جستجوی استاد راهنمای دانشگاهی

• Batteries
• Biosourced polymers
• Design of experiments
• +۷ مورد دیگر

Federico Bella is Full Professor of Chemical Foundations of Technologies at Polytechnic University of Turin, leading research on post-Li batteries , electrochemical nitrogen reduction , and hybrid photovoltaics within the Electrochemistry Group. He serves as Member of the Interdepartmental Center Ec-L - Energy Center Lab and oversees multiple laboratories including the Testing Laboratory and Material synthesis units. Department: Department of Applied Science and Technology (DISAT) Scientific Sector: CHEM-06/A - Chemical Foundations of Technologies ERC Skills: Electrochemistry, Chemical Engineering, Intelligent Materials His research focuses on sustainable energy systems, including green ammonia production , polymer electrolytes , and next-generation batteries . He has led over 20 major research projects, including the ERC SuN2rise (€1.5M) redesigning ammonia production and GREEN2MOVE for sustainable potassium battery manufacturing. His work aligns with SDG 7 (Affordable Clean Energy) and SDG 9 (Industry Innovation). Scientific recognitions include the ENI Award (2016), USERN Prize (2021), and European Young Chemist Award (2016). He serves on editorial boards of ChemSusChem and ACS Sustainable Chemistry & Engineering , and has coordinated the Italian Chemical Society's Early-Career Division. PhD Students Supervised: Antonio Benigno, Andrea Muscatello, Lorenzo Tamboia Key Collaborations: Royal Society of Chemistry, EuCheMS, ENI He teaches advanced courses on Research Design , Battery Systems , and Scientific Publishing across Materials Science, Chemical Engineering, and Management programs.

• Biopolymers
• Natural fillers for polymers
• Polymer processing
• +۵ مورد دیگر

Alberto Frache is a Full Professor at the Department of Applied Science and Technology (DISAT) of Politecnico di Torino. He serves as Scientific Coordinator for numerous research projects and teaches courses on polymer technology, degradation, and recycling at the Master's program in Materials Engineering for Industry 4.0. Scientific Director for collaborations with hospitals and industry partners Member of scientific committees for Italian polymer associations Research Focus His research addresses: Development of biopolymers with natural fillers Polymer processing optimization for 3D printing Flame retardant systems and fire safety Recycling of automotive and packaging plastics Nanocomposite materials with graphene-based additives The 15 most recent publications demonstrate expertise in polymer recycling, nanocomposite processing, and fire-retardant material development with applications in: 3D printing Automotive components WEEE recycling Biodegradable materials Scientific Recognition Recipient of Polymers 2024 Best Paper Award Scientific coordinator for EU and regional projects Advisory roles for industrial innovation networks Academic Leadership Mentor for PhD students in Materials Science Principal Investigator for 20+ funded research projects Director of ALL-Polymer research team at DISAT Laboratory Facilities Oversees multiple specialized laboratories at DISAT including: Fire Testing Laboratory Plastic Processing Laboratory Polymeric Characterization Surface Treatments Chemical Synthesis

Marco Stefanucciمشاهده پروفایل

استادیار

• Statistical Methodology
• Functional Data Analysis
• Spectroscopy
• +۳ مورد دیگر

Marco Stefanucci is an Assistant Professor in Statistics at the Department of Economics and Finance, University of Rome Tor Vergata. Previously, he held positions at the University of Rome La Sapienza, University of Trieste, and served as a postdoctoral researcher at the University of Padova. He earned his PhD from the University of Rome La Sapienza under Professor Pierpaolo Brutti. His research focuses on statistical methodology, functional data analysis, and applications in spectroscopy, mortality trends, and neuroscience. Collaborations include work with Professors Mauro Bernardi, Pierpaolo Brutti, and Laura Sangalli, among others. Research interests include advanced statistical techniques for functional data, compositional data analysis, and their applications in diverse fields such as demography, chemistry, and medical imaging. His recent work emphasizes adaptive regression frameworks, sparse modeling, and classification of complex datasets. He has published extensively on topics like mortality trend analysis, spectroscopic data interpretation, and multimodal imaging methodologies. While no awards or grants are explicitly mentioned, his contributions to statistical theory and applied research are evident through his academic trajectory and collaborative projects. Teaching roles include lecturing on Quantitative Methods and Statistical Learning at undergraduate levels.

Claudio LUPIمشاهده پروفایل

استاد

• Econometrics
• Financial Accounting
• Time Series Analysis
• +۳ مورد دیگر

Prof. Claudio LUPi is a Full Professor at the Department of Economics, University of Molise. His expertise spans econometrics, financial accounting, and time series analysis with a focus on Benford's Law applications, regional economics, and consumer behavior. He has contributed significantly to understanding financial statement quality in public entities, business cycle synchronization, and the impact of elections on governance. His research also explores innovative areas like medical data simulation for atrial fibrillation detection. Key research areas include statistical methodology (e.g., unit root testing, copula models), public sector economics (municipal governance, fiscal policies), and consumer studies (cultured meat acceptance, dietary trends). His work bridges theoretical econometrics with practical applications in policy and healthcare. Prof. LUPi has authored over 50 publications since 1992, with recent articles emphasizing Benford's Law validation, cross-country banking analysis, and spatial economic dynamics. He actively contributes to R package development for econometric testing (e.g., CADFtest) and has collaborated on national projects like Italy's GDP forecasting.

Rosario Baroneمشاهده پروفایل

استادیار

• Statistics
• Economics
• Finance
• +۲ مورد دیگر

Rosario Barone is an Assistant Professor of Statistics at the University of Rome Tor Vergata. His research focuses on methodological development of statistical tools with applications in economics, finance, social sciences, and medicine. He specializes in Bayesian inference, Markov processes, and copula models, with recent work addressing complex dependencies and stochastic systems. His research interests include Bayesian nonparametrics, time-interaction processes, and semi-Markov models. Applications span healthcare (e.g., preterm birth analysis) and econometrics. Barone's publications highlight advancements in MCMC methods for continuous-time models and high-dimensional data analysis. He has contributed to interdisciplinary fields, merging statistical theory with practical applications in diverse domains.

Alessio Farcomeniمشاهده پروفایل

استاد

• Statistics
• Statistical Methodology
• Data Science
• +۵ مورد دیگر

Alessio Farcomeni is a Professor of Statistics at the University of Rome Tor Vergata, specializing in statistical methodology development. His work bridges academia and applied research across disciplines including economics, medicine, ecology, and engineering. He has authored/co-authored over 250 peer-reviewed papers and two books, with notable contributions in hidden Markov models, Bayesian analysis, and quantitative social science measurement. His research emphasizes interdisciplinary collaboration, reflected in studies on population health, economic policy evaluation, and surgical outcome optimization. Farcomeni’s research interests span statistical theory, with a focus on methodological innovations for complex data structures (e.g., longitudinal, spatial, and high-dimensional datasets). He has pioneered approaches in quantile regression, semi-Markov processes, and latent variable modeling. His applied work addresses real-world challenges such as estimating material deprivation scales, modeling cardiovascular disease risk factors, and analyzing pandemic dynamics (e.g., COVID-19 forecasting in Italy). His recent articles highlight advancements in statistical techniques for healthcare (e.g., AI-driven dermatology diagnostics, atrial fibrillation prediction models) and socio-economic analysis (e.g., macroprudential policy impacts, cross-country material deprivation comparisons). He is recognized for developing open-source statistical software packages, contributing to reproducible research practices. Farcomeni holds the distinction of being ranked among Italy’s top scientists by VIA-Academy. His work frequently integrates Bayesian methods, machine learning, and big data analytics to address pressing questions in public health, environmental science, and economic policy.

• Experimental Phonetics
• Sociolinguistics
• Bilingual Speech
• +۳ مورد دیگر

Alessandro Vietti is a Tenured Associate Professor of Linguistics at the Free University of Bozen-Bolzano, Italy, and Director of the ALPS (Alpine Laboratory of Phonetic Sciences). He holds a PhD in theoretical linguistics and sociolinguistics from the University of Pavia. His research focuses on experimental phonetics, sociolinguistics, and the quantitative analysis of speech variation using advanced methods like Ultrasound Tongue Imaging (UTI) and social network analysis. He leads projects such as the AlpiLinK corpus and the Phoné initiative for spoken Italian recognition systems. Key research areas include bilingual speech patterns in multilingual contexts, articulatory phonetics, and the sociolinguistic implications of phonetic variation. Vietti has developed a specialized laboratory for phonetic studies and contributed to documenting endangered languages through ASR systems. He teaches courses like Introduction to Linguistics and Sociolinguistics at the Bachelor level. His work bridges theoretical linguistics with applied methodologies, emphasizing empirical and technological innovation in language research. Notable projects include a DFG-funded study on Tyrolean dialect sounds (€500k) and collaborative research on multilingual speech models. Vietti’s publications span phonetic articulation, sociolinguistic modeling, and computational tools for language analysis. His contributions reflect a commitment to interdisciplinary approaches, integrating linguistics with technology and social science.

• Biomedical Engineering
• Medical Robotics
• Neural Engineering
• +۳ مورد دیگر

Giacomo Severini is a Lecturer in Biomedical Engineering at University College Dublin, Ireland. He holds a MSc in Electronic Engineering (2008) and a PhD in Biomedical Engineering (2012) from Roma Tre University. His postdoctoral research included roles at Harvard Medical School and Spaulding Rehabilitation Hospital in the USA. His work focuses on applying robotics to upper/lower limb rehabilitation, with contributions to muscle synergy analysis and tremor suppression systems. He participated in the EU-FP7 'TREMOR' project (2008–2011). Key research areas include EMG signal processing, cortico-muscular coherence, and rehabilitation technology. His projects emphasize clinical applications such as functional electrical stimulation and real-time movement intent detection. He has published widely in journals like IEEE Transactions on Neural Systems and Rehabilitation Engineering, and conferences including the International Society of Electrophysiology and Kinesiology (ISEK). His work also extends to bio-inspired neural models for tremor control and wearable robotic systems for mobility assistance. Lab affiliations include BioLab³ at Roma Tre University and the Motion Analysis Laboratory at Spaulding Hospital. His research integrates robotics, neuroscience, and biomechanics to enhance rehabilitation outcomes. Current efforts center on synergy-based approaches to movement analysis and robotic-assisted therapies.

• Psychometrics
• Health Psychology
• Clinical Psychology
• +۷ مورد دیگر

Paola Gremigni is an Associate Professor of Psychometrics at the Department of Psychology 'Renzo Canestrari' of the University of Bologna . She specializes in questionnaire development, multivariate statistics applied to personality and health behaviors, and clinical psychology with a focus on ADHD and systemic-relational psychotherapy. Her roles include heading the Service of Psychological Diagnosis in Adults and coordinating the Integrated Trainee Commission University-Board of Psychologists . Education: Master's in Philosophy (University of Pisa), Specializations in Psychology (University of Siena) and Systemic-Relational Psychotherapy (IPR Firenze), PhD in Psychology (University of Bologna). Editorial Roles: Associate Editor for Health Qual Life Out , Frontiers Psychol , and Int J Envir Res Pub Health . Research Interests: Focus on psychometric validation, health-related quality of life, stress in chronic illnesses (e.g., fibromyalgia, cancer), and infertility-related stress. Her work integrates clinical practice with statistical methodologies to address psychological well-being and healthcare communication. Her clinical activities include diagnostic assessment, psychotherapy for adults with ADHD, and training for psychotherapy trainees. She also leads studies on green food purchasing behavior and the psychological impact of medical interventions.

Gaia Meoniمشاهده پروفایل

پژوهشگر ارشد

• Metabolomics
• Foodomics
• NMR Spectroscopy
• +۳ مورد دیگر

Gaia Meoni is a Research Fellow in the Department of Chemistry at the University of Florence, Italy, affiliated with the Magnetic Resonance Center (CERM). She holds a Master's Degree in Molecular Biology and Genetics from the University of Pavia (2015) and a PhD in Structural Biology from the University of Florence (2018, cum laude). Her research focuses on NMR-based metabolomics, foodomics, and multivariate statistics, with applications in biomedical diagnostics, food quality, and agro-food systems. Key projects include the COMETA initiative studying metabolic profiles of COVID-19 patients, metabolomic analysis of Parkinson’s disease, and lipidomic studies of bacterial infections. She has contributed to over 30 peer-reviewed articles, emphasizing NMR applications in disease biomarker discovery and food authentication. Awards include the 2019 Faber 2 Prize for innovation in scientific talent development in Tuscany. Her work bridges clinical and agricultural sectors: analyzing biofluids (urine, saliva) for disease pathways, optimizing dairy cow health via milk metabolite profiling, and evaluating olive oil quality through post-harvest practices. She collaborates with industry (Giotto Biotech) and academic networks (CIRMMP), advancing translational metabolomics research. Grants include Tuscany Regional funding for SARS-CoV-2 metabolic studies and postdoctoral support from the University of Florence. Current projects explore boron supplementation in calves and selenium biofortification in tomatoes, reflecting a commitment to both human and agricultural health. Lab affiliations include CERM and CIRMMP, where she applies advanced NMR spectroscopy and machine learning to metabolomic challenges. Her research narrative emphasizes interdisciplinary solutions to global health and sustainability issues.

Alejandro Luis Callaraمشاهده پروفایل

پژوهشگر

• Biomedical Signal Processing
• Neuroimaging
• Brain Connectivity
• +۶ مورد دیگر

Alejandro Luis Callara serves as a postdoctoral researcher at the University of Pisa's Research Center "E. Piaggio," specializing in biomedical signal and image processing methodologies for neuroscience applications. His work bridges engineering and cognitive science through advanced computational approaches to physiological data analysis. His academic foundation includes: Bachelor’s Degree in Biomedical Engineering (2012), University of Pisa Master’s Degree in Biomedical Engineering (2015), University of Pisa PhD in Information Engineering (2019), University of Pisa Callara's research centers on developing analytical pipelines for EEG and fMRI data to map brain connectivity networks, with particular expertise in autonomic nervous system interactions during emotional processing. He actively contributes to the Brain matters team's development of neuronal segmentation tools for confocal microscopy data, extending his methodological focus to multi-scale tissue imaging. His technical proficiency spans directed coherence analysis, dynamic causal modeling, and thermal response quantification. Analysis of his 15 most recent publications (2024-2025) reveals three dominant research trajectories: (1) autonomic physiology investigations examining parasympathetic-sympathetic coupling during emotional tasks using EDA and HRV metrics; (2) innovative neuroimaging techniques for brainstem fMRI analysis and sparse connectivity mapping; and (3) multimodal integration studies exploring olfactory-visual-auditory interactions in affective disorders through VR/AR paradigms. Methodologically, his work consistently employs advanced signal processing frameworks like PCA-based partial correlation and ThermICA for multivariate analysis. Within the Research Center "E. Piaggio," Callara collaborates across bioengineering and robotics initiatives, particularly through the Brain matters team where he applies computational neuroscience to neuronal morphology analysis. His current projects focus on refining contactless stress classification systems using thermal imaging and developing immersive VR scenarios for anxiety disorder research, demonstrating strong translational potential for clinical applications.

Mimma Nardelliمشاهده پروفایل

استادیار

• Biomedical Signal Processing
• Wearable Monitoring
• Nonlinear Physiological Dynamics

Mimma Nardelli is an Assistant Professor at the University of Pisa's Department of Information Engineering and Research Center 'E. Piaggio'. Her research focuses on biomedical signal processing, wearable monitoring, and nonlinear analysis of physiological dynamics in clinical and healthy populations. She develops methods for assessing autonomic function, emotional states, and clinical conditions through multimodal biosignal analysis. She coordinates the PRIN project MOONSHINE and collaborates on EU projects including POTION and NEVERMIND. Her teaching includes Biometrics Systems, Affective Computing, and AI in Medicine. Awards include the 2017 GNB Award for her PhD thesis on HRV analysis for mood assessment. Research spans: wearable photoplethysmography validation, autonomic state characterization using multiscale entropy, cardiovascular coupling analysis, and physiological responses to affective stimuli. Applications include neonatal care, mental health monitoring, and human-robot interaction.

• Econometrics
• Computational Statistics
• Financial Risk Management
• +۵ مورد دیگر

Marco Bee is a Full Professor at the Department of Economics and Management, University of Trento. His expertise spans applied econometrics, computational statistics, finance, and risk modeling. He focuses on methodologies for handling heavy-tailed distributions, extreme value theory, and machine learning applications in financial risk assessment. Education details are available in his CV (CVeng.pdf). His research interests include developing statistical models for operational risk, volatility forecasting, and credit scoring, often employing mixture models, copula-based approaches, and indirect inference techniques. He has contributed significantly to the analysis of spatial econometrics and the application of extreme value theory to financial crises and insurance analytics. His recent work emphasizes tail risk estimation, with over 150 publications since 2006. Notable contributions include methodologies for Value-at-Risk (VaR) forecasting, distribution fitting for skewed data, and the use of machine learning to predict defaults in small businesses. His research bridges theoretical statistics and practical financial applications, with a focus on high-frequency data and scenario-based risk analysis. Awards and grants are not explicitly listed in the provided data, but his extensive publication record reflects recognition in quantitative finance and econometrics. He advises students on topics related to computational econometrics and risk modeling, though specific advisee names are not documented here.

• Statistics
• Decision Analysis
• Multivariate Analysis
• +۳ مورد دیگر

Antonio Lucadamo is an Associate Professor at the Department of Law, Economics, Management and Quantitative Methods (DEMM) of the University of Sannio. His research focuses on statistical modeling, decision analysis, and multivariate methods with applications in diverse fields such as financial markets, cultural festivals, environmental science, and healthcare evaluation. Key Research Areas : Decision theory, ordinal data handling, AHP methodology, environmental quality assessment Recent Collaborations : Pietro Amenta, Ida Camminatiello, Gabriella Marcarelli, and Matteo Rossi Publication Trends : His work spans from foundational statistical techniques (e.g., co-inertia analysis, Taguchi index generalization) to applied studies in financial decision-making, festival loyalty models, and environmental quality assessment. Notable subfields include pairwise comparison matrices, OWA operators, and spectral soil analysis. Contact : antonio.lucadamo@unisannio.it

Marco Geraciمشاهده پروفایل

استاد

• Statistical Methods in Health Sciences
• Quantile Inference
• Random-Effects Models
• +۹ مورد دیگر

Marco Geraci is a Professor at the Department of Methods and Models for Economy, Territory and Finance at Sapienza University of Rome . He teaches courses such as Statistics for Health Economics and Computational Tools for Finance . His research focuses on Statistical Methods in Health Sciences , including Quantile Inference , Random-Effects Models , Multivariate Statistics , and Missing Data Analysis . He also specializes in Accelerometer Data , Physical Activity , and Pediatric Oncology . His recent publications emphasize Quantile Regression applications in Public Health , Environmental Science , and Health Economics . Methodological contributions include Directional Quantile Classifiers , Functional Quantile Regression , and Laplace Distribution Projections . Themes span Biostatistics , Surgical Safety , and Maternal/Child Health Disparities .