Paola Lecca is an Assistant Professor at the Free University of Bozen-Bolzano's Faculty of Engineering, specializing in theoretical and applied research on graph theory, dynamical networks, control theory, and causal inference. She is a Senior Professional Member of the Association for Computing Machinery and leads projects at the Smart Data Factory laboratory, focusing on technology transfer to industry. Her research integrates mathematical methods for complex systems in biological contexts, including systems biology, biophysics, and biochemistry. She develops computational approaches for network dynamics, simulation, and analysis, aiming to understand emergent properties in multi-agent systems. Courses taught include Mathematics and Statistics for Data Science and Preparatory Mathematics. She actively contributes to conferences and editorial boards, including Frontiers in Bioinformatics and Big Data Analysis for Medical Sciences.
Antonina Pirrotta is Full Professor at University of Palermo, serving as Director of the PhD School (since 2023) and CIDiS Research Center (since 2021). Her research in structural dynamics includes vibration control systems and probabilistic methods. Honors include the EASD Senior Research Prize (2020), EMI Fellowship (2020), and International Excellence Fellowship at KIT (2021). Innovations include optimized dampers for seismic and wind load mitigation. Research integrates analytical stochastic methods with experimental dynamics. Recent publications advance fractional calculus applications in random vibration theory and control device optimization. Editorial roles include Associate Editor for Meccanica and Journal of Engineering Mechanics .
Federico Marini is a Full Professor at the Department of Chemistry, University of Rome La Sapienza. He holds editorial roles including Editor-in-Chief of *Chemometrics and Intelligent Laboratory Systems* and membership in multiple journal boards. His research focuses on chemometrics, particularly method development and application in food chemistry, metabolomics, and multi-block data analysis. He has authored over 300 publications and edited books like *Chemometrics in Food Chemistry* (Elsevier 2013). Education: PhD in Analytical Chemistry (University of Rome La Sapienza, 2004) with Marie Curie Fellowship (2000–2004). Postdoctoral roles included visiting positions at universities in Copenhagen, Stellenbosch, and Lille. Research interests span advanced chemometric methods for food authentication, omics data processing, and non-linear modeling. Notable contributions include SO-PLS(-LDA) algorithms and multi-block fusion strategies. He coordinates the Chemometrics Task Group of DAC-EuCheMS and serves as Vice President of the Italian Society of NIR Spectroscopy. Awards include the 2006 Young Researcher Award (Italian Chemical Society) and 2012 Chemometrics Award. His work bridges analytical chemistry with data science, addressing real-world problems in agriculture, food safety, and biomedicine through innovative spectroscopic and statistical techniques.
Giovanna Maria Dimitri is a tenure-track Assistant Professor in Artificial Intelligence at the Università degli Studi di Milano (Statale), with strong affiliations at the University of Siena (DIISM) and the University of Cambridge. She conducts research in deep learning, machine learning, and AI applications across domains such as computer vision, bioinformatics, climate modeling, and healthcare. She also lectures in Business Intelligence at the University of Siena and serves as a Guest Lecturer in Data Science at the University of Cambridge's Institute of Continuing Education. PhD in Artificial Intelligence, University of Cambridge MPhil in Advanced Computer Science (Distinction), University of Cambridge Master's and Bachelor's in Computer and Automation Engineering (110/110 cum laude), University of Siena Her research spans foundational AI models and their applications in diverse fields including neuroscience, environmental science, and medical diagnostics. She develops methodologies in deep learning, graph neural networks, and multimodal data analysis, with a growing interest in sustainable AI and ethical implications of machine learning systems. Her recent publications reflect a strong trend in applying AI to real-world challenges: from detecting synthetic images and analyzing brain signals to modeling climate impacts and assessing sustainable development goals. Her work bridges theoretical innovation with practical implementation across healthcare, environmental monitoring, and digital humanities. Scientific Awards and Editorial Roles: Ai-Net Fellows Scholarship (DAAD, 2023) Associate Editor, Neurocomputing (Elsevier) Associate Editor, IEEE Transactions on Technology and Society (since May 2024) Giovanna has extensive experience in teaching, supervising, and science communication. She has delivered seminars at top institutions like the University of Cambridge and has been featured in Italian media for her AI expertise. She mentors students and collaborates internationally, including with Prof. Gemma Roig at the DAAD-sponsored Ai-Net program. She is actively involved in academic service, conference organizing, and public engagement, contributing to both technical and societal aspects of AI advancement. She is a life member of Clare Hall College, University of Cambridge, and maintains active research collaborations across Europe. Her lab and research group focus on developing robust, interpretable, and sustainable AI systems, with ongoing projects in medical AI, climate informatics, and ethical machine learning.
Daniela Piazzese is an Associate Professor at the University of Palermo within the School of Basic and Applied Sciences . Her academic profile focuses on analytical and environmental chemistry with extensive research in marine systems, food chemistry, and rare earth element behavior. Office hours: Wednesday 11:00-13:00 at via Archirafi 26 Contact: +3909123897955 Email: daniela.piazzese@unipa.it Research interests span: Environmental chemistry of marine and coastal systems Food chemistry and preservation techniques Rare earth element geochemistry Biopolymer interactions and trace metal speciation Bioremediation and waste valorization Advanced analytical methodologies Recent publications highlight her expertise in bio-plastic detection, marine pollution biomarkers, and sustainable food processing. She has consistently published on topics ranging from: Biopolymer-metal interactions Coastal water quality analysis Food product development Trace element fractionation Environmental impact studies Sustainable resource utilization
Francesco Morandin is a Researcher (Assistant Professor) in Probability and Statistics at the Department of Mathematical, Physical and Computer Sciences, University of Parma. His research spans theoretical and applied mathematics, focusing on nonlinear PDEs, SPDEs, and stochastic processes like branching and generalized urn models, with applications in medical data analysis, industrial statistics, and computational biology. Education: Mathematics degree from Scuola Normale Superiore di Pisa (1998), PhD program (1999-2000). Collaborations: University of Pisa (microarray analysis), Avio S.p.A. (mechanical failure detection), Parma burial office (cremation dynamics), Heinz-Plasmon (quality control). His recent work in machine learning includes SwitchPath activation functions for exploration enhancement, GloNets for global connectivity, and reinforcement learning applications in healthcare and game theory. He has supervised 4 bachelor's, 13 master's, and co-supervised 15 theses, with a focus on industrial and medical statistics education. His publications integrate probability theory with applications in cancer therapy prediction, single-cell RNA analysis, and stochastic modeling of turbulence.
Francesco Zammori is an Associate Professor at the Department of Systems Engineering and Industrial Technologies (DISTI) , University of Parma. His career spans academic research, teaching, and industry collaboration, focusing on lean manufacturing, supply chain innovation, and simulation modeling. Scientific High School Diploma, 100/100, Leonardo da Vinci Scientific High School (2000) Bachelor's in Management Engineering (logistics and production), 110/110 cum laude , University of Pisa (2002) Master's in Management Engineering (logistics and production), 110/110 cum laude , University of Pisa (2004) PhD in Mechanical Engineering (plants and technologies), University of Pisa (2009) Zammori's research centers on lean manufacturing , where he develops techniques for identifying inefficiencies using Value Stream Mapping (VSM) and Overall Equipment Effectiveness (OEE). He specializes in Vendor Managed Inventory (VMI) modeling, discrete-event simulation of complex systems with multivariate statistical analysis, and solving NP-hard problems in operations management using mathematical programming and heuristics. His work also explores process mapping with IDEF/BPMN methods and IT system prototyping for transactional data. Recent publications highlight trends in supply chain circularity (2024), automated storage systems (2023), and educational gamification (2023). He applies Monte Carlo simulation , Markov chains , and life cycle analysis to industrial challenges. Scientific Contributions: Editor-in-Chief (European area), Decision Science Letters (Growing Science) Organizer & Chair, IESM2015 special session on 'Lean in Make To Order Firms' Member, AIIE2015 international conference scientific committee Zammori has taught 40+ corporate training modules for Tuscan companies and delivered university courses on ERP systems , business process management , and management information systems across multiple Italian universities since 2005. His funded projects include RFID tracking systems for paper coils and plasma bags, extended enterprise logistics frameworks, and lean process reengineering for manufacturing firms.
Mattia Laurini is a Fixed-term Researcher at the Department of Engineering and Architecture , University of Parma. His academic work focuses on control engineering, biomedical applications, and optimization algorithms, with teaching assignments in Computer Engineering for Master's Degree programs since 2023. Research Interests: Control systems for anesthesia Pharmacokinetics/Pharmacodynamics (PK/PD) modeling Traffic flow estimation Dynamic programming applications Vehicle motion optimization Medical device automation Research Trends: Recent publications (2025) demonstrate interdisciplinary work merging control theory with biomedical applications, particularly in automating anesthesia delivery. Key methodologies include Branch and Bound optimization, dynamic programming for traffic systems, and hybrid control paradigms combining MPC with PID strategies. Research spans both theoretical advances (e.g., acceleration-constrained shortest path algorithms) and clinical applications (e.g., propofol/remifentanil co-administration optimization). Teaching: Laboratory of Control Engineering (2023-2025) Multivariable Systems (2023-2025) Reference teacher for Computer Engineering program Contact: mattia.laurini@unipr.it | Office: Building 1, Parco Area delle Scienze, 181/A 43124 Parma | Phone: 906183
Biagio Simonetti is an Associate Professor in Statistics (SECS-S/01) at the Department of Law, Economics, Management and Quantitative Methods (DEMM) of the University of Sannio, Italy. He has been serving in this role since 2015, following a progression from Researcher since 2006. His academic journey began with a PhD in Computational Statistics from the University of Naples Federico II in 2003. His research interests center on applied statistics , particularly in multivariate analysis , correspondence analysis , fuzzy systems , cluster analysis , and ordinal data modeling . His work extends into interdisciplinary domains such as healthcare economics, customer satisfaction, tourism, and financial markets. He has applied statistical techniques to evaluate obesity’s impact on healthcare costs, model doctor-patient communication, and analyze cultural perceptions of food. The trend in his recent publications reflects a strong focus on fuzzy logic , big data applications , and robust statistical methods in socio-economic and health contexts. His work often involves international collaboration, particularly with researchers in Spain, Australia, India, and Turkey. Certificate of Appreciation for collaboration with Hanoi University (Vietnam), 2014 Simonetti has participated in numerous research projects, including European TEMPUS and Jean Monnet programs, and has coordinated EU-funded research on grapevine virology and applied statistics education. He has served on the editorial boards of journals such as the Journal of Reliability and Statistical Studies and Electronic Journal of Applied Statistical Analysis . He has also been actively involved in organizing and serving on scientific committees for international conferences like DYSES, MTISD, and Agrostat. He has collaborated extensively with institutions abroad, including the University of Moncton (Canada), University of Western Sydney (Australia), and Universitat Rovira i Virgili (Spain), and has held research visits in Denmark and Barbados. His academic service includes participation in PhD programs and doctoral examination committees, particularly in biostatistics and socio-economic systems.
Matilde Bini is a Professor of Economic Statistics (SECS-S/03) and Director of the Department of Human Sciences at the University of European Rome (UER). She holds a PhD in Applied Statistics from the University of Florence (1995) and has taught Corporate Statistics and Statistical Methods for Business Decisions at UER since 2009. Visiting positions: University of Florida (USA), IMT Lucca, University of Cordova (Spain) Active in national research groups funded by the Italian Ministry of Research Editorial roles: Associate Editor for Statistical Methods and Applications and Italian Journal of Applied Statistics Her research focuses on generalized linear mixed models, structural equation models, multivariate methods, and longitudinal models. She specializes in robust diagnostic analysis for data quality and anomaly detection, with applications in labor markets, firm productivity, entrepreneurship, and higher education evaluation. Recent publications examine zero-inflated beta regression for university career prediction, multilevel modeling of educational effectiveness, and robust analysis of high-tech firm competitiveness. Her work frequently appears in peer-reviewed international statistics journals. Professional affiliations include the Italian Statistical Society, International Statistical Institute, American Statistical Association, Royal Statistical Society, and the International Society for Business and Industrial Statistics.
Maria Carannante is a Lecturer at the European University of Rome's Department of Human Science, specializing in Mathematical Methods for Economics, Actuarial Sciences, and Finance (STAT-04). She maintains active membership in The Association for Mathematics Applied to Social and Economic Sciences (AMASES). Her research program centers on developing advanced quantitative methods for real-world applications. Primary domains include: Machine learning implementations for longitudinal data analysis Stochastic modeling of mortality and longevity risks Climate risk quantification in insurance contexts Multidimensional analysis of financial time series Big data processing frameworks for economic systems Publication analysis reveals consistent focus on actuarial innovations, with recent emphasis on: Machine learning applications in insurance risk transfer Pandemic mortality modeling and insurance implications ESG integration in actuarial pricing Advanced dependency modeling using copulas Longevity risk solutions for pension systems
Franco Pellerey is a Full Professor at the Department of Mathematical Sciences (DISMA) of the Polytechnic University of Turin. He serves as Coordinator of the College of Mathematical Engineering and is actively involved in teaching and research coordination activities. Co-organizer of the International School on Stochastic Comparisons (2004) Program Chair for the 14th International Conference on Ordered Statistical Data (2022) Scientific Coordinator for multiple national research projects (BRIC-2024, PRIN) Research Interests : Stochastic orders and their applications in risk theory Dependence notions and positive dependence concepts Reliability theory and actuarial sciences Stochastic processes in engineering contexts Applied statistics for technical systems Scientific Leadership : BRIC-2024 Acoustics Research (2025-2027) Supermodularity in Economic Theory (2002-2004) Continuous Financial Market Models (2001-2003) International Engagements : Full Professor at Turin Polytechnic University in Tashkent (2018-2021) Full Professor at ESCP Europe (2016-2018)
Claudio Agostinelli is a Full Professor at the Department of Mathematics, University of Trento. He teaches Advanced Statistical Methods Probability and Statistics Statistics of Stochastic Processes across various degree programs including Mathematics (LM), Computer Science (L), and Data Science (LM). His research focuses on statistical methodologies for data analysis, including Robust Statistics Computational Statistics Environmental Statistics Statistical Learning Multivariate Analysis Monte Carlo Methods Optimization Techniques
Edoardo Fadda is a Fixed-term tenure-track Assistant Professor at the Department of Mathematical Sciences (DISMA), Politecnico di Torino . He serves as a member of the College of Mathematical Engineering and College of Electronic, Telecommunications and Physics Engineering . Specializes in Operations Research and Mathematical Programming Active in stochastic optimization , reinforcement learning , and control applications Teaching roles include Optimization Methods for Control Applications and Stochastic Programming courses His research spans supply chain optimization , logistics , and AI-integrated decision systems , focusing on uncertainty modeling and multi-stage stochastic programming. He leads the Development of Decision Support Systems and the SUPERSONIC project for ecological logistics, alongside commercial consulting for RIDIX SPA through Fondimpresa contracts. Notable collaborations include Paolo Brandimarte and Francesca Maggioni . Edoardo supervises PhD candidates Alessia De Crescenzo (39th cycle) and Lorenzo Mazza (40th cycle). His publications emphasize stochastic customer behavior , perishable product policies , and kernel-based system identification , with applications in aerospace, smart cities, and industrial manufacturing.
Gianfranco Genta serves as an Associate Professor in the Department of Management and Production Engineering (DIGEP) at Politecnico di Torino. His academic career spans industrial metrology, quality engineering, and design of experiments with significant contributions to manufacturing technologies and systems. He actively participates in the College of Chemical and Materials Engineering, College of Management and Production Engineering, and College of Mechanical, Aerospace and Automotive Engineering. His research focuses on industrial metrology, quality engineering, design of industrial experiments, and technological surface characterization. Genta's work addresses critical challenges in manufacturing precision and quality control, with particular emphasis on measurement systems, statistical process control, and surface characterization techniques. His research bridges industrial engineering principles with advanced metrological science to develop innovative solutions for manufacturing quality assurance. Genta's recent publications (2024-2025) demonstrate a strong trajectory toward digital transformation in manufacturing quality systems. His work increasingly integrates human-robot collaboration, digital traceability frameworks, and advanced metrology with machine learning applications. Key research themes include quality control in food processing, electronic component assembly, and advanced materials characterization, with notable emphasis on sustainable manufacturing practices aligned with UN SDG 9 and 12. As a research leader, Genta serves as Scientific Responsible for the TracInd BVK-H project (2023-2026) on indentation measurements traceability and contributes to the DI-VISION project (2024-2027) on machine vision systems. He has supervised multiple PhD students including Alberto Piovano (focusing on sustainable agri-food processes), Stefano Puttero (examining collaborative robots in quality control), and Jasurkhuja Kholkhujaev (specializing in geometrical and mechanical characterization of metallic components). Genta's teaching portfolio includes Industrial Experiment Planning, Advanced Techniques for Quality Measurement, and Quality Control Techniques in Materials Engineering across various degree programs. His pedagogical approach emphasizes practical applications of statistical methods and metrological principles in industrial settings, preparing students for careers at the intersection of engineering and quality management.
