Domenico Vitale is a Researcher at the Department of Methods and Models for Economy, Territory, and Finance within Sapienza University of Rome . His work spans environmental statistics, economic modeling, and data science. He teaches courses including Time Series Analysis (6 CFU), Introduction to Spatial Data (3 CFU), and Basic Statistics for Business Sciences. Office hours are held in Room 420, 4th Floor, Faculty of Economics. Research Focus : Eddy covariance data processing and quality control Statistical modeling of environmental and economic phenomena Machine learning applications for survey data and flux measurements Time series alignment and prewhitening techniques Recent Publications explore topics like quasi-formal employment modeling, carbon flux scaling frameworks, and pandemic dynamics. His work integrates interdisciplinary methodologies from climate science to econometrics. Labs and Collaboration : Active in DidaLab , Spinelli Lab , and ICOS Ecosystem Stations , focusing on standardized environmental data processing.
Andrea Curioni is a Full Professor at the University of Padova , affiliated with the Department of Agronomy, Food and Animal Sciences (DAFNAE). His research focuses on enology, food chemistry, and sustainable processing of wine by-products, particularly wine lees and yeast-derived compounds. Academic Field: AGR/15 - Food Science Key research areas include: Antioxidant properties and bioactive peptides from yeast Mannoprotein extraction and wine stabilization Colloid formation and protein-phenolic interactions in red wines Valorization of winery waste through green chemistry Recent publications highlight his work on sustainable extraction methods, sensory interactions in wine, and molecular characterization of grape and wine compounds. His research employs advanced analytical techniques like asymmetrical flow field-flow fractionation and FTIR spectroscopy for wine composition analysis. While no specific awards are documented in this dataset, his extensive publication record demonstrates leadership in food and wine chemistry. He investigates multisensory interactions, allergenicity of grape products, and innovative applications of plant proteins in food systems.
Prof. Federico Solari is a fixed-term researcher at the Department of Industrial Systems and Technologies Engineering (DISTI) at the University of Parma. He teaches courses including Food Industry Systems (Second Cycle Degree in Engineering for the Food Industry) and Mechanical Plant and Equipment (First Cycle Degree in Mechanical Engineering). Academic Appointments: Second Cycle Degree (2021–2025), First Cycle Degree (2019–2023) Research Focus: IoT applications in agriculture, sustainable logistics, computer vision for food quality, and inventory management for perishable goods His recent publications address trends in innovative teaching methodologies, smart agricultural systems, post-COVID supply chain sustainability, and optimization of reordering policies using advanced statistical techniques. He collaborates with researchers like Eleonora Bottani and Giovanni Romagnoli on food industry systems.
Paolo Tilli is a Full Professor in the Department of Mathematical Sciences "G. L. Lagrange" (DISMA) at Politecnico di Torino, Italy. He is actively involved in research, teaching, and doctoral supervision, with a strong presence in mathematical analysis and its applications. His research focuses on calculus of variations , partial differential equations , shape optimization , and phase space analysis with applications to quantum mechanics. He is a member of the Analysis and Quantum Theory research group at DISMA, and his work spans theoretical analysis of singular models, spectral theory, and nonlinear dynamics on networks and metric graphs. The recent publications of Paolo Tilli reveal a consistent and high-impact research trajectory in nonlinear PDEs , time-frequency analysis , and quantum graphs . His work frequently appears in top journals such as Inventiones Mathematicae and Advances in Mathematics , with a focus on Faber-Krahn inequalities, localization operators, and ground states in nonlinear Schrödinger equations. These contributions reflect deep analytical techniques and interdisciplinary relevance, particularly in mathematical physics and signal processing. He has supervised PhD students including Federico Riccardi and has been a long-standing member of doctoral college committees for the PhD programs in Mathematical Sciences at Politecnico di Torino and the University of Turin. His teaching includes core courses such as Metodi Variazionali e Applicazioni and Analisi Matematica II across various engineering and mathematics programs. His research groups include: Analysis and Quantum Theory Group (DISMA)
Enrico Bertuzzo is a Full Professor at Ca' Foscari University of Venice, affiliated with the Department of Environmental Sciences, Computer Science and Statistics. His research focuses on hydrological modeling, river network biogeochemistry, and epidemiology of waterborne diseases. He has held roles including Scientist at École Polytechnique Fédérale de Lausanne (2011–2016) and Visiting Assistant Professional Specialist at Princeton University (2007–2008). He earned a PhD in Civil & Environmental Engineering from the University of Padua in 2008. Teaching: Environmental Engineering, Hydrology, Fluid Mechanics Research: River network metabolism, urban expansion modeling, and infectious disease dynamics His research integrates hydrological processes with biogeochemical and epidemiological models, addressing topics like carbon dynamics in rivers, cholera transmission, and climate impacts on ecosystems. He contributes to projects such as the EU-funded CONSTRAIN and NewTechAqua initiatives. Publications emphasize river network biogeochemistry and carbon cycling, with recent work exploring O₂-CO₂ coupling and urban expansion drivers. He serves on editorial boards including Royal Society Open Science and Advances in Water Resources.
Paolo Falcarin is an Associate Professor at Ca' Foscari University of Venice, affiliated with the Department of Environmental Sciences, Computer Science and Statistics. His research focuses on cybersecurity, software engineering, and AI compliance, with notable contributions to software protection mechanisms, reverse engineering defenses, and cyber-physical systems. He actively participates in editorial roles for journals like Computers & Security and serves on program committees for IEEE/ACM conferences. Key Projects: ASPIRE (EU FP7), SERICS (PNRR), and Flexymob (Currant s.r.l.) Research Interests: Cybersecurity Knowledge Graphs, Runtime Security (Falco), AI Act Compliance, and Software Renewability His work bridges theoretical cybersecurity advancements with practical applications in distributed systems and IoT. Recent publications emphasize anomaly detection in large-scale systems and regulatory compliance frameworks for AI.
Giulia Ellena serves as a Research Fellow at the Interdepartmental Center for Mind/Brain Sciences (CIMEC) within the University of Trento, Italy, where her work bridges experimental neuroscience and cognitive psychology through advanced brain stimulation methodologies. Her research program centers on Neuroscience and Cognitive Science , with specialized expertise in Motor Control , Time Perception , and Brain Stimulation techniques. She employs transcranial magnetic stimulation (TMS) and statistical learning paradigms to investigate neural plasticity during proactive motor tasks and temporal processing, utilizing quantitative approaches to decode cognitive-motor interactions. Analysis of her recent publications reveals a cohesive research trajectory focused on non-invasive neuromodulation, particularly rTMS applications for enhancing motor learning and dissecting time perception mechanisms. Her work demonstrates strong interdisciplinary integration between psychological theory and neurophysiological measurement, with emphasis on statistical learning frameworks and causal brain-behavior relationships in human cognition. No scientific awards are documented in the available records. Current information indicates no formal student supervision or grant leadership activities have been publicly recorded at this time.
Paolo Solinas is an Associate Professor at the Department of Physics, University of Genoa. His research focuses on theoretical physics of fundamental interactions, quantum computing, and superconductivity. He teaches courses such as General Physics , Quantum Information Processing , and Fundamentals of Quantum Computing across multiple degree programs including Robotics Engineering and Computer Science. His research leverages mathematical methods to explore quantum systems, with specific emphasis on quantum information theory, superconducting devices, and thermodynamic phenomena in quantum regimes. Recent publications highlight collaborations in quantum measurement techniques and electric field control of superconductivity. Contact: Department of Physics, University of Genoa, Via Dodecaneso 33, 16146 Genoa, Room S709, Phone: +39 010 3536260.
Santa Di Cataldo is an Associate Professor at the Department of Control and Computer Engineering (DAUIN) of Politecnico di Torino. His research focuses on computer vision, pattern recognition, digital image processing, and medical image processing, with applications in industrial systems and AI for manufacturing. Scientific Branch: IINF-05/A - Information Processing Systems ERC Sectors: PE6_8 - Computer graphics, computer vision, multi media, computer games ERC Sectors: PE6_11 - Machine learning, statistical data processing His work includes developing AI-driven anomaly detection frameworks, physics-informed neural networks for additive manufacturing optimization, and neuro-symbolic approaches for Industry 4.0 applications. He supervises PhD students in Artificial Intelligence and Computer Engineering programs, collaborating on projects like BIG (Blue Is Green) and PNRR-Complementary Plan. Premio Donna Innovazione (2010) He leads courses such as Machine Learning in Applications and Applied AI and Machine Learning , while contributing to bioinformatics and robotics-related teaching. His research is supported by IAM@PoliTo and EDA groups, utilizing LADISPE laboratory facilities.
Bartolomeo Montrucchio is a Full Professor of Information Processing Systems (ING-INF/05) at the Department of Control and Computer Engineering (DAUIN) of the Polytechnic University of Turin. He is a member of the Interdepartmental Center Photonext - PoliTo Interdepartmental Center on Applied Photonics and serves as deputy director at the Interuniversity Center of Regional Interest for the Training of Secondary School Teachers (CIFIS) since July 2012. Additionally, he has held an adjunct professor position at the University of Illinois at Chicago during July 2008. Professor Montrucchio's research spans several cutting-edge areas with a primary focus on quantum computing, computer vision, and sensor networks. His work encompasses image processing, scientific visualization, parallel and distributed systems, and wireless sensor networks. He actively contributes to European research initiatives including the EQUO (European QUantum ecOsystems) project as Scientific Responsible. His research bridges theoretical computer science with practical applications across multiple industries. His publication record shows a strong trajectory toward quantum technologies, with numerous recent publications focusing on quantum machine learning, quantum algorithms for financial applications, and quantum applications in cybersecurity. His work demonstrates increasing emphasis on practical implementations of quantum computing in real-world scenarios, particularly in industrial settings and telecommunications. Best student paper award at BIOSIGNAL2002, conferred by EURASIP, Italy (2002) Associate Editor of IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2019-present) Professor Montrucchio actively supervises numerous PhD students working on quantum computing applications across various domains including finance, cybersecurity, traffic optimization, and industrial use cases. His teaching portfolio includes courses on Quantum Computing, Parallel and Distributed Computing, and Image Processing and Computer Vision across multiple degree programs including Computer Engineering, Biomedical Engineering, and Quantum Engineering. He leads multiple research projects funded by both competitive calls and commercial contracts, with a significant focus on quantum technologies since 2019. His patent portfolio includes several inventions related to tire manufacturing processes and visual rehabilitation for telemedicine.
Barbara Trivellato is an Associate Professor in the Department of Mathematical Sciences (DISMA) at the Polytechnic University of Turin. She serves as a member of the College of Mathematical Engineering, College of Electronic, Telecommunications and Physics Engineering, and as an invited member of the College of Computer, Film, and Mechatronics Engineering. Her research focuses on Exponential models , Stochastic differential equations , and Stochastic utility maximization . As part of the "Probability and Applications" research group, her work spans optimization problems in finance and mathematical statistics. Her expertise aligns with ERC sectors including application of mathematics in sciences, control theory, optimization, mathematical statistics, and probability. Dr. Trivellato's recent publications demonstrate a strong focus on financial mathematics and probability theory. Her work examines mean-variance optimization in insurance contexts, utility maximization using stochastic differential equations, properties of exponential statistical models, and applications to demographic modeling across journals in financial mathematics, applied mathematics, theoretical probability, and physics. Scientific Director for PRIN project "Stochastic methods for expected utility maximization" (2004-2006) Current PhD supervisor for Giulio Cuniberti (Mathematical Sciences, 39th cycle) She teaches Stochastic Processes for Mathematical Engineering and Mathematical Methods for Engineering across multiple engineering disciplines including Physics, Aerospace, Computer, Film and Media, and Management Engineering for academic years through 2025/26.
Mauro Gasparini is a Full Professor at the Department of Mathematical Sciences (DISMA) of Polytechnic University of Turin. He serves as Director of DISMA since 2019, Member of Academic Senate, and co-leader in the SmartData@PoliTO Big Data Laboratory. His career spans academia and industry, including roles at Purdue University (Assistant Professor 1992-1996) and Novartis (Senior Statistician 1996-1998). He has been Editor of Biometrical Journal (2012-2015) and maintains referee activities across international journals. PhD from University of Michigan (1992, Dirichlet process applications) Academic leadership: Department Director, Editorial boards, ISTAT Advisor Research spans Bayesian methodology with biomedical applications Maintains collaborations with Novartis, Chiesi, and research centers His research interests focus on Bayesian inference , Biostatistics , and Clinical trials methodology, particularly addressing issues in pharmaceutical development, genomic data analysis, and medical decision-making. Recent work includes vaccine efficacy modeling, optimal imaging timing for cancer diagnostics, and adaptive trial designs. Key publication trends show interdisciplinary applications in Statistics in Medicine , Biometrics , and Statistical Methods in Medical Research , with emphasis on biomedical data science, Bayesian adaptive methods, and clinical decision support systems. Scientific contributions include: Editor, Biometrical Journal (2012-2015) Advisor, Italian National Institute of Statistics (2020-2024) Leadership in multiple research projects (NODES, SORGENTE, IDEAS) As PhD advisor, he supervises students in: Shaoshi Tang (Clinical trial modeling) Saeed Sani (Biomedical data analysis) Marco Ratta (Genomic statistics) Luca Rondano (Bayesian methods) Vittorio Zampinetti (Tumor DNA sequencing) Fulvio Di Stefano (Evidence-based decision statistical methods) He leads research projects in pharmaceutical statistics, genomic surveillance, and spatial risk assessment frameworks, with recent emphasis on SARS-CoV-2 analysis and cancer progression modeling.
Paolo Oresta serves as an Associate Professor within the Department of Mechanics, Mathematics & Management at the Polytechnic University of Bari, Italy, with primary contact via paolo.oresta@poliba.it and departmental address at Via Orabona 4, 70125 Bari. His research program centers on fluid mechanics and thermal engineering, with core expertise in nanofluid thermal conduction, turbulent convection phenomena, energy recovery systems, and fluid machinery design. He investigates heat transfer enhancement mechanisms, multiphase flow dynamics, and thermal energy storage optimization through computational modeling and experimental validation. Analysis of his 15 most recent publications (2023-2017) reveals consistent focus on nanoscale heat transfer in fluid suspensions, 3D flow reconstruction techniques, and Industry 4.0 applications for industrial plants. His work bridges theoretical fluid dynamics with practical energy systems engineering, particularly in thermal storage and pressure recovery devices, demonstrating strong interdisciplinary integration across mechanical, thermal, and computational domains.
Anthony Cossari is a University Researcher in Statistics (SECS-S/01) at the Department of Economics, Statistics, and Finance "Giovanni Anania" (DESF) at the University of Calabria, where he has been employed since September 1, 2003. He holds a Laurea in Scienze Statistiche ed Attuariali from the University of Calabria (1995) with highest honors. Cossari is a member of the Italian Statistical Society (SIS) and the European Network for Business and Industrial Statistics (ENBIS). His research interests center on statistical experimental design methodologies: Screening designs for identifying significant factors in preliminary experimental phases Supersaturated designs for studying numerous factors with limited experimental runs Follow-up designs to enhance initial experimental analyses Robust designs for minimizing variability from environmental factors Cossari maintains active research collaborations across disciplines, particularly with medical researchers from the Catholic University of the Sacred Heart in Rome and mechanical engineering researchers from the University of Calabria. His publication record shows a transition from purely statistical experimental design research to increasingly collaborative medical research, especially in sepsis prognosis, alcoholic cardiomyopathy, and dental health in patients with alcohol use disorders. Recent publications (2021-2025) demonstrate strong interdisciplinary work while maintaining his core statistical expertise. His academic service includes membership on the Departmental Board (2004-2006) and the Scientific-Technical Committee of the Interdepartmental Library of Economic and Social Sciences "E. Tarantelli" (2007-present). He has served as thesis advisor for numerous undergraduate and graduate students across various statistical topics and was a member of the Doctoral Committee for the PhD program in "Economic History, Demography, Institutions and Society in Mediterranean Countries" (2007-2009).
Gioacchino Cafiero is an Associate Professor at the Department of Mechanical and Aerospace Engineering (DIMEAS), Polytechnic University of Turin. His research focuses on data-driven experimental fluid mechanics, particularly applying machine learning techniques like deep reinforcement learning and genetic algorithms to control turbulent flows and optimize fluidic actuators. As a member of the Fluid Dynamics research group, he leads projects such as GREENER (drag reduction via sinusoidal riblets) and WINDED (drone wind investigation), while also directing commercial research on friction stress measurement methodologies. Specializes in turbulent flow control and machine learning applications Teaches PhD courses on Machine Learning for Flow Control Supervises students in aerospace engineering programs Recent publications analyze jet turbulence with explainable AI, heat transfer fluctuations in channel flows, and riblet-induced drag reduction. His work bridges aerospace engineering and fluid dynamics, contributing to SDG goals 9 (Industry Innovation) and 13 (Climate Action). Scientific awards include the Learning to Teach (L2T) Open Badge from Politecnico di Torino.
