recent scholarly work demonstrates consistent focus on robust statistical methodologies, with publications spanning robust circle fitting algorithms, graphical model selection under non-normal distributions, and contamination-resistant statistical procedures. Her research frequently addresses challenges in model robustness and distributional flexibility.

Nina Deliuمشاهده پروفایل

استادیار

• Bayesian Inference
• Reinforcement Learning
• Multi-armed Bandits
• +۶ مورد دیگر

Nina Deliu is a Tenure-track Assistant Professor in Statistics at Sapienza University of Rome's MEMOTEF Department, with joint appointments as a Visiting Faculty Researcher at Google and Visiting Researcher at the MRC-Biostatistics Unit, University of Cambridge. She holds editorial roles at Trials journal and YoungStatS, and maintains active collaborations with institutions including the University of Toronto, National University of Singapore, ISTAT, NADO Italia, and FAO. Education: PhD in Methodological Statistics, Sapienza University of Rome (2021) MSc in Statistics and Decisions, Sapienza University of Rome (2017) MSc in Mathématiques, Informatique, Décision et Organisation, Université Paris Dauphine (2016) Research spans Bayesian inference, reinforcement learning, multi-armed bandits, adaptive experimental design, copula models, and uncertainty quantification, with applications in healthcare, education, and public health. Her work bridges theoretical statistics with real-world challenges in biostatistics, mobile health interventions, and digital education platforms. Publications focus on adaptive experimentation frameworks, response-adaptive clinical trials, reinforcement learning in healthcare, and copula-based statistical methods. Recent work emphasizes finite-sample error control, zero-inflated count data modeling, and multivariate dependency analysis. Awards: XPRIZE $1M Digital Learning Challenge (2023) for the Adaptive Experimentation Accelerator project Research Projects: The role of self-reported health outcomes in cancer risk prediction using UK Biobank data Contextual Multi-armed Bandits for Developing Personalized Mobile Health Interventions Leads collaborations through the IAI Lab (University of Toronto) and coordinates interdisciplinary teams for projects in statistical methodology, health interventions, and official statistics innovation.

Alessandro Casaمشاهده پروفایل

دانشیار

• Mixture Models
• Modal Clustering
• Graphical Models
• +۵ مورد دیگر

Alessandro Casa is an Associate Professor of Statistics at the Faculty of Economics and Management, Free University of Bozen-Bolzano (Italy). His research focuses on developing statistical methodologies for high-dimensional and complex data, including latent variable models, density-based clustering, and applications in spectroscopy. He holds a PhD in Statistics from the University of Padova (2016-2020), preceded by master's and bachelor's degrees in Statistical Sciences and Statistics, Economics, and Finance, both from the University of Padova. Education: PhD in Statistics, University of Padova (2016-2020) Master Degree in Statistical Sciences, University of Padova (2014-2016) Bachelor Degree in Statistics, Economics, and Finance, University of Padova (2011-2014) Research Interests: Mixture models, modal clustering, graphical models, variable selection, latent variable modeling, high-dimensional data inference, computational statistics, and chemometrics. His work often addresses challenges in spectroscopic data analysis and applications in agriculture and physics. Teaching: Statistical Methods for Business Analysis (MSc programs) Research Methods and Experimental Design (Tourism Management) Statistics for Tourism, Sport, and Event Management (BSc) Professional Experience: Associate Professor (2024–Present), Free University of Bozen-Bolzano Senior Assistant Professor (2024), University of Bergamo Postdoctoral Research Fellow (2019–2021), University College Dublin Labs/Teams: Collaborations with Vistamilk SFI Research Centre and Insight SFI Research Center during his postdoctoral tenure. Active in model-based clustering research communities, contributing to conferences and workshops globally.

Ayokunle Anthony Osuntuyiمشاهده پروفایل

استادیار

• Financial Econometrics
• Computational Econometrics
• Bayesian Inference
• +۳ مورد دیگر

Ayokunle Anthony Osuntuyi is an Assistant Professor (Econometrics) at the Department of Economics, Ca' Foscari University of Venice. His research focuses on Financial and Computational Econometrics, with expertise in Bayesian Inference, Monte Carlo Methods, GARCH Models, Risk Management, and Portfolio Theory. PhD Economics (2014), University Ca' Foscari Venice, supervised by Monica Billio and Roberto Casarin Erasmus Mundus Master in Quantitative Economics (2009), University Ca' Foscari Venice, University of Paris 1, and University of Bielefeld BSc Statistics (2004), Obafemi Awolowo University, Nigeria Osuntuyi's research spans Bayesian nonparametric methods, Markov-switching GARCH models for financial volatility, climate risk analysis, EEG spectral dynamics, and optimization algorithms. He has contributed to energy futures hedging, financial cycles, and biomedical signal processing. His recent work trends include integrating Bayesian inference with panel data analysis for climate economics, advancing computational finance through nonparametric GARCH models, and applying statistical methods to neuroscience data. Collaborative projects with Roberto Casarin and Mauro Costantini highlight his focus on methodological innovation. Riccardo Faini award for best Master Thesis (2012) Erasmus Mundus Master Scholarship (2007-2009) Multiple research grants at Ca' Foscari University (2012-2020) Osuntuyi has received federal and institutional scholarships in Nigeria (2002-2003) and contributes as a referee for journals like Economic Modeling and Journal of the Nigerian Mathematical Society. His current role includes teaching and leading research projects on financial econometrics.