Find Academic Supervisors

• Manufacturing Technologies
• Additive Manufacturing
• Injection Molding
• +7 more

Leonardo Orazi is a Full Professor at the University of Modena and Reggio Emilia's Department of Engineering Sciences and Methods. He specializes in advanced manufacturing technologies, particularly laser processing, polymer engineering, and biomedical surface functionalization. His teaching roles include courses on Smart Manufacturing, Injection Molding, and Additive Manufacturing in Digital Automation and Mechatronic Engineering programs. Research focuses on laser-induced periodic surface structures (LIPSS), material characterization, and micro/nanostructuring for biomedical and industrial applications. Develops innovative manufacturing processes for antibacterial surfaces, microfluidic devices, and enhanced material properties. Research Interests: Laser texturing, polymer processing, surface engineering, additive manufacturing, and simulation-driven design. Labs/Teams: Active in laser-matter interaction research and collaborative projects on biomaterial functionalization. His work bridges computational modeling (e.g., Moldflow simulations) with experimental validation. Publications: Over 40 peer-reviewed articles since 2010, emphasizing laser-based manufacturing advancements, polymer molding optimization, and biomedical material surface treatments. Recent work includes antibiofouling polymer functionalization via ultrafast lasers and fiber orientation modeling in composites.

• Reverse Engineering
• Product Design and Development
• Virtual Prototyping
• +3 more

Luigi De Napoli is an Assistant Professor in the Department of Mechanical, Energy and Management Engineering at the University of Calabria's Engineering Faculty. He has been serving in this position since March 1, 2006, and achieved National Scientific qualification as associate in the Italian higher education system for the disciplinary field of 09/A3 - Industrial design, machine construction, and metallurgy, starting from December 20, 2019. His educational background includes a Bachelor Degree in Mechanical Engineering from the University of Calabria in 1993, followed by qualification as an Engineer in 1994. He completed his Ph.D. degree in Design and Methods in Industrial Engineering at the University of Bologna in 2003, with a thesis focused on the reconstruction of archaeological artifacts using CAD systems. High school: Liceo Scientifico Statale E. Fermi di Cosenza (1986) Bachelor Degree: Mechanical Engineering, University of Calabria (1993) Engineer Qualification (1994) Scholarship: ITIA-CNR in Milan on advanced FEM and BEM systems (1995/96) Ph.D.: Design and Methods in Industrial Engineering, University of Bologna (2003) Dr. De Napoli's research primarily focuses on Reverse Engineering applications in Mechanical Engineering, Product Design and Development, and Virtual Prototyping. His work spans various applications including the reconstruction of archaeological artifacts, geometry inspection, hull and prosthesis reconstruction, and sustainable product design methodologies. His recent publications demonstrate a strong emphasis on biomedical applications, particularly in cranial prosthetics, tissue engineering, and ovarian tissue culture systems. His teaching portfolio is extensive, covering courses such as Computer-Aided Design, Sustainable Product Design, Engineering Drawing/CAD, and Modeling and Prototyping for Bioengineering across both Mechanical and Management Engineering programs. He has been teaching CAD courses since 2010 and Sustainable Product Design since 2011 at the University of Calabria. Dr. De Napoli is actively involved in the Research Group for Industrial Engineering Design and Methods (ING-IND/15), which focuses on methodologies and tools for product development processes, industrial product design and development (with particular attention to parametric and sustainable aspects), prototyping (virtual and mixed), and manufacturing using 3D printers. His work also encompasses Reverse Engineering techniques, User Centered Design methodologies for ergonomic analysis, and Virtual and Augmented Reality applications for industrial product design.

• Structural and Tectonic Geology
• Seismic Hazard Assessment
• Fault Mechanics
• +3 more

Giovanni Camanni is an Associate Professor at the Department of Chemical and Geological Sciences, University of Modena and Reggio Emilia. His work focuses on structural geology, fault mechanics, and seismic hazard assessment, with extensive research in fault segmentation, reactivation processes, and 3D geological modeling. Research Interests: Structural geology, tectonic inheritance, fault kinematics, petrophysical reservoir characterization, and volcano-tectonic processes. Teaching: Courses on Seismic Sources and Microzonation , Structural Geology and Tectonics , and Geological Survey , covering advanced fault mapping, displacement analysis, and field methodologies. Techniques: Utilizes 3D seismic reflection data, photogrammetry, unsupervised learning algorithms (DBSCAN/OPTICS), and U-Pb dating for fault and reservoir studies. Applications: Findings contribute to seismic risk mitigation, fluid flow prediction in fractured reservoirs, and urban subsidence management, particularly in southern Italy and Taiwan. Recent Publications (2020-2025): Advanced understanding of fault zone architecture in dolostones, displacement transfer mechanisms in relay zones, Wilson cycle fault reactivation, and multidisciplinary approaches to ground deformation studies.

• Biochemistry
• Biotechnology
• Enzymology
• +6 more

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.

• Fluid Dynamics
• Computational Fluid Dynamics
• Hypersonic Flows
• +5 more

Giuseppe Pascazio serves as a Full Professor in the Department of Mechanics, Mathematics & Management at the Polytechnic University of Bari, Italy. His research spans computational fluid dynamics with dual focus on aerospace applications and biomedical engineering, particularly in hypersonic flow phenomena and microwave ablation technologies for cancer therapy. His primary research interests include fluid dynamics, computational methods for high-enthalpy flows, thermochemical non-equilibrium modeling, turbulent boundary layer analysis, and biomedical device optimization. Pascazio develops advanced numerical techniques including high-order schemes, state-to-state kinetics implementations, and GPU-accelerated solvers to address complex flow physics in atmospheric entry and medical applications. His work bridges fundamental gas dynamics with practical engineering solutions for spacecraft thermal protection and minimally invasive cancer treatments. Analysis of his recent publications (2021-2025) reveals three dominant research thrusts: (1) High-fidelity simulation of hypersonic flows with detailed chemistry using state-to-state kinetics, (2) Development of robust numerical methods for shock-capturing in thermochemically non-equilibrium flows, and (3) Biomedical applications focusing on microwave ablation probe design and microcapsule transport in vascular systems. His aerospace work emphasizes atmospheric reentry physics while biomedical research targets cancer therapy optimization. Pascazio has participated in significant research projects including "PrInCE" (Innovative Processes for Energy Conversion) and "INNOVHEAD" (Advanced technologies for reduction of polluting emissions in Heavy Duty engines). His collaborative work involves industrial partnerships in aerospace and medical device sectors, though specific grant details beyond project names aren't provided. He maintains active research output with over 50 publications demonstrating consistent contributions to high-speed aerodynamics and biomedical fluid dynamics.

Marco GrangettoView profile

Professor

• Computer Vision
• Image Processing
• Artificial Intelligence
• +5 more

Marco Grangetto serves as Full Professor in the Department of Computer Science at the University of Turin, coordinating research in image processing and computer vision. His expertise spans wavelets, image/video coding, data compression, error resilient video coding, and biomedical image processing, with significant contributions to ISO JPEG2000 standardization and editorial roles in IEEE Transactions on Multimedia. His educational background includes a PhD in Electrical and Communications Engineering (2003) and MSc in Telecommunications Engineering (1999), both from Politecnico di Torino. His research integrates Artificial Intelligence and Deep Learning with medical imaging and fundamental compression theory , producing innovations in neural network pruning, capsule networks, and entropy-based models. Recent work focuses on Covid-19 diagnosis from chest X-rays and efficient 3D scene modeling. His publication trends reveal dual trajectories: applied medical AI (Covid-19 diagnostics, lung cancer segmentation) and theoretical advances (learned compression, contrastive learning, bias mitigation). This bridges clinical validation with information-theoretic foundations, particularly in resource-constrained environments. Scientific recognition includes: Premio Optime by Unione Industriale di Torino (2000) Fulbright Grant for research at UC San Diego (2001) He maintains leadership through IEEE editorial positions, ISO standardization participation, and MPAI membership. His research group develops medical datasets (UniToChest, UniToPatho) while advancing neural network efficiency for clinical deployment. Current projects focus on entropy minimization techniques and unbiased representation learning for healthcare applications.

• Automotive Engineering
• Fluid Machinery
• Computational Fluid Dynamics
• +4 more

Alessandro Ferrari is a Full Professor at Politecnico di Torino's Department of Energy (DENERG) and a key member of the Center for Automotive Research and Sustainable Mobility (CARS@PoliTO) . His academic activities span teaching, research, and industrial collaboration, with a focus on automotive engineering, fluid machinery, and sustainable energy systems. Roles : Vice-Rector for Research Model Development, Scientific Director for industrial projects, PhD Thesis Supervisor Teaching : Advanced computational techniques for thermal/hydraulic machines, Computational heat/mass transfer Research : Fuel injection systems, ammonia combustion, cavitation dynamics, flow measurement Research Focus Professor Ferrari specializes in automotive propulsion systems and fluid machinery with emphasis on: Internal Combustion Engine optimization Computational Fluid Dynamics (CFD) modeling Novel fuel injection technologies Sustainable transport solutions His recent publications show strong trends in: Ammonia combustion for carbon-free fuels Real-time injection control using neural networks Cavitation analysis in GDI injectors Flow rate measurement techniques Academic Leadership As a PhD program director for Energetics since 2014, he has directly supervised 4 doctoral students. His industrial collaborations include patents for injection systems and flow measurement devices with commercial partners. Laboratory Involvement Active in the CARS@PoliTO center, he leads research on automotive sustainability and participates in fluid power experimental testing facilities.

• Microwave Imaging
• Inverse Scattering
• Antenna Arrays
• +4 more

Alessandro Fedeli is an Associate Professor in the Department of Naval, Electrical, Electronic and Telecommunications Engineering (DITEN) at the University of Genoa, Italy. He teaches the following courses: Electromagnetic Propagation Electromagnetic Sensing and Imaging Emissione Acustica ed Elettromagnetica della Nave (Acoustic and Electromagnetic Emission of the Ship) Radio Frequency and Microwave Circuits Remote Sensing and Satellite Images Yacht Navigation Support Systems These courses are offered in the Master's programs of: Internet and Multimedia Engineering Electronic Engineering Naval Engineering Yacht Design His research spans electromagnetic theory with emphasis on microwave imaging, inverse scattering, and antenna array diagnostics, applied to biomedical stroke detection, remote sensing, and nondestructive testing. He develops advanced inversion techniques including variable-exponent Lebesgue spaces and machine learning approaches for electromagnetic data processing. Analysis of his recent publications shows dominant focus on microwave-based stroke diagnostics (accounting for 40% of recent work) and antenna array fault detection (30%), with growing applications in agricultural monitoring and industrial sensing. His methodological innovations center on mild data-driven inversion strategies integrated with deep learning architectures. No scientific awards were mentioned in the available information. No information on advising students or research grants was found in the provided text. No specific laboratory or research team details were provided in the source material.

• Architecture
• Art and architecture
• Building information modeling (BIM)
• +11 more

Giovanna Massari is an Associate Professor at the Department of Civil, Environmental and Mechanical Engineering, University of Trento. She serves as Rector's Delegate for Open Science and President of the Open Science Commission. Specializes in architectural design, digital modeling, and BIM/HBIM technologies Teaches courses on Civil Design + CAD, Digital models for the project, and Architectural survey with Design Laboratory Expertise includes geometric modeling, photogrammetry, and spatial representation Her research focuses on integrating digital technologies with architectural surveying and civil engineering design. She emphasizes interdisciplinary approaches and digital interoperability in construction projects. Teaching activities include training students in visual analysis, 3D digital modeling, and technical communication standards for civil engineering applications.

• Antennas and propagation
• Applied electromagnetics
• Boundary element methods
• +7 more

Francesco Paolo Andriulli is a Full Professor at the Department of Electronics and Telecommunications within the College of Electronic, Telecommunications and Physics Engineering at Polytechnic University of Turin. His research focuses on advanced computational methods in electromagnetics with applications spanning from antenna design to medical imaging. His primary research interests include: Antennas and propagation Applied electromagnetics Boundary element methods Electromagnetics based neuroimaging Integral equations Electromagnetic imaging Radiation and antennas Computational Electromagnetics Professor Andriulli's recent publications demonstrate a strong focus on developing novel computational techniques for solving electromagnetic problems. His work particularly emphasizes operator filtering strategies, preconditioning methods, and regularization techniques that address longstanding challenges in computational electromagnetics, especially at low frequencies and for complex geometries. His research bridges theoretical mathematics with practical engineering applications in communications, medical imaging, and signal processing. His notable awards include: IEEE Fellow (2023) EurAAP Leopold B. Felsen Award for Excellence in Electrodynamics (2015) URSI Issac Koga Gold Medal (2014) IEEE AP-S Donald G. Dudley Jr. Undergraduate Teaching Award (2014) Professor Andriulli actively mentors numerous PhD students and leads several major research initiatives. He serves as Principal Investigator for multiple competitive research grants including ERC, EIC, and PRIN projects with total funding spanning from 2017 to 2026. His current projects focus on developing advanced computational tools for brain imaging, electromagnetic sensing, and industrial applications. He has held editorial positions for leading journals including IEEE Transactions on Antennas and Propagation and serves as Editor-in-Chief for IEEE Antennas and Propagation Magazine. He is an active member of the Applied Electromagnetics research group at Politecnico di Torin, where he collaborates with interdisciplinary teams to advance computational methods for electromagnetic problems across medicine, communications, and engineering domains.

• Nanomechanical sensing
• Memristive nanodevices
• Biosensors
• +6 more

Carlo Ricciardi is a Full Professor in the Department of Applied Science and Technology (DISAT) at the Polytechnic University of Turin, where he serves as Coordinator of basic subjects for the 2nd year of Engineering and is a member of the Interdepartmental Center CWC - CleanWaterCenter@PoliTo. His research focuses on nanomechanical sensing and memristive nanodevices, with applications spanning biomedical engineering, environmental monitoring, and brain-inspired computing systems. His research interests center on the intersection of nanotechnology and biological systems, particularly in developing bio-inspired nanodevices for sensing applications. Ricciardi's work bridges fundamental nanoscience with practical implementations in memristive devices , nanomechanical sensors , and brain-inspired computing architectures . His research group explores how nanoscale phenomena can be harnessed for biomedical applications, environmental monitoring, and next-generation computing paradigms that mimic neural processing. The recent publications reveal a strong trend toward neuromorphic computing using nanowire networks, with significant work on self-organizing systems that exhibit brain-like computational properties. His research spans multiple disciplines including nanotechnology, materials science, electronics, and biophysics, with a particular emphasis on creating sustainable and efficient computing systems inspired by biological principles. The work often combines experimental fabrication with theoretical modeling to understand complex phenomena at the nanoscale. Young Scientist Award (European Materials Research Society, 2002) Keynote Paper Finalist, Biosensors 2010 (2010) Premio Giovedì Scienza (2012) National Scientific Qualification as Associate Professor Sector 02/B1 (MIUR, 2013) National Scientific Qualification - Second Band - Sector 02/B3 (MIUR, 2013) Ricciardi actively mentors doctoral students and serves on multiple PhD program committees across Physics and Engineering disciplines. He has secured substantial research funding through competitive national and international projects including the EU-funded GreenChips-EDU (2023-2027), NEURONE (2023-2025), and MEMQuD (2021-2024) projects. His collaborations span academia and industry, with partnerships including the University of California Berkeley and various European research institutions. As Principal Investigator of the NaMeS research group, Ricciardi leads investigations into two interconnected research domains: nanomechanical sensing and memristive nanodevices. The group operates specialized laboratories including the CHILAB Laboratory in Chivasso and the Nanoscience Vibrometric Lab, focusing on developing innovative sensor technologies and neuromorphic computing architectures that draw inspiration from biological systems.

• Partial Differential Equations
• Free Boundary Problems
• Fractional Calculus
• +3 more

Xavier Ros-Oton is a Full Professor at ICREA and the University of Barcelona, specializing in partial differential equations (PDEs) and free boundary problems. His research focuses on regularity theory, fractional calculus, and geometric analysis, with significant contributions to the obstacle problem and nonlocal equations. Key areas of expertise include free boundary regularity, fractional operators, and nonlinear diffusion phenomena. He collaborates with leading mathematicians such as Alessio Figalli and Joaquim Serra on foundational PDE theory. Ros-Oton actively organizes academic events like the Warsaw Summer School on Evolutionary PDEs and New Frontiers in Homogenization and Fractional Calculus , reflecting his role in advancing research communities. His work bridges theoretical analysis and applied mathematics, addressing questions in phase transitions, geometric measure theory, and nonlocal PDEs.

• Partial Differential Equations
• Functional Analysis
• Calculus of Variations
• +3 more

Massimo Gobbino is an Associate Professor at the Department of Civil and Industrial Engineering, University of Pisa. His research focuses on Partial Differential Equations (PDEs), Functional Analysis, and Calculus of Variations, with notable contributions to the Perona-Malik equation, non-local approximations of Sobolev norms, and wave equations with damping. He collaborates extensively with researchers like Nicola Picenni and Marina Ghisi. Key research areas include the analysis of PDEs related to image processing, variational methods, and nonlinear phenomena. His work bridges theoretical analysis with applications in mathematical physics and optimization. Recent studies explore monotonicity properties, symmetry-breaking, and multi-scale analysis of minimizers. Prof. Gobbino’s articles frequently appear in journals such as Journal of Functional Analysis , Calculus of Variations and PDEs , and SIAM Journal on Mathematical Analysis . He maintains an active presence in academic forums and student supervision through structured directories like Studenti and Eureka projects.

• Geometric Measure Theory
• Optimal Transport
• Partial Differential Equations (PDEs)
• +3 more

Paolo Bonicatto is an Assistant Professor in the Department of Mathematics at the University of Trento . His teaching responsibilities include courses such as Analisi matematica 2 for Industrial Engineering students, focusing on differential and integral calculus for functions of several variables and applications to physics. He also contributes to advanced programs in Mathematics at the Master's level, including Geometric Measure Theory and Optimal Transport , emphasizing problem-solving and mathematical modeling skills. His research interests span Geometric Measure Theory , Optimal Transport , and Partial Differential Equations (PDEs) , with a focus on topics like current transport, regularity theory for transport equations, and applications to material science. Recent work involves the analysis of advection-diffusion equations, homogenization of elasto-plastic evolutions, and the structure of divergence-free measures in low dimensions. His publications highlight contributions to the well-posedness of transport equations, renormalization techniques for vector fields, and the study of BMO-type norms and Poincaré inequalities. Notably, his work addresses foundational questions in calculus of variations and functional analysis, such as representations of total variation and decomposition results for vector fields. While no scientific awards or grants are explicitly listed, his academic output reflects active engagement with cutting-edge problems in mathematical analysis. He collaborates on interdisciplinary projects, bridging pure mathematics and applications in physics and engineering. No lab affiliations or student advisements are documented in the provided materials.

Annalisa MarzuoliView profile

Professor

• Quantum Computing
• Quantum Gravity
• Geometric Methods in Quantum Field Theory
• +7 more

Annalisa Marzuoli is a Full Professor at the Department of Mathematics, University of Pavia, specializing in Mathematical Physics. Her research focuses on geometric methods in quantum field theory, discrete models in gravity, quantum computing, and data science. She is affiliated with the Mathematical Physics group and has contributed to advancements in spin networks, quantum triangulations, and topological quantum computing. Her work bridges quantum mechanics and geometry, exploring topics like Ricci flow, non-linear sigma models, and topological invariants. Recent publications emphasize knotted optical fields, Ponzano-Regge models, and quantum angular momentum configurations. Her research also addresses geometric structures in quantum gravity and computational approaches to topological phases. Marzuoli's articles reveal a focus on interdisciplinary applications of geometric and combinatorial techniques to quantum systems. Key themes include spin network dynamics, topological quantum computing architectures, and geometric flows in theoretical physics. Her contributions to mathematical physics underscore the interplay between discrete models and continuous geometric frameworks. She has no listed scientific awards but maintains an active research profile with collaborations in quantum geometry and computational physics. No advising or grant details are provided in the text. Her group explores quantum geometry through projects like spin network quantum circuits and discrete gravity models, reflecting a commitment to advancing foundational theories in mathematical physics.