Find Academic Supervisors

• Anesthesiology
• Intensive Care Medicine
• Critical Care
• +3 more

Massimiliano Greco is an Assistant Professor at Humanitas University and an anesthesiologist/intensivist at the IRCCS Humanitas Research Hospital in Milan. He leads clinical research in the Department of Anesthesiology and Intensive Care while maintaining roles in teaching, clinical practice, and academic leadership. His educational background includes a Medical Degree from the University of Milan, a specialization in Anesthesiology and Intensive Care, and a Master of Science in Epidemiology from the London School of Hygiene and Tropical Medicine. Teaching responsibilities include physiology courses for the MEDTEC Degree program and clinical planning modules for nursing science students. He also instructs advanced life support courses (ALS/ILS and ATLS) for emergency responders. His research focuses on critical care innovations, pandemic response strategies, and data science applications in medicine, with notable contributions to studies on postoperative outcomes, sepsis management, and wearable health technologies. Key Projects: Data Science Supervisor for the DASMEN PhD Project Coordinator of the UNITE-COVID-II multicenter study on critical care outcomes Principal Investigator for the BRAIN-PROMISE randomized trial on brain-targeted therapies Dr. Greco’s academic recognition includes the Premio Anzalone 2020 (for pandemic-era research), EACTA Young Investigator Grant, and grants from Italy’s Ministry of Health. His work emphasizes translational research bridging clinical practice and emerging technologies, particularly during the SARS-CoV-2 pandemic where he contributed to ICU strain analysis and vitamin C treatment trials. Grants & Collaborations: ESICM Methodology Group member SIAARTI Regional Board member Lead on EU-funded projects involving machine learning in critical care His clinical roles involve managing complex cases in anesthesia and resuscitation while advancing evidence-based practices through guidelines development (e.g., SIAARTI regional anesthesia safety protocols). He also oversees initiatives to improve patient monitoring via wearable devices and AI-driven predictive analytics.

• Machine Learning
• Deep Learning
• Neural Networks
• +3 more

Claudio Gallicchio is an Associate Professor of Deep Learning at the Department of Computer Science, University of Pisa, Italy. His research focuses on Machine Learning, Deep Learning, Neural Networks, and Dynamical Systems, with specialization in Dynamical Neural Networks, Reservoir Computing, and Graph Learning. He actively contributes to IEEE Task Forces on Reservoir Computing and Randomized Neural Networks, and is a member of several AI societies including AAAI and ENNS. He holds a Ph.D. in Computer Science from the University of Pisa. His work emphasizes addressing challenges in graph neural networks—such as oversquashing—and advancing energy-efficient neural architectures using memristive systems. He supervises students on topics like Recurrent Neural Networks, Neural ODEs, and Deep Learning for Digital Humanities. Gallicchio's recent publications explore Reservoir Computing applications in industrial processes, non-dissipative graph networks, and federated learning. His research bridges theoretical foundations (e.g., Hamiltonian architectural bias) with practical implementations (e.g., memristor-based models). He has pioneered frameworks like GRAMA for adaptive graph time-series analysis and the TEACHING platform for human-centric autonomous systems.

• Geotechnical Engineering
• Slope Stability
• Earthquake Engineering
• +7 more

Ernesto Ausilio is an Associate Professor in the Department of Civil Engineering at the University of Calabria, Italy. He is actively engaged in teaching and research, with a strong focus on geotechnical engineering and seismic risk assessment. His academic work spans numerical modeling, landslide analysis, soil-structure interaction, and geotechnical monitoring of critical infrastructure. Research Interests: His primary research areas include slope stability, earthquake-induced landslides, seismic ground motion analysis, and geotechnical modeling for infrastructure resilience. He employs advanced numerical methods and data-driven approaches such as machine learning and time-frequency analysis to study complex geotechnical phenomena. The recent publications highlight a consistent trend in applying innovative computational techniques—including metaheuristic algorithms and random forest models—to solve practical geotechnical problems related to seismic stability, liquefaction, and infrastructure safety. His work often involves case studies from Southern Italy and Japan, emphasizing real-world applicability and multidisciplinary approaches. Scientific Contributions: While no formal awards are listed, his extensive publication record in high-impact journals and conferences reflects significant scholarly contributions to geotechnical earthquake engineering. Teaching and Mentorship: He teaches courses such as Geotechnical Engineering and Geotechnical Design at both undergraduate and graduate levels. Although no students are listed, his role in research groups suggests advisory and collaborative mentorship. He is involved in research projects and supervises laboratory activities related to geotechnics. Laboratories and Research Groups: He is a member of the Geotechnical Engineering Research Group, focusing on porous media mechanics, numerical modeling of slope failure, seismic response analysis, and ground improvement techniques. He is associated with the Geotecnica Laboratory within the Department of Civil Engineering, supporting research, teaching, and technical services.

• Redox Biology
• Molecular Nutrition
• Food Science
• +3 more

Paolo Bergamo is a Researcher at the Institute of Biosciences and BioResources (IBBR) of the National Research Council of Italy (CNR) in Naples, a position held since 2021. Previously, he served as a Researcher at the CNR Institute of Food Sciences (ISA) in Avellino (2003-2021) and the CNR Institute for the Animal Production System in the Mediterranean Environment (ISPAAM) (1993-2002). His academic foundation includes: Bachelor in Biological Science, University of Naples "Federico II" (1987, summa cum laude) Postgraduate training, Stazione Zoologica "Anton Dohrn" (1987-1989) CNR fellowship, ISPAAM (1990-1991) Bergamo's research centers on dietary bioactives' modulation of redox homeostasis, with emphasis on conjugated linoleic acid (CLA), plant extracts, and fatty acids. He investigates their impact on the Nrf2 pathway, mitochondrial function, and oxidative stress in contexts including neuroprotection, male fertility under pollution, and inflammatory bowel disease. His work bridges molecular nutrition, biochemistry, and translational health to develop dietary strategies against oxidative damage. Analysis of his 2019-2023 publications reveals consistent exploration of Nrf2 pathway activation by dietary compounds across celiac disease models, neurodegeneration, metabolic disorders, and environmental toxicology. This cohesive theme demonstrates how nutritional interventions target oxidative stress in multiple organ systems through shared molecular mechanisms. No scientific awards or fellowships are documented in the provided information. While specific grant details are unlisted, Bergamo's sustained CNR research positions indicate continuous project funding. He has not formalized graduate student supervision but actively contributes as a reviewer for journals including Free Radical Biology and Medicine, PLoS One, and Journal of Leukocyte Biology. His collaborative network spans CNR divisions and international partners. Within IBBR's Naples division, Bergamo leads laboratory investigations into diet-redox interactions, utilizing in vitro and in vivo models to study bioactive molecules' effects on cellular pathways and physiological outcomes in health and disease contexts.

Raffaella BurioniView profile

Professor

• Statistical Physics
• Complex Networks
• Random Walks
• +5 more

Raffaella Burioni is a Full Professor of Theoretical Physics in the Department of Mathematics, Physics and Computer Science at the University of Parma. She serves as Chair of the Non-Linear and Statistical Physics Division of the European Physical Society (EPS) and co-founded the Italian Society of Statistical Physics (SIFS), where she holds the position of Vice President. Her academic leadership includes directing the Ph.D. School in Physics and previously managing quality assurance for the Master's program in Physics (2017-2023). Her educational background includes an MS in Physics with distinction from the 2nd University of Rome and a PhD in Theoretical Physics from the University of Rome 'La Sapienza'. Postdoctoral experience spans the Theoretical Physics Laboratory of the École Normale Supérieure in Paris, the University of Milan, and the National Institute for the Physics of Matter (INFM). Prof. Burioni's research centers on equilibrium and non-equilibrium statistical physics, with deep expertise in graph theory, complex networks, random walks, and stochastic processes. She pioneers interdisciplinary applications to biological systems, neuroscience, and machine learning. Her work on rare events and anomalous diffusion has established fundamental principles like the 'single big jump' mechanism in transport phenomena. Recent investigations bridge statistical physics with neural network theory, examining kernel renormalization and feature learning in deep architectures. Analysis of her 15 most recent publications (2022-2025) reveals three dominant trends: (1) Theoretical advances in rare event statistics for jump processes and extreme value theory, (2) Network-based epidemic modeling incorporating adaptive temporal dynamics and simplicial structures, and (3) Machine learning physics connecting neural network theory to statistical mechanics through Bayesian effective actions and kernel methods. Her work consistently demonstrates how statistical physics principles solve complex problems across disciplines. Her scientific accolades include: Two-time recipient of the Enrico Persico Prize from the Accademia Nazionale dei Lincei Fellow of the Institute for Scientific Interchange (ISI) since 2014 American Physical Society Outstanding Referee (2018) Fellow of the European Centre for Living Technology (2020) As Director of the Ph.D. School in Physics, she mentors doctoral candidates while serving on editorial boards for Physical Review E, JSTAT, and Journal of Physics A. Her research is supported by international collaborations with institutions including the Kavli Institute for Theoretical Physics, Max Planck Institute, and Ben-Gurion University, evidenced by frequent keynote invitations at major conferences like StatPhys, ECCS, and APS March Meetings. Prof. Burioni leads collaborative research networks through her EPS division chairmanship and SIFS leadership, fostering cross-institutional projects on statistical physics applications. Her campus-based studies leverage Wi-Fi data from Parma University to model pedestrian dynamics and epidemic spreading in real-world constrained environments.

• Calculus of variations
• Partial differential equations
• Geometric measure theory
• +4 more

Filippo Cagnetti is an Associate Professor (Professore di II fascia) in the Department of Mathematical, Physical and Computer Sciences at the University of Parma , Italy. He regularly teaches foundational courses such as Calculus 2A and Mathematical Analysis A to first- and second-year students enrolled in Mathematics, Geological Sciences (Earth Sciences), and Management Engineering degree programmes, spanning academic years from 2023/2024 through 2025/2026. His research lies at the intersection of calculus of variations , partial differential equations , and geometric measure theory . A recurrent theme is the rigorous derivation of effective models for materials with microstructures via deterministic and stochastic homogenisation , particularly for free-discontinuity problems that describe brittle fracture. Parallel efforts focus on symmetrisation inequalities (Pólya–Szegö, Steiner, Schwarz, Gaussian) and their rigidity properties: under which geometric or analytic conditions equality in an inequality forces the domain to be symmetric or even trivial. Over the past decade his publication portfolio shows a clear evolution from foundational results on viscosity solutions and large-time behaviour of Hamilton–Jacobi equations to highly specialised contributions on Korn- and Poincaré-Korn-type inequalities in spaces of special functions of bounded deformation (GSBD), and on optimal regularity of free boundaries in cohesive fracture models. The techniques employed combine Γ-convergence, fine properties of BV and GSBD spaces, measure-theoretic arguments, and stochastic two-scale convergence. Contact: Email: filippo.cagnetti@unipr.it

Sandro Marcel WimbergerView profile

Associate Professor

• Quantum Mechanics
• Quantum Control
• Quantum Chaos
• +7 more

Prof. Sandro Marcel Wimberger is an Associate Professor at the University of Parma’s Department of Mathematical, Physical and Computer Sciences since 2017. His research spans theoretical physics of matter, focusing on quantum control, many-body dynamics, and light-matter interaction. He holds a binational German-Italian PhD (2004) from Ludwig Maximilians University Munich and Università dell’Insubria. Education: Diploma in physics (LMU Munich, 2000), PhD (LMU Munich/Insubria University, 2004) Awards: Humboldt Fellowship, EPS membership, INFN association Wimberger’s research interests include quantum optics , open quantum systems , and Bloch-Floquet engineering , with applications to Bose-Einstein condensates and quantum search protocols. His recent work focuses on non-equilibrium dynamics and counterdiabatic control. He has co-authored over 130 peer-reviewed papers, two editions of Springer’s Nonlinear Dynamics and Quantum Chaos , and organized major conferences like the Statistical Physics and Complex Systems meetings in Parma. His collaborations with experimental groups worldwide are documented in joint publications. Scientific Awards : Feodor-Lynen Fellowship (2004-2006) Heidelberg Academy young researcher award (2008) Hengstberger Prize (2009) Akademiepreis (2010) EPS membership (2023-25) Wimberger has advised over 50 students and 2 postdocs, secured over €1M in external funding, and contributed to interdisciplinary projects like the Center for Quantum Information Science at Parma University. His recent grants include EU-funded Q-DYNAMO (2024-28) and PNRR projects.

• Sports Physiology
• Exercise Science
• Physical Training
• +5 more

Daniele Zangla is an Associate Professor in the Department of Psychological, Pedagogical, Physical Exercise and Training Sciences at the University of Palermo's School of Medicine and Surgery. His academic position (MEDF-01/A) focuses on the intersection of sports science, exercise physiology, and physical training methodology. He maintains regular office hours on Tuesdays from 10:00 to 11:00 at Via Pascoli and is actively involved in teaching multiple courses for the 2025/2026 academic year. Professor Zangla's research interests span sports biomechanics, exercise physiology across different populations, adapted physical activities, and the physiological effects of training. His work demonstrates particular expertise in rowing biomechanics, cycling performance, volleyball training methodologies, and the physiological adaptations to various training protocols. He has published extensively on the effects of exercise on cardiovascular parameters, hormonal responses, and performance metrics in athletes ranging from youth to professional levels. His recent publications (2020-2025) reveal a strong focus on sports-specific performance analysis, particularly in rowing, cycling, and volleyball. The research shows consistent methodological approaches combining biomechanical analysis with physiological monitoring. Notably, his work addresses both elite athlete performance optimization and adapted physical activities for special populations including individuals with visual impairments, congenital conditions, and post-surgical patients. Professor Zangla teaches several key courses including Joint Physiology and Functional Movement Analysis, Methodology and Planning of Individual Sports Activities in the School Environment, Training Theory and Methodology, and Theory, Technique, and Teaching of Aquatic Sports Activities. His teaching portfolio reflects his research expertise in sports physiology, biomechanics, and adapted physical activities.

• Gynecological Oncology
• Minimally Invasive Surgery
• Fertility Preservation
• +4 more

Marco Monti serves as Associate Professor at Sapienza University of Rome's Department of Maternal and Child Health and Urological Sciences, where he teaches Obstetrics (Corso di Laurea Ostetricia) with specific focus on childbirth assistance. His clinical expertise spans gynecological oncology, minimally invasive surgery, and reproductive medicine, supported by extensive publications in high-impact journals. His primary research interests include: Gynecological cancer management (particularly ovarian and cervical malignancies) Fertility-sparing treatments for early-stage endometrial/cervical cancers Innovative endometrial preparation techniques for hysteroscopic procedures Non-invasive therapies for genitourinary syndrome of menopause Obstetric complications in high-risk pregnancies Analysis of his 2022-2025 publications reveals three dominant trends: (1) Optimization of rapid-start hormonal protocols for outpatient hysteroscopy, (2) Advancement of PARP inhibitor therapies in ovarian cancer, and (3) Expansion into public health domains including pandemic risk assessment and disaster response. His work consistently bridges clinical practice with translational research through multicenter trials. Dr. Monti leads two major research initiatives: Conservative treatment of early-stage endometrial cancer - Investigating fertility preservation and obstetric outcomes Conservative treatment of early-stage cervical cancer - Evaluating pregnancy outcomes after conservative management His research receives institutional support through Sapienza University frameworks, with recent projects examining minimally invasive surgical approaches and menopausal symptom management using CO2 laser therapy.

ANTONIO MUSOLESIView profile

Professor

• Econometrics
• R&D and Innovation
• Productivity Analysis
• +5 more

Antonio Musolesi is a Full Professor of Econometrics at the Department of Economics and Management, University of Ferrara, where he has worked since 2021. Previously, he served as Associate Professor (2013-2021) and held research positions at INRA and CNRS in France. His research spans econometrics, innovation, productivity, environmental economics, and spatial modeling. Education: PhD in Economics (University of Nice Sophia-Antipolis, 2004), M.S. in Statistics and Econometrics (University of Toulouse, 2002), B.A. in Political Science (University of Bologna, 2000) His research focuses on econometric modeling of innovation, productivity, and environmental policy, with expertise in panel data, nonparametric methods, and spatial econometrics. Current work includes semiparametric models for cross-sectional dependence and applications to knowledge production and climate change. Recent publications investigate R&D spillovers, environmental Kuznets curves, and policy evaluation using advanced econometric techniques. He has participated in EU FP7 and FP6 projects and serves as editor for Open Economics . Key scientific awards: National Scientific Qualification to Full Professor, CNRS and INRA fellowships Musolesi supervises PhD students and teaches econometrics at the University of Ferrara and University of Lyon. He has co-organized international workshops on climate econometrics and spatial modeling.

Emilio LeonardiView profile

Professor

• Communication Networks
• Complex Systems
• Epidemic Spreading
• +7 more

Emilio Leonardi is a Full Professor at the Department of Electronics and Telecommunications (DET) of Politecnico di Torino, Italy, since 2015. His research focuses on communication systems, complex networks, epidemic spreading, and online social networks. He has held visiting roles at INRIA (2016-2017), NEC Laboratories Europe (2012), and collaborated with institutions like UCLA, Bell Labs, and Stanford. Key research areas: Telecommunications and network engineering Stochastic processes in network modeling AI-driven caching and content delivery Social network temporal dynamics Epidemic propagation on graphs Recent publication trends highlight his expertise in similarity caching algorithms, federated learning, re-identification attacks, and generative AI applications in information retrieval. His work spans both theoretical modeling and practical implementation in real-world networks. Scientific recognition: Best Paper Award at IEEE Globecom (2002) Multiple IEEE/ACM conference awards (2006, 2012) Guest Editor for IEEE special issues Editorial board member of IEEE Transactions Teaching and mentoring: Main teacher for PhD courses in Electrical, Electronic and Communications Engineering, including Stochastic processes and queuing theory and Operational research . Supervised PhD student Franco Galante (2020-2024) on social interaction modeling. Labs and collaborations: Member of TNG research group at DET. Participated in European projects like NAPA-WINE (FP7), COOPERATION-ICT, and national PRIN initiatives. Industry collaborations with Lucent, IBM, Microsoft Research, and NEC.

Riccardo TomaselloView profile

Associate Professor

• Spintronics
• Micromagnetic Modeling
• Magnetic Skyrmions
• +7 more

Riccardo Tomasello is an Associate Professor at the Department of Mechanical Engineering, Polytechnic University of Bari. His research focuses on Spintronics , particularly on Micromagnetic Modeling of Magnetic Skyrmions and Spin-Transfer-Torque Magnetic Random Access Memory (STT-MRAM) , with applications in low-power devices, neuromorphic computing, and microwave detection. He leads the project ThunderSKY , funded by the Hellenic Foundation for Research and Innovation (HFRI) and the European Investment Bank. Research Highlights : Skyrmion dynamics, antiferromagnetic materials, spin-orbit torque, magnetic tunnel junctions, 3D nanomagnetism. Key Collaborations : HFRI, GSRT, European Investment Bank. His recent work explores Probabilistic Ising Machines , Spintronic Diodes , and Quantum Annealing for unconventional computing. He has published extensively on magnetic solitons, domain walls, and their electrical control, contributing to advancements in Neuromorphic Hardware and Edge Computing . Notable grants include funding from the Hellenic Foundation for Research and Innovation and the European Investment Bank for the ThunderSKY project. His teaching involves Principles of Electrical Engineering within the Bachelor's Degree in Mechanical Engineering .

Omiros PapaspiliopoulosView profile

Professor

• Computational Statistics
• Machine Learning
• Probability
• +5 more

Omiros Papaspiliopoulos is a Full Professor at Bocconi University’s Department of Decision Sciences. He joined Bocconi in 2021, previously serving as an ICREA Research Professor at Universitat Pompeu Fabra in Barcelona. His academic career includes roles at Warwick, Oxford, Lancaster, Berlin, Osaka, Paris, Madrid, and Lima. He has been awarded the Royal Statistical Society’s Guy Medal (2010) and the DeGroot Prize for his influential work with Nicolas Chopin. His research focuses on computational statistics, spanning Bayesian inference, machine learning, probability, and applied mathematics. Notably, he founded Europe’s first Master in Data Science at the Barcelona Graduate School of Economics (2013) and directed the Data Science Center until 2021. Since 2022, he has been Director of Bocconi’s Bachelor of Science in Economics, Management, and Computer Science (BEMACS). Papaspiliopoulos is co-Editor of Biometrika (top-4 in Statistics) and Associate Editor of the Journal of Uncertainty Quantification . He has delivered keynote talks at institutions like Chicago Booth, Duke, and LSE, emphasizing the societal impact of data science. His teaching spans courses on data science, statistics, machine learning, and quantitative methods in social sciences. Education & Academic Leadership PhD in Statistics (Implied by career trajectory) Founded Bocconi’s BEMACS program (2022) Directed the Master in Data Science (2013–2021) Executive course design for SDA Bocconi and Barcelona School of Economics Research Interests Computational Statistics & Bayesian Methods Machine Learning & Applied Mathematics Data Science in Social Sciences Hidden Markov Models & State-Space Systems High-Dimensional Inference & Scalable Algorithms Recent Work Trends His publications emphasize scalable Bayesian computation, treatment effect inference, and applications in social sciences. Recent topics include confounder importance learning, particle filtering, and computational efficiency in hierarchical models. Collaborations bridge theory and practice, addressing challenges in policy, finance, and public administration. Awards & Recognition 2010: Royal Statistical Society’s Guy Medal DeGroot Prize for Nonparametric Hidden Markov Models Onassis Foundation Scholar Grants & Outreach Directed the Barcelona Data Science Center (2016–2021) Outreach activities: Talks for high-school students, policymakers, and the European Commission Editorial roles in top journals: Biometrika , Journal of Uncertainty Quantification Labs & Teams Current affiliation with Bocconi’s Department of Decision Sciences and involvement in interdisciplinary data science initiatives.

• Homogenization Theory
• Calculus of Variations
• Nonlinear Analysis
• +3 more

Valeria Chiadò Piat is an Associate Professor at Politecnico di Torino, specializing in homogenization theory, calculus of variations, and nonlinear analysis. Her research focuses on multiscale problems, including the analysis of degenerate functionals, oscillating manifolds, and composite materials. She has organized significant events such as the 2025 'Perspectives in the Calculus of Variations' conference and the 2020 'Calculus of Variations and Applications' workshop. Her work bridges theoretical analysis and applied material science, with key contributions to homogenization of high-contrast materials, discrete double-porosity models, and anisotropy properties in polycrystalline magnetic systems. Notable collaborations include projects with A. Braides on extension theorems and non-local functionals, and with O. Bottauscio on magnetic materials' effective properties. Recent publications (2021–2025) emphasize relaxation of degenerate functionals and homogenization in oscillating domains. Her research also explores phase transitions in composite media and variational inequalities for elasto-plastic systems. She has contributed to both foundational theory and numerical methods in material science.

• Statistical Mechanics
• Mathematical Physics
• Probability Theory
• +4 more

Claudio Giberti is a Full Professor at the University of Modena and Reggio Emilia, affiliated with the Department of Engineering Sciences and Methods. His academic roles include teaching advanced courses in Rational Mechanics, Applied Mathematics, Stochastic Methods for Simulations, and Mathematical Physics. He holds a permanent faculty position with expertise spanning theoretical physics, applied mathematics, and interdisciplinary research in healthcare analytics. Research Interests: His work focuses on statistical mechanics, non-equilibrium thermodynamics, and complex systems. Key areas include anomalous transport in low-dimensional systems, phase transitions in spin models, and applications of stochastic methods to biomedical problems such as electrocardiogram (ECG)-based mortality risk assessment. He also explores interdisciplinary topics like queueing models for logistics optimization. Publications: Over 15 recent articles (2015–2025) address topics ranging from uphill diffusion phenomena in Ising models to machine learning applications in cardiology. Notable contributions include studies on microscopic state equations for oscillator chains and annealed Ising models on random graphs, highlighting his dual expertise in theoretical physics and applied mathematics. Teaching: Courses include Rational Mechanics for Mechatronics Engineering, Stochastic Simulation Methods for Mathematics students, and Applied Mathematics for Management Engineering. He emphasizes hands-on learning with practical exercises and software tools for structural analysis. Future Work: Current projects involve refining ECG-based predictive models for cardiovascular risk and extending studies on non-equilibrium dynamics in multi-component systems. Collaborations with biomedical researchers and engineers underscore his commitment to bridging theoretical and applied research.