جست‌وجوی استاد و پژوهشگر

• Artificial intelligence
• Biomedical signal processing
• Human movement analysis
• +۱۲ مورد دیگر

Marco Ghislieri is an Assistant Professor at the Department of Electronics and Telecommunications (DET) of Politecnico di Torino, Italy. He is a member of the Interdepartmental Center PolitoBIOMed Lab and teaches in the Biomedical Engineering program, including courses like Neuroengineering and Design of Programmable Biomedical Devices . His research spans Artificial Intelligence, Biomedical Signal Processing, Neuroscience, and Rehabilitation Engineering . PhD in Bioengineering and Medical-Surgical Sciences (2017-2021) at Politecnico di Torino Thesis: Muscle Synergy Assessment during Cyclic and Non-Cyclic Movements His research focuses on muscle synergy analysis in Parkinson’s Disease (PD) patients post- Deep Brain Stimulation (DBS) , AI-driven gait analysis for fall prevention, and wearable sensor applications for stress-cognitive decline monitoring. He leads the S-CoDe and OMNIA-PARK projects, and contributes to PRIN as a team member. Recent publications highlight advancements in machine learning for intraoperative DBS targeting , statistical gait analysis , and neurorehabilitation tools . He serves as Associate Editor for Scientific Reports and Applied Bionics and Biomechanics , and Guest Editor for Frontiers in Neural Circuits . Awards include the Carlo J. De Luca Award (2022) , GNB Doctoral Award (2022) , and the Best Poster Award at M. Grattarola Summer School (2022) . He supervises Fabrizio Sciscenti (PhD candidate) and collaborates on neuroengineering and biomedical device design courses. His work addresses Goal 3 (Good Health) and Goal 4 (Quality Education) of the UN SDGs.

Andrea Garzelliمشاهده پروفایل

استاد

• Remote Sensing
• Image Processing
• Signal Processing
• +۴ مورد دیگر

Andrea Garzelli is a Full Professor at the University of Siena's Department of Information Engineering and Mathematical Sciences. His research focuses on remote sensing image processing, particularly in optical and SAR sensor technologies, image fusion, and spatial resolution enhancement. He holds teaching roles in 'Fundamentals of Signal Processing and Telecommunications' and 'Statistical Signal Processing.' He earned his Ph.D. in Computer Science and Telecommunication Engineering from the University of Florence. Notably, he was recognized as a World's Top 2% Scientist by Stanford University for 2019–2023 and his career-long contributions. He served as President of the University of Siena's Quality Assurance Committee (2016–2021) and currently coordinates the graduate program in Computer and Information Engineering. Research interests include satellite data analysis (e.g., Sentinel-2, PRISMA), hypersharpening techniques, and environmental monitoring. His work bridges theoretical advancements (e.g., pansharpening algorithms) and practical applications like urban land classification and vegetation index enhancement. Recent articles emphasize reproducibility, meta-analysis, and synthetic data generation through GANs. Awards: World's Top 2% Scientists (2019–2023 & career). Grants/Advising: Supervises remote sensing theses; no specific grants mentioned. Labs/Teams: Leading research in the department's remote sensing and signal processing groups.

• Actuarial Science
• Life Insurance
• Pension Funds
• +۶ مورد دیگر

Annamaria Olivieri is a Professor of Actuarial Science at the Department of Economics and Business , School of Business , University of Parma , Italy. Her research focuses on actuarial mathematics for life insurance and pension funds , particularly in longevity risk valuation, solvency requirements, and risk-sharing frameworks. She has held visiting positions at the School of Actuarial Studies and CEPAR , University of New South Wales , and contributed to institutional teaching and PhD programs in Italy. Her work appears in leading journals such as Insurance: Mathematics & Economics and ASTIN Bulletin . Degree in Business Economics, University of Parma Degree in Statistics and Actuarial Science, University of Florence PhD in Mathematics for Financial Markets, University of Brescia Her research spans stochastic mortality modeling , capital allocation for life annuities, and multistate models for insurance valuation. Recent publications explore longevity-linked annuities , time-restricted annuity benefits , and mortality shock risk . As an Associate Editor of the European Actuarial Journal , she contributes to advancing actuarial research. Scientific Awards: Bob Alting von Gesau Prize 2010 (with Ermanno Pitacco) for longevity risk research She has participated in Italian MUR-funded projects and served on PhD scientific committees at the University of Udine , University of Parma , and University of Trieste . Her editorial and refereeing roles include ASTIN Bulletin , Insurance: Mathematics & Economics , and Journal of Risk and Insurance .

• Nanotechnology
• Quantum Physics
• Materials Science
• +۳ مورد دیگر

Dr. Emanuele Marino is a Researcher in the Department of Physics and Chemistry at the University of Palermo , affiliated with the School of Basic and Applied Sciences . His work bridges quantum physics and nanotechnology, focusing on nanocrystal superparticles, photonic materials, and fluctuation-driven assembly processes. Current research areas include quantum dot lasing, Casimir effects, and 3D nanoparticle superlattices Teaches courses like Modern Physics Laboratory (2024, School of Basic and Applied Sciences) and Physics II (Polytechnic School) Recent publications highlight trends in: Tunable photonic properties via nanocrystal emulsion systems Quantum-excitonic coupling in heterostructures Critical Casimir forces for nanoparticle control Dynamic phase transformations in colloidal superlattices Microlaser fabrication and chirality engineering Based in the Emilio Segrè Physics and Chemistry Department , he conducts experimental and theoretical studies from nanoscale fabrication to quantum optical phenomena.

Federico Nutarelliمشاهده پروفایل

استادیار

• International Trade
• Health Economics
• Machine Learning
• +۳ مورد دیگر

Federico Nutarelli is an Assistant Professor of Economics at the IMT School for Advanced Studies Lucca, Italy. His research focuses on the intersection of machine learning and economic analysis, particularly in international trade, health economics, and industrial organization. He holds a Ph.D. in Economics from IMT Lucca, and previously conducted postdoctoral research at Bocconi University. In 2024, he was a Visiting Scholar at MIT Sloan School of Management. Key research interests include causal machine learning methods to analyze heterogeneous firm responses to economic shocks, pharmaceutical market pricing strategies, and structural demand models. His work bridges methodological rigor with applied relevance, contributing to health economics, trade dynamics, and innovation policy. Recent publications (2020–2025) explore topics such as matrix completion for world trade analysis, machine learning applications in economic complexity, and modeling innovation ecosystems. His work often employs advanced statistical techniques like Shapley values and reinforced Bernoulli processes. No scientific awards were explicitly mentioned in the provided texts. Federico collaborates with institutions like Bocconi University and MIT Sloan, reflecting his interdisciplinary network in economics and data science.

• Big data analytics
• Data analysis
• Data management
• +۸ مورد دیگر

Daniele Apiletti is an Associate Professor at the Polytechnic University of Turin , affiliated with the Department of Control and Computer Engineering (DAUIN). He serves as a member of the Interdepartmental Center SmartData@PoliTO and acts as Academic Advisor for the Master's degree program in Data Science and Engineering. Research Groups: DBDM - Database and Data Mining Group (DAUIN) ERC Sectors: Algorithms, Artificial Intelligence, Machine Learning, Web and Information Systems Research Interests span Big Data Analytics, Data Science, Machine Learning, Computer Vision, and Quantum Computing. His work focuses on integrating data-driven and theory-guided approaches for heterogeneous data querying, cloud continuum machine learning, and spatio-temporal models for crisis management. Recent Publications highlight trends in medical image segmentation, predictive industrial modeling, and fault-tolerant data systems. Key subfields include AI in healthcare, scalable manufacturing analytics, and vision-language models for game tutorials. Teaching roles include course ownership of Big Data: Architectures and Data Analytics and Internships across multiple academic years. He has collaborated on courses in Data Science, Database Technologies, and Data Management. PhD Students Supervised: Etibar Vazirov (Cloud Continuum Machine Learning) Gabriele Scaffidi Militone (Cloud Storage Microservices) Daniele Rege Cambrin (Spatio-Temporal Ecology Models) Simone Monaco (Theory-Guided Data Science) Research Projects include commercial contracts on: - Natural language querying of corporate research archives - National tourism ecosystem platforms - AI for thermotechnical system design - Machine Learning in clinical trials and supply chains

• Neuroscience
• Computational Modeling
• Meditation
• +۵ مورد دیگر

Giuseppe PAGNONI is an Associate Professor at the Department of Biomedical, Metabolic and Neurosciences of Università di Modena e Reggio Emilia . His research spans neuroscience , computational modeling , meditation , and brain network analysis . He teaches courses such as Neural Systems Modeling for Bioengineering students and Human Physiology and Pathophysiology in Medicine programs, with a focus on predictive coding , default mode network , and emotional valence processing . Pagnoni has contributed to ENIGMA-Meditation , a global initiative exploring meditation's neuroscientific basis, and developed sparse Bayesian models for analyzing brain network individual differences. His work on Alzheimer's disease investigates anosognosia mechanisms through resting-state fMRI, while other studies examine ghrelin's role in obesity-related reward processing and oxytocin's effects on social anxiety . He employs dynamic causal modeling and predictive processing frameworks to study cognitive effort, mind wandering, and neuromorphic learning. His methodological expertise includes functional MRI , independent component analysis , and computational simulations .

• Structural Health Monitoring (SHM)
• Smart / self-sensing cementitious composites
• Bridge engineering and life-cycle assessment
• +۶ مورد دیگر

Filippo Ubertini is Professor of Civil and Environmental Engineering at the University of Perugia, Italy, where he coordinates the International Doctoral Programme in Civil & Environmental Engineering and represents the University inside the FABRE national bridge-research consortium. He leads the Structural Health Monitoring Laboratory ( SHM-Lab ) and is the primary contact for assignments linked to smart-infrastructure research. Education: While explicit degrees are not listed in the supplied text, his role as programme coordinator and full professor implies completion of a PhD and habilitation in Civil Engineering. Research focus: Ubertini’s work sits at the intersection of smart materials and data-driven infrastructure management . He develops self-sensing cementitious composites doped with carbon micro-fibers or graphene nano-platelets that can measure strain, cracking and moisture in real time, turning whole bridges and buildings into distributed sensors. Complementary research threads include low-cost acquisition electronics, UAV & InSAR remote sensing, Bayesian & adversarial machine-learning algorithms for damage detection, digital twins and life-cycle cost analysis of bridge networks. Publication trends (2024-2025): Roughly 30 peer-reviewed items per year concentrate on (i) AI-enhanced operational modal analysis and transfer-learning damage classification across bridge populations, (ii) experimental characterisation of 3D-printed and cast self-sensing concrete, (iii) full-scale validation on curved box-girder, masonry and railway bridges, and (iv) integration of satellite radar data with numerical collapse simulations to predict residual service life of landslide-affected viaducts. Scientific awards & recognition: No specific prizes or fellowships are mentioned in the provided text. Doctoral supervision & grants: The text does not enumerate individual students or funded projects; however, his coordination of an international PhD programme and numerous experimental campaigns imply sizeable supervisory and funding responsibilities. Laboratory & team: Ubertini heads the SHM-Lab at UniPg, maintaining facilities for material mixing, 3D concrete printing, electrical impedance tomography, UAV photogrammetry, and large-scale structural testing, while collaborating with the European FABRE consortium and multiple EU projects.

• Manufacturing Engineering
• Welding Technologies
• Non-Destructive Testing
• +۵ مورد دیگر

Manuela De Maddis is a Tenured Researcher at the Department of Management and Production Engineering (DIGEP) of the Polytechnic of Turin (PoliTo), where she has worked since 2005. She is also a member of the Interdepartmental Center J-Tech@PoliTo. PhD in Industrial Production System Engineering (2004), Polytechnic of Turin MSc in Management Engineering (2001), University of Calabria Her research focuses on Manufacturing Technologies , particularly Welding Processes and Infrared Thermography for non-destructive testing. She leads projects like TECNOPROTEO (2024-2027) and NDTxW (2024-2025) as Scientific Manager. Her work integrates Machine Learning and High-Fidelity Modeling for digital manufacturing systems. Recent publications analyze active thermography in weld quality, electrode degradation in spot welding, and probabilistic tolerancing methods. She supervises PhD students in Materials Science and Production Engineering . Mentoring Polito Project (M2P) (2023) Learning to Teach (L2T) (2023) Manuela teaches courses like Industrial Welding Processes , Advanced Manufacturing Technologies , and Ergonomics in Production Innovation at both undergraduate and graduate levels. She contributes to interdisciplinary labs focused on Manufacturing Process Innovation and Technological Validation .

Agostino Cortesiمشاهده پروفایل

استاد

• Software Engineering
• Static Analysis
• Cybersecurity
• +۵ مورد دیگر

Agostino Cortesi is a Full Professor at Ca' Foscari University of Venice , affiliated with the Department of Environmental Sciences, Informatics and Statistics. He serves as Rector's Delegate for Research Quality Assessment and Deputy Coordinator of the Scientific Committee for the Innovation Ecosystem Project. His academic career includes a PhD in Applied Mathematics and Informatics from the University of Padova (1992), a postdoctoral fellowship at Brown University, and visiting professor roles at institutions such as the University of Illinois and École Normale Supérieure Paris. Research interests focus on software engineering , static analysis , security applications , and abstract interpretation . He has pioneered techniques for formal verification of software systems and explored cybersecurity in e-Government and robotics. His work spans over 200 publications in top journals and conferences (e.g., ACM TOPLAS, IEEE TSE, POPL, PLDI). Key contributions include advancements in abstract domains for behavioral property verification and security-oriented analysis frameworks. He has held leadership roles including Vice-Rector at Ca' Foscari, Dean of Computer Science programs, and Chair of the Department of Computer Science. Cortesi coordinates EU Horizon 2020 projects (e.g., Families_Share €1.6M) and regional initiatives like CEVID (€360K). He founded Factors , a university spin-off focused on robotic systems verification, which won the 2020 Veneto SmartCup ICT Prize. Education: PhD in Applied Mathematics and Informatics (1992, University of Padova) Editorial Roles: Co-Editor-in-Chief of Springer’s 'Services and Business Process Reengineering', and member of editorial boards for 'Computer Languages' and others Grants: Over €3M in EU and regional funding for projects in cybersecurity, Industry 4.0, and digital innovation Teaching includes courses on Software Correctness , Data Programming , and Computer Networks across Computer Science and Management programs. His research lab actively engages in industrial partnerships with Cisco, Leonardo, and AGID (Italy’s Digital Agency).

• Numerical Analysis
• Partial Differential Equations
• Integral Equations
• +۳ مورد دیگر

Mario Annunziato is a Researcher in Mathematics at the Department of Physics, University of Salerno, since 2004. His work focuses on numerical methods for stochastic processes and optimal control. Institution: University of Salerno Department: Department of Physics Academic Rank: Researcher Research Interests include numerical solutions of PDEs and integral equations for stochastic processes, probability density function optimization, and modeling random phenomena. His work addresses positivity, monotonicity, and conservation in discrete PDFs. Article Trends span stochastic control frameworks, computational finance, biophysics applications, and numerical methods for jump-diffusion processes. Key topics involve Fokker-Planck equations, Hamilton-Jacobi-Bellman formulations, and splitting methods. Advising and Grants include teaching Numerical Analysis until 2013 and securing funding from the University of Salerno's FARB program, INdAM-GNCS, and the European Science Foundation's OPTPDE grants. He participated in the STRIKE Marie Curie ITN network. Labs & Teams : Collaborated with Prof. Alfio Borzì at Würzburg University and contributed to open-source tools like MATLAB Central File Exchange for PDP solvers.

• Marine Renewable Energy
• Offshore Engineering
• Fluid-Structure Interaction
• +۵ مورد دیگر

Giuseppe Giorgi is a fixed-term researcher at the Department of Mechanical and Aerospace Engineering (DIMEAS), Politecnico di Torino. He serves as Scientific Coordinator for multiple EU-funded projects including MERMAIDS, BLUE-X, and AIMS, and leads commercial research contracts for offshore wind microclimate studies. Research focuses on hybrid offshore platforms integrating Floating Offshore Wind Turbines (FOWTs) with Wave Energy Converters (WECs) Expertise in nonlinear hydrodynamics , fluid-structure interaction , and experimental validation through lab tests and sea trials Research Interests : Marine Renewable Energy Systems Nonlinear Dynamic Modeling Mechanical and Techno-Economic Optimization Hybrid Wind-Wave Energy Platforms Parametric Resonance Energy Harvesters Scientific Achievements : 2022: IFAC CAMS Best Paper Award 2022: Institution of Civil Engineers - Baker Medal 2022: AIMETA Junior Mechanics of Machines Award 2023: IFToMM Bronze Best Student Paper Award Academic Leadership includes supervising 6 PhD students and teaching Numerical Modeling of Marine Energy Converters (PhD level). His 15 most recent publications focus on wave energy converter optimization, floating wind turbine dynamics, and hybrid offshore energy systems with applications in the Mediterranean Sea and North Sea.

• Complex Systems Dynamics
• Information Theory
• Neuroscience
• +۵ مورد دیگر

Leonardo Ricci is an Associate Professor at the Department of Physics, University of Trento , with a 28-year teaching career spanning 56 courses (31 in English) and extensive roles in the Interdepartmental Center for Mind/Brain Sciences - CIMEC (30% affiliation). His research bridges nonlinear dynamics , information theory , and neuroscience , focusing on chaos detection in time series and entropy analysis. Academic Career : From 1994 post-doc at Max-Planck-Institut to 2022 promotion to Associate Professor Teaching : Courses in Experimental Physics, Advanced Electronics, and Statistical Methods across Physics and Computer Science programs Ricci leads the NSE Lab (Nonlinear Systems and Electronics) , developing hardware/software systems for experimental research. His 2022 Entropy cover story on permutation entropy highlights his impact in information theory. Scientific Contributions : 20 patents (visibility measurement devices), collaborations with international researchers on complex systems Editorial Roles : Associate Editor for Chaos, Solitons & Fractals and Frontiers in Network Physiology

• Optimal Transport
• Partial Differential Equations
• Mean Field Games
• +۳ مورد دیگر

Alpár R. Mészáros is a Full Professor at Durham University's Department of Mathematical Sciences. His research focuses on optimal transport, partial differential equations, and mean field games. He has organized conferences such as the 2025 Durham Symposium on Mean Field Games and contributed to events like the LMS Invited Lecture Series in 2023. Mészáros holds a PhD in Mathematics and has authored numerous papers on topics including displacement monotonicity, master equations, and cross-diffusion systems. His work bridges theoretical mathematics with applications in control theory and stochastic processes. Education: PhD thesis on A variational approach to second order mean field games with density constraints (2015), MSc thesis on BV Estimates in Optimal Transportation (2015). Research interests span optimal transport theory, nonlinear PDEs, and their interplay with game theory and probability. Key contributions include analysis of mean field games master equations, convergence rates for particle systems, and well-posedness results for Hamilton-Jacobi-Bellman equations. His publications reflect a focus on monotonicity conditions, conservation laws, and stabilization in dynamic systems. Collaborations include work with leading researchers like Wilfrid Gangbo, Filippo Santambrogio, and Charles Mou. He actively contributes to the academic community through organizing workshops and advancing theoretical frameworks in applied mathematics.

• Biochemistry
• Biotechnology
• Enzymology
• +۶ مورد دیگر

Silvia Holler is a Researcher (RTD-A) at the Department of Cellular, Computational, and Integrative Biology (CIBIO) at the University of Trento. She specializes in biochemistry, biotechnology, and synthetic biology with a focus on enzymology, catalysis, and structural biology. Her work spans experimental and computational studies of protocells, droplet-based systems, and self-organizing soft matter. Teaching responsibilities include co-teaching the Biochemistry course at CIBIO, where she collaborates with scholars like Giovanni Piccoli and Martin Michael Hanczyc. The course covers foundational topics in biochemistry, enzymology, and molecular structures with practical skills in chromatography and enzymatic kinetics. Research interests emphasize artificial life systems, droplet engineering, and the physics of biological organization. Key themes include protocell formation, compartmentalized biochemistry, and ethical implications of synthetic biology innovations. Recent work explores self-organized patterns in soft matter, active matter dynamics, and computational modeling of multi-phase systems. Publications focus on droplet microfluidics, vesicle interactions, and agglomeration phenomena across scales. Collaborative efforts include editorial roles for artificial life conference proceedings and interdisciplinary projects combining biophysics with materials science. No scientific awards were explicitly mentioned in the provided materials. Her research lab activities are embedded within CIBIO's facilities, focusing on experimental setups for droplet-based synthetic biology and computational simulations of complex systems.