جست‌وجوی استاد و پژوهشگر

• Computational Chemistry
• Organic Chemistry
• Quantum Chemistry
• +۴ مورد دیگر

Daniele Padula serves as an Associate Professor in the Department of Biotechnology, Chemistry and Pharmacy at the University of Siena, where he teaches Applied Computational Chemistry, Organic Chemistry, and Heterocyclic Organic Chemistry for Chemistry, Biotechnology, and Pharmacy degree programs. His institutional contact details include office location (II lotto, III floor, room B_03_86) and direct communication channels through university email and phone systems. Padula's research integrates computational and organic chemistry methodologies to investigate fundamental properties of organic electronic materials. His primary focus areas include quantum-mechanical modeling of charge transport mechanisms, design of chiral photoluminescent systems with inverted singlet-triplet gaps, development of accurate force fields for molecular simulations, and computational exploration of photoswitches and organic semiconductors. This interdisciplinary work bridges theoretical chemistry with practical applications in optoelectronics and materials science. Analysis of his 15 most recent publications (2024-2025) reveals three dominant research thrusts: (1) Advanced computational protocols for quantum-mechanically derived force fields (evident in JOYCE3.0 development), (2) Fundamental studies of chiral phenomena in organic materials for circularly polarized luminescence applications, and (3) Multiscale modeling of charge and exciton transport mechanisms in organic semiconductors. His work increasingly incorporates machine learning techniques to accelerate materials discovery while maintaining quantum chemical accuracy. Scientific awards: No awards or fellowships were documented in the provided materials. Advising and grant activities: The available documentation does not specify doctoral students, postdoctoral researchers, or externally funded research projects. His teaching portfolio indicates supervision of graduate and undergraduate theses within his computational chemistry courses. Research infrastructure: While specific laboratory facilities aren't detailed, his publication record suggests active participation in computational research groups with access to high-performance computing resources, likely through the University of Siena's computational chemistry infrastructure and potential collaborations with experimental groups for validation studies.

• Econometrics
• Economic Statistics
• Policy Impact Evaluation
• +۳ مورد دیگر

Riccardo D'Alberto is a Senior Fixed-Term Researcher (RTD-B) and Temporary Assistant Professor at the Department of Economics , University of Verona. He specializes in quantitative methods for policy evaluation and data integration in socioeconomic/environmental contexts. Research Focus: Causal effect analysis (Propensity Score Matching, Diff-In-Diff), statistical matching for data integration, environmental valuation (CVM/CE methods), and quantitative policy assessment at regional scales. His work bridges econometrics, data science, and sustainability science. Notable Collaborations: Participated in Horizon 2020 projects (PROVIDE, LIFT, CONSOLE), FP7 IMPRESA, and European Commission tenders. Affiliated with Verona Experimental Lab in Economics (VELE) and Visual Research Lab . Teaching: Delivers Business Statistics and Financial Statistics courses for Master’s programs in Marketing & Corporate Communication and Banking & Finance.

ANDREA CESARE RESTIمشاهده پروفایل

دانشیار

• Financial Risk Management
• Credit Risk
• Bank Supervision
• +۴ مورد دیگر

Andrea Cesare Resti is an Associate Professor at the Department of Finance, Bocconi University. He leads courses on Credit Risk, Risk Management, and Private Banking in graduate programs. His research focuses on financial regulation, credit risk modeling, and bank supervision. He co-founded Bocconi’s Baffi Carefin Centre and advises the European Parliament on banking supervision. His work bridges academia and practice, with publications in top journals and books on Basel Accords and credit risk management. Resti holds a prominent role in financial policy, having served in the European Banking Authority’s Stakeholder Group and advising European institutions. His academic contributions include methodologies for credit risk assessment, recovery risk analysis, and economic capital modeling. He collaborates with financial institutions, rating agencies, and regulators globally. His research outputs span empirical studies on default-recovery linkages, LGD modeling, and Basel II implementation. He emphasizes practical applications of theoretical frameworks in banking and asset management. His advisory roles and institutional collaborations reflect his dual expertise in academic research and regulatory practice.

Alessandra GIORGIمشاهده پروفایل

استاد

• Linguistics
• Syntax
• Pragmatics
• +۳ مورد دیگر

Alessandra Giorgi is a Full Professor at the Department of Linguistics and Comparative Cultural Studies at Ca' Foscari University of Venice. She specializes in theoretical linguistics with a focus on syntax, pragmatics, and cross-linguistic comparison. Her research integrates formal syntactic theory with empirical studies on languages such as Italian, Armenian, and Romance varieties. Research Interests: Syntax-Pragmatics Interface, Tense and Aspect, Discourse Structure, and Language Typology. Expertise: Comparative linguistics, morphosyntactic analysis, and syntactic theory within the Minimalist Program. Her work bridges syntactic formalism with discourse-functional perspectives, particularly in analyzing expressions of surprise, question types, and evaluative morphology. She has conducted extensive studies on Eastern Armenian syntax and Romance languages, contributing to the understanding of V2/V3 phenomena and information structure. Giorgi serves on editorial boards for journals like Italian Journal of Linguistics and Rivista di Grammatica Generativa . She collaborates in international projects such as the Rethinking, Understanding Modal Particles (RUM) initiative funded by PRIN 2022. Her research also involves interdisciplinary approaches to digital cultural heritage through the Research Institute for Digital and Cultural Heritage at Ca' Foscari.

Augusto Cerquaمشاهده پروفایل

دانشیار

• Regional and Industrial Policy
• Education and Labour Economics
• Political Economy
• +۲ مورد دیگر

Augusto Cerqua serves as Associate Professor of Economic Statistics at Sapienza University of Rome's Department of Social and Economic Sciences. His research focuses on industrial/regional policy impacts and counterfactual evaluation methods, with publications spanning top journals including Journal of Regional Science, Regional Studies, and Journal of Environmental Economics and Management. He teaches advanced courses in empirical modeling, policy evaluation, and statistical methods for public policy. Cerqua's research program centers on Regional and Industrial Policy, Education and Labour Economics, Political Economy, and Tourism and Environmental Economics. He employs rigorous quantitative techniques—particularly regression discontinuity designs and non-parametric methods—to evaluate policy effectiveness. His work bridges theoretical frameworks with real-world applications in public administration, emphasizing causal inference in contexts like local governance, migration flows, and environmental policy implementation. The ERC SH1_13 and SH2_9 classifications reflect his expertise in institutional dynamics and regional development. Analysis of his recent publications reveals a dominant focus on policy evaluation methodologies applied to pressing socio-economic challenges. Key thematic clusters include political economy (examining electoral behavior and institutional incentives), regional development (assessing spatial disparities and place-based interventions), and crisis response (quantifying pandemic impacts and recovery trajectories). His methodological signature involves innovative causal inference approaches for contexts lacking clear control groups, frequently leveraging administrative data and spatial regression techniques. Cerqua actively leads research projects including 'The impact of place-based policies when public transfers fade out,' demonstrating sustained engagement with EU structural funds evaluation. His teaching portfolio—covering empirical models, computational policy methods, and quantitative public policy analysis—directly translates research expertise into graduate education for programs in International Economic Relations, Environmental Sustainability, and Global Economics.

Maria Prandiniمشاهده پروفایل

استاد

• Distributed Optimization
• Stochastic Hybrid Systems
• Randomized Methods for Systems and Control
• +۳ مورد دیگر

Maria Prandini is a Full Professor at the Politecnico di Milano , where she chairs the Automation and Control Engineering Program within the Department of Electronics, Information, and Bioingegneria. With a PhD in Information Technology from the University of Brescia (1998), she conducted postdoctoral research at UC Berkeley (1998-2000) and held visiting positions at Delft University, Cambridge, and ETH Zurich. Research Interests: Her work spans Distributed and Stochastic Optimization Stochastic Hybrid Systems Randomized Methods for Control Air Traffic and Energy Management Identification Theory Recent Article Trends: Her publications focus on cyber-physical systems, multi-agent optimization, unmanned aircraft control, and computational geometry methods, with a strong emphasis on real-world applications in energy and transportation. Scientific Awards: IEEE CSS Distinguished Member (2018) IEEE Fellow (2019) Editorial & Conference Roles: She serves on editorial boards of Automatica , IEEE Transactions on Network Systems , and Cyber Physical Systems , and has chaired major conferences like IEEE CDC and IFAC World Congress. Teaching: Courses include Hybrid Systems, Nonlinear Control, and courses at Lund University, University of Brescia, and Politecnico di Milano.

Enzo Tartaglioneمشاهده پروفایل

دانشیار

• Deep Learning
• Model Compression
• Pruning
• +۶ مورد دیگر

Enzo Tartaglione serves as Associate Professor at Télécom Paris, Institut Polytechnique de Paris, holding a Hi!Paris chair and contributing as Associate Editor for IEEE Transactions on Neural Networks and Learning Systems. His academic journey spans multiple institutions across Europe and the US, reflecting a strong interdisciplinary foundation. Educational milestones include: MS in Electronic Engineering, Politecnico di Torino (2015, cum laude) MS in Electrical and Computer Engineering, University of Illinois at Chicago (2015, magna cum laude) MS in Electronics, Politecnico di Milano (2016, cum laude) PhD in Physics, Politecnico di Torino (2019, cum laude), thesis: 'From Statistical Physics to Algorithms in Deep Neural Systems' His research centers on efficient deep learning , with pioneering work in model compression, neural pruning, and debiasing techniques. He actively develops methods for privacy-aware learning and green AI, targeting real-world deployment constraints in computer vision and medical imaging applications. His approach bridges theoretical physics with practical AI optimization. Recent publications (2024-2025) demonstrate consistent focus on computational efficiency, with 60% of works addressing model compression for vision tasks, 25% on bias mitigation, and emerging contributions in privacy preservation. Key venues include ICCV, CVPR, and IEEE Transactions, reflecting strong industry-academia impact. Scientific recognition includes: Finalist for Multimedia Rising Star Award (2025) He mentors 10 active PhD candidates across compression, debiasing, and on-device learning domains, having previously guided 3 PhD graduates and 17+ Master's researchers. Research funding includes the Hi!Paris GIFFAI project (2025) for frugal AI and ANR's BANERA initiative (2024) on bias-aware architecture search. His group operates within Télécom Paris' joint laboratory, driving the Frugal AI initiative through collaborations with ELLIS Society partners and industry stakeholders focused on sustainable deep learning deployment.

Joseph Orioloمشاهده پروفایل

استاد

• Control Systems
• Robotics
• Humanoid Robots
• +۷ مورد دیگر

Joseph Oriolo is a Full Professor of Automatic Control and Robotics at the Department of Computer, Control and Management Engineering (DIAG) at Sapienza University of Rome, where he also serves as the director of the DIAG Robotics Lab. He received his Ph.D. in Control Engineering from Sapienza University of Rome in 1992 and joined the DIAG in 1994. As an IEEE Fellow, he has made significant contributions to the field of robotics and control systems. His research spans multiple areas within robotics and control engineering, with particular focus on humanoid robots , mobile robots , UAVs , visual motion control , multi-robot systems , and sensor-based navigation . His work bridges theoretical control systems with practical robotics applications, emphasizing motion planning, learning control, and kinematically redundant robots. His research has resulted in over 230 publications in international journals and conferences, as well as two books. An analysis of his recent publications (2022-2025) reveals a strong emphasis on advanced control techniques for humanoid and mobile robots, particularly Model Predictive Control (MPC) applications for gait generation, navigation, and manipulation. His work increasingly integrates vision-based approaches for safe human-robot interaction and navigation in complex environments, with a growing focus on real-world applications including crowd navigation and cooperative robotics. Best Paper Award at the 17th International Workshop on Human-Friendly Robotics (HFR 2024) IEEE Robotics and Automation Magazine Best Paper Award for 2020 IEEE Fellow Professor Oriolo has served in significant editorial roles including Associate Editor (2001-2005) and Senior Editor (2009-2014) of the IEEE Transactions on Robotics. He has been actively involved in major robotics conferences, serving as Organization Chair for the 2007 IEEE International Conference on Robotics and Automation in Rome and on the Program Committees of numerous international conferences including ICRA, IROS, and RSS. He currently teaches courses on Control Systems and Autonomous and Mobile Robotics at Sapienza University of Rome. As director of the DIAG Robotics Lab, he leads research efforts in humanoid robotics, mobile manipulation, and autonomous navigation. The lab focuses on developing control frameworks that enable robots to operate effectively in complex, dynamic environments, with applications ranging from industrial automation to human-robot collaboration.

Marco Gaiottiمشاهده پروفایل

دانشیار

• Naval Structural Engineering
• Composite Materials in Marine Applications
• Underwater Explosion Effects
• +۳ مورد دیگر

Marco Gaiotti is an Associate Professor in the Department of Naval, Electrical, Electronic and Telecommunications Engineering at the University of Genoa, Italy. He serves as Coordinator of the Study Program for Naval Engineering and Yacht Design, teaching core courses including Naval Construction and Yacht Construction Technologies for both undergraduate and graduate programs. His research focuses on naval structural integrity under extreme conditions, with expertise in ultimate strength analysis of ship structures, composite material applications, underwater explosion effects, and buckling behavior of stiffened panels. He employs integrated experimental and numerical methodologies to advance structural safety and design efficiency in marine engineering. Analysis of his 2022-2025 publications reveals consistent emphasis on structural response to underwater explosions, cyclic loading effects, and composite material behavior, demonstrating methodological rigor through experimental validation and advanced numerical modeling across naval applications. No information on scientific awards, student supervision, research grants, or laboratory facilities was found in the provided sources.

• Microeconometrics
• Social Interactions
• Network Econometrics
• +۴ مورد دیگر

Tiziano Arduini serves as an Associate Professor of Econometrics in the Department of Economics and Finance (DEF) at Tor Vergata University of Rome, holding position within the ECONOMETRICS [SECS-P/05] sector. He teaches graduate courses including 'Causal Inference' and 'Quantitative Methods for Economics' for Master's Degree programs, maintaining an active research profile with institutional contact through tiziano.arduini@uniroma2.it and Twitter @ardui1. His research centers on microeconometrics with specialized focus on social interaction effects in economic outcomes, particularly examining how network structures influence health behaviors like eating disorders. Methodologically, he develops advanced techniques for causal inference under interference, network identification with heterogeneous interactions, and partial identification frameworks for treatment response. His work bridges theoretical econometrics with empirical applications in health economics, residential choice, and crisis modeling. Analysis of his 2019-2024 publications reveals dominant themes in network econometrics and interference-aware causal methods, including regression discontinuity designs under spillovers and complementarity/substitutability frameworks. Key applications span health risk behaviors (eating disorders, substance use), residential mobility decisions, and financial crisis dynamics, consistently addressing identification challenges in peer effect estimation. Scientific Awards: No awards mentioned in source materials. Advising and Grants: Source texts provide no information regarding student supervision, grant funding, or research projects. Research Infrastructure: No dedicated laboratories, research centers, or collaborative teams are specified in available documentation.

• Machine Learning
• Non-parametric Methods
• Applied Statistics
• +۳ مورد دیگر

Simone Borra is an Associate Professor at the University of Rome Tor Vergata, specializing in Statistics (SECS-S/01). He teaches courses in Big Data Analytics, Business Analytics, and Statistical Methods for Management at both bachelor's and master's levels. His research focuses on machine learning, non-parametric methods, and applied statistics, with applications in public administration evaluation, environmental science, and management consulting. Current courses: BIG DATA ANALYTICS, BUSINESS ANALYTICS, METODI STATISTICI PER IL MANAGEMENT Office hours: Thursdays 14:00-15:30 in Room P3 SB5 Contact: borra@economia.uniroma2.it His research interests include statistical methodologies for economic and social sciences, data mining, and the application of neural networks. He has published extensively on topics such as credit scoring models, survey methodology, and remote sensing for environmental monitoring. Recent work includes analyses of solar power plant detection using Sentinel data and studies on management consulting trends in Italy. Notable contributions span academic publications in computational statistics, multilevel modeling, and the evaluation of public administration contracts. His work bridges theoretical statistical methods with practical applications in business, environmental science, and public policy.

• Financial Econometrics
• Market Microstructure
• Nonlinear Filtering
• +۷ مورد دیگر

Giuseppe Buccheri serves as an Associate Professor of Econometrics (13/ECON-05) in the Department of Economics at the University of Verona since 2024. Previously, he held positions as senior assistant professor (RTDB) at the same department and junior assistant professor (RTDA) at the Department of Economics and Finance of University of Rome Tor Vergata. His academic appointments include membership on the Faculty Board of PhD in Economics and Finance, Collegio didattico di Economics and Data Analysis, Research Commission, and Economics Department Council. His educational background features a PhD in Financial Mathematics from Scuola Normale Superiore, an MSc in Finance from Bocconi University, and an MSc in Theoretical Physics from the University of Catania. This interdisciplinary foundation supports his research at the intersection of financial theory, statistical methods, and economic applications. Dr. Buccheri's research focuses on advanced econometric techniques for financial markets, particularly in Financial Econometrics, Market Microstructure, Nonlinear Filtering, and Financial Economics. His work addresses critical challenges in time-series analysis, model validation, volatility estimation, and portfolio optimization. The JEL classifications of his research span C32 (Time-Series Models), C52 (Model Evaluation), C58 (Financial Econometrics), and G11 (Portfolio Choice). His recent publications demonstrate a strong trend toward developing sophisticated statistical methods for high-frequency financial data analysis, with particular emphasis on score-driven models, realized volatility/covariance estimation, and handling market microstructure effects. These contributions advance the field by addressing measurement errors, asynchronous trading, illiquidity effects, and model identification challenges in modern financial markets. As an educator, Dr. Buccheri teaches Financial Econometrics, Quantitative Methods for Business and Economics, and Time Series and Forecasting across multiple graduate programs including Master's degrees in Banking and Finance and Economics and Data Analysis, as well as PhD courses in Financial Time Series. He serves on various academic committees related to research, teaching, and PhD program governance. His research activities connect with several institutional resources including CIDE (Centro Interuniversitario di Econometria) and the broader econometric research community at the University of Verona. His work contributes significantly to the department's research profile in quantitative methods for economics and finance.

• Multivariate Time Series Analysis
• Non-Parametric Statistics
• Financial Networks
• +۵ مورد دیگر

Lorenzo Frattarolo is a Tenure-track Assistant Professor at the Department of Economics of the University of Verona since 2023. His academic journey includes positions as a researcher at the Joint Research Center of The European Commission in the Economy and Finance unit, and as a postdoctoral researcher at Ca' Foscari University of Venice and Goethe University of Frankfurt. Dr. Frattarolo holds a joint PhD in Applied Mathematics/Economics from Paris 1 and Ca' Foscari, and a MSc in Theoretical Physics from the University of Rome La Sapienza. His academic credentials reflect a strong quantitative background that informs his research approach. His research focuses on advanced statistical and econometric methodologies with applications in finance and economics. Key areas include Multivariate Time Series Analysis, Non-Parametric Statistics, Financial Networks, and Forecasting. His work bridges theoretical statistical development with practical financial and economic applications, particularly in risk modeling and economic forecasting. Frattarolo's publications span top journals in econometrics and statistics, demonstrating expertise in copula methods, financial network analysis, and economic forecasting techniques. His recent work has addressed timely issues including pandemic-related economic analysis, climate risk, and European financial markets. Econometrics Statistical Methods Financial Networks Time Series Analysis Forecasting Within the Department of Economics at the University of Verona, Frattarolo contributes to various academic committees including the Economics Department Council and teaches courses across multiple degree programs, including Econometrics, Statistical and Econometric Analysis, and Machine Learning for Economics.

• Robust Statistics
• Bias Reduction Methods
• Estimation Theory
• +۵ مورد دیگر

Nicola Lunardon is an Associate Professor of Statistics at Ca' Foscari University of Venice. He holds a PhD in Statistics from the University of Padua and has held academic positions at the University of Milan-Bicocca, University of Trieste, and others. His research focuses on robust statistics, bias reduction methods, pseudo-likelihoods, and asymptotic theory. He has contributed to advancements in estimation functions and computational statistical methodologies. Current Affiliation: Department of Environmental Sciences, Computer Science and Statistics Previous Roles: Associate Professor at University of Milan-Bicocca (2019–2023), Research Fellowships at Padua and Trieste Universities (2012–2016) Research Interests: Lunardon's work emphasizes improving inferential procedures through robust statistical techniques. He has developed methods to address bias in estimating functions, tackle incidental parameters, and enhance computational efficiency. His Bayesian non-parametric approaches have been applied to molecular systems analysis. Publications span methodological contributions in top journals like Biometrika , Journal of the Royal Statistical Society , and Biometrics . Themes include global sensitivity analysis, longitudinal data modeling, and small-sample GEE estimation. Notable Software: Co-developed the ROSE package for imbalanced learning in R

Paolo Carmelo COZZUCOLIمشاهده پروفایل

دانشیار

• Statistics
• Statistical Quality Control
• Multivariate Statistical Processes
• +۳ مورد دیگر

Paolo Carmelo COZZUCOLI is an Associate Professor of Statistics (scientific-disciplinary sector SECS-S/01) at the Department of Economics, Statistics and Finance "Giovanni Anania" at the University of Calabria, where he has been in service since December 2006. Previously, he worked as a Statistics Researcher at the Faculty of Economics and Political Sciences of the University of Calabria from June 1992 to December 2006. Professor Cozzucoli's research focuses on statistical methodologies with particular emphasis on multivariate statistical processes, Bayesian statistics, and applications in quality control. His work spans various domains including social media analysis, environmental sustainability, financial forecasting, and chemical engineering. He has developed innovative approaches for hate speech detection, service quality assessment, and statistical process monitoring. His recent publications demonstrate a consistent focus on multivariate analysis techniques applied across diverse fields. The research shows a progression from fundamental statistical methodology development toward increasingly applied interdisciplinary work, with strong emphasis on practical implementation of statistical models in real-world settings. His work frequently employs Bayesian approaches, permutation tests, and multivariate process control methods. Professor Cozzucoli teaches courses including "Statistics for decisions," "Statistica ed elementi di inferenza," and "Deep learning Techniques and Neural Networks" for programs in Public Administration Sciences, Economics, and Data Science for Business Analytics. He is an active member of the "Statistica & Demografia" research group, which focuses on developing new statistical and demographic methodologies for data collection, analysis, description, and interpretation. Within this group, his specific interests include: multivariate statistical process control, Bayesian networks, sampling theory, and applications in quality management.