Find Academic Supervisors

• Civil Engineering
• Structural Engineering
• Machine Learning in Structural Engineering
• +4 more

Giuseppe Carlo Marano is a Full Professor at the Department of Structural, Building and Geotechnical Engineering at Politecnico di Torino. He is also a component of the SISCON Interdepartmental Center for Infrastructure Safety. With expertise in civil and structural engineering, his work focuses on machine learning applications, seismic risk reduction, and sustainable structural optimization. Education Graduated cum laude in Structural Engineering from Polytechnic University of Bari PhD in Structural Engineering from University of Florence (2000) Research Interests Marano's research spans structural optimization, seismic engineering, and machine learning applications in civil infrastructure. He develops advanced computational models for: Seismic retrofitting of existing structures Optimization of steel and masonry structures Recycled materials in concrete production AI-driven structural health monitoring Multiobjective design methodologies Publication Trends His recent work emphasizes: Machine learning for concrete mix design and damage assessment Optimization of gridshells and arch structures Seismic isolation systems and vibration control Sustainable construction practices with recycled materials Multiobjective genetic algorithms for structural design Scientific Recognitions National Scientific Qualification - First Band (2013, MIUR Italy) Certificate of Appreciation for Outstanding Lecture (2012, China) Academic Contributions As an educator, he teaches: Consolidamento Strutturale (Structural Consolidation) Dinamica delle Vibrazioni Random (Random Vibration Dynamics) Progettazione Generativa (Generative Design) He also leads Challenge@PoliTo initiatives and contributes to national infrastructure safety regulations. Research Projects ADAPT4CE - Adaptive Digital Systems for Circular Economy (2025-2028) AI-ENVISERS - AI for Seismic Retrofit Environmental Impact (2023-2025) ADDOPTML - Additive Manufacturing Optimization (2021-2025)

• Hydraulic Engineering
• Hydrology
• Computational Hydraulics
• +6 more

Alessia Ferrari is a fixed-term researcher in the Department of Engineering and Architecture at the University of Parma, Italy. She lectures on Hydrology within the Bachelor’s degree programme in Civil and Environmental Engineering and serves as the reference teacher for the same programme across multiple academic years (2020/2021 – 2025/2026). Research Focus Ferrari’s research integrates advanced numerical modelling with real-world flood-risk management. Key themes include: High-resolution 2-D shallow-water simulations using GPU-parallel codes. Porosity-based approaches for large-scale urban flood modelling. Levee-breach hydraulics and emergency-action planning. Calibration of hydraulic models using tools such as PEST. Integration of machine-learning techniques with physics-based flood forecasting. Publication Trends Across more than 25 peer-reviewed works (2015-2025), Ferrari has concentrated on computational hydraulics applied to extreme flood events in Northern Italy (e.g., Parma 2014, Lamone 2024). Her papers consistently advance numerical schemes (ADER, HLLEM Riemann solvers) and GPU acceleration while validating models against field data, thereby bridging theoretical development and practical flood-mitigation strategies. Contact & Office E-mail: alessia.ferrari@unipr.it Office: Science and Technology Campus – Pavilion 10, Engineering Scientific Headquarters, Parco Area delle Scienze 181/A, 43124 Parma, Italy.

Daniele LoiaconoView profile

Associate Professor

• Artificial Intelligence
• Machine Learning
• Medical Imaging
• +6 more

Daniele Loiacono is an Associate Professor at Politecnico di Milano's Department of Electronics, Information, and Bioengineering (DEIB), affiliated with the Artificial Intelligence and Robotics Lab (AIRLab). His research focuses on interdisciplinary applications of Artificial Intelligence, Machine Learning, and Deep Learning in medical imaging, radiation therapy, and procedural content generation for games. He leads projects in synthetic image generation for radiotherapy quality assurance, automated treatment planning, and bias analysis in medical AI systems. Key research areas include medical image synthesis using GANs, radiation therapy optimization, and algorithmic game design. His contributions span clinical applications such as total marrow irradiation (TMI) planning and lymph-node segmentation, alongside innovations in shader generation and interactive evolutionary tools for game development. Loiacono collaborates on multi-center studies to validate AI-driven workflows in healthcare and has pioneered methods combining lean Six Sigma with machine learning for treatment process improvement. His work bridges clinical medicine and computer science, addressing challenges in radiation oncology, anatomical imaging, and procedural content automation. The AIRLab serves as a hub for his research, integrating AI advancements into real-world medical and engineering solutions.

• Structural Health Monitoring
• Seismic Analysis
• Bayesian Calibration
• +14 more

Gaetano Miraglia is a Fixed-term Assistant Professor in the Department of Structural, Building and Geotechnical Engineering (DISEG) at Politecnico di Torino, where he conducts research in structural health monitoring, seismic analysis, and computational modeling. He is a member of the Interdepartmental Center R3C – Responsible Risk Resilience Centre, contributing to interdisciplinary efforts in risk mitigation and infrastructure resilience. His work spans both theoretical and applied domains, with strong emphasis on heritage preservation and sustainable urban development. His research interests include Bayesian calibration of nonlinear models, hybrid simulation, peridynamics, masonry structures, and the integration of satellite interferometric (InSAR) data with in-situ measurements for structural monitoring. He applies advanced computational and machine learning techniques to improve the accuracy and reliability of structural assessments, particularly in historical and monumental buildings. His work supports UN Sustainable Development Goals 9, 11, and 13. His recent publications demonstrate a consistent focus on data fusion, digital twinning, domain adaptation, and real-time damage detection. He frequently collaborates with researchers such as Rosario Ceravolo and Erica Lenticchia, publishing in high-impact journals like Computer-Aided Civil and Infrastructure Engineering , Structures , and Scientific Reports , as well as at major conferences including EWSHM, SAHC, and EVACES. His research is applied in projects such as the monitoring of the Vicoforte Sanctuary and the development of the CAMELOT and HY-LEARN toolboxes. Research Projects: MONITORAGGIO VICOFORTE (2024–2026) – Member of Research Group CAMELOT – PoC Transition (2023–2024) – Member of Research Group HY-LEARN – Model Calibration via Hybrid Simulation and ML (2022–2024) – Scientific Manager (PNRR Mission 4) He teaches in various programs, including as a course collaborator in PhD, Master’s, and Bachelor’s level courses such as Earthquake Engineering , Structural Consolidation , and Seismic Risk of Cultural Heritage . He is also an inventor on national and international patents and software related to the CAMELOT toolbox, highlighting the translational impact of his research. He has no listed scientific awards or formal advisees in the provided text.

Guido PerboliView profile

Professor

• Operations Research
• Logistics
• Last-mile Delivery
• +9 more

Guido Perboli is a Full Professor in the Department of Management and Production Engineering (DIGEP) at the Polytechnic University of Turin, where he also serves as Logistics Coordinator and Project Coordinator for activities supporting relationships with government bodies. He is a member of the Interdepartmental Center CARS@PoliTO (Center for Automotive Research and Sustainable Mobility) and serves as Director of the ICT for City Logistics and Enterprises (ICElab@Polito) research center, which he founded in 2016. His research interests span a broad range of topics including Operations Research, Logistics, Last-mile Delivery, Sustainable Logistics, Combinatorial Optimization, Stochastic Programming, Business Development, and Lean Business methodologies. His work particularly focuses on City Logistics, Green Logistics, and the application of emerging technologies like Blockchain and AI in supply chain management. He has developed GUEST, a Lean Business methodology for innovation processes from early idea definition to implementation. Professor Perboli's recent publications demonstrate a strong focus on urban logistics, last-mile delivery optimization, blockchain applications in supply chains, and the integration of AI techniques in transportation systems. His work shows an increasing trend toward interdisciplinary research that combines optimization methods with emerging technologies to address sustainable urban mobility challenges. Professional Recognition: CASE Best Paper award from IEEE Conference on Automation Science and Engineering (2011) Effective member of INFORMS (2019-present) Effective member of EURO (1995-present) Effective member of AIRO (1995-present) Associate Editor for Journal of Applied Research and Technology (2020-present) Associate Editor for Sustainability (2018-present) Professor Perboli actively advises PhD students and has supervised numerous research projects, including EU-funded initiatives like SINFONICA, HESTER, and 5G-LOGINNOV. He serves as Scientific Director for multiple commercial research projects focused on blockchain, IoT, and AI applications in logistics. Beyond academia, he is Chief Scientific Officer of Arisk S.p.A., a fintech company specializing in business crisis prediction using AI and machine learning. His research group, ICElab@Polito, focuses on two main areas supporting urban growth: logistics and enterprises. The center collaborates with numerous companies including Amazon, DHL, and FCA, addressing real-world challenges in urban logistics and supply chain management through innovative research approaches.

• Physical Limnology
• Sediment Transport
• Tidal Hydrodynamics
• +3 more

Marco Toffolon is a Full Professor at the University of Trento's Department of Civil, Environmental and Mechanical Engineering, where he leads the Physical Limnology Laboratory. He serves as Deputy Director for International Relations and previously directed the Environmental Engineering programs. His research spans ecohydraulics, sediment transport, lake hydrodynamics, and environmental modeling. He investigates physical limnology, tidal morphodynamics, and stratified flows using analytical and numerical approaches. His work integrates field measurements with machine learning for water quality prediction and climate impact assessment. His publications focus on lake dynamics, river morphodynamics, and sustainable water management, with recent emphasis on climate-driven changes in alpine systems. Research demonstrates strong interdisciplinary linkages between hydraulics, ecology, and climate science. Awards: 2016 Coastal Engineering Journal Award 2013 Enrico Marchi Lecture invitation He leads international collaborations with institutions like EPFL and Sun Yat-sen University, and organizes conferences including the Physical Processes in Natural Waters workshop series.

• Structural Health Monitoring
• Machine Learning in Civil Engineering
• Earthquake Engineering
• +9 more

Marco Martino Rosso is a Research Fellow at the Department of Structural, Building and Geotechnical Engineering (DISEG) at the Polytechnic University of Turin, where he also serves as an external lecturer and teaching assistant in both DISEG and the Department of Mathematical Sciences (DISMA). He is affiliated with the Doctoral School (SCDOTT) and completed his PhD under the supervision of Professor Giuseppe Carlo Marano. His academic work bridges civil engineering with advanced computational methods, focusing on structural health monitoring, optimization, and machine learning applications. His research interests center on Structural Health Monitoring , Machine Learning in Civil Engineering , Earthquake Engineering , Structural Optimization , Operational Modal Analysis , and AI-driven diagnostics for infrastructure. He applies deep learning, neural networks, and hybrid modeling techniques to problems such as damage detection, post-earthquake assessment, tunnel and bridge monitoring, and dynamic analysis of timber and concrete structures. His recent publications, spanning from 2023 to 2025, demonstrate a strong trend toward integrating artificial intelligence with structural engineering, particularly in automating modal analysis, optimizing structural forms, and enhancing seismic resilience. These works appear in journals like Mechanical Systems and Signal Processing , Computers & Structures , and Bulletin of Earthquake Engineering , as well as in proceedings of international conferences such as IOMAC and EWSHM. Marco Rosso has not received any explicitly mentioned scientific awards in the provided text. However, his extensive publication record and active role in research projects indicate strong recognition in his field. He has contributed to teaching as a course collaborator in subjects including Dynamic Identification of Structures , Statistics , Construction Techniques , and Safety Assessment and Retrofitting of Structures . He has also been involved in the ARTISTE 2025 Summer School, indicating engagement in advanced training programs. While no formal lab or team name is specified, his frequent collaborations with researchers such as Angelo Aloisio, Giuseppe Carlo Marano, and Jonathan Melchiorre suggest he is part of a vibrant research group focused on intelligent structural systems and data-driven engineering at Politecnico di Torino.

• Structural Health Monitoring (SHM)
• Smart / self-sensing cementitious composites
• Bridge engineering and life-cycle assessment
• +6 more

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.

• Applied Geophysics
• Glaciology
• Geophysical Data Integration
• +3 more

Alberto Godio is a Full Professor at the Politecnico di Torino, affiliated with the Department of Environmental, Land and Infrastructure Engineering (DIATI). He coordinates Latin America relations under the University Strategic Plan and is a member of the Interdepartmental Center Photonext for Applied Photonics. His research focuses on Applied Geophysics, Geophysical Data Integration, and Glaciology. He graduated in Mining Engineering (1988) and earned a PhD in Underground Resources Engineering (1993). He has been an Associate Professor (2005-2024) and Full Professor (2024-present) at PoliTO, leading projects funded by EU (FP7, LIFE, Horizon), MIUR (PRIN, FIRB), and regional bodies. His recent publications explore geophysical methods for subsurface modeling, glacial systems, and environmental remediation, with keywords spanning Geophysics, Hydrology, and Climate Science. His work emphasizes ground-penetrating radar, seismic noise analysis, and hybrid modeling techniques. Scientific awards include the Best Paper Award at the Near Surface Geoscience Conference (2008). He has supervised PhD students on fiber optic sensors and GPR optimization, advised projects on digital twins, and led EU-funded research on biogas enhancement in landfills.

• Fluid Mechanics
• Sediment Transport
• Fluvial Morphodynamics
• +7 more

Marco Tubino is a Full Professor in the Department of Civil, Environmental and Mechanical Engineering at the University of Trento, where he serves as Department Director since 2012. Previously, he was Dean of the Faculty of Engineering (2005-2012) and has held academic positions since 1990, including Associate Professor at the University of Genoa before joining Trento in 1994. Education: 1977: Diploma di Maturità Classica, Liceo Statale "Andrea D'Oria", Genoa 1982: Laurea in Chemical Engineering (with honors), University of Genoa 1986: PhD in Hydrodynamics, University of Padua Research Focus: Tubino's work centers on fluid mechanics and fluvial morphodynamics , with expertise in sediment transport, tidal hydrodynamics, ecohydraulics, and environmental fluid mechanics. His research integrates field observations, mathematical modeling, and experimental studies to address river bifurcations, meandering dynamics, debris flows, and climate change impacts on alpine systems. Recent work emphasizes AI applications for river prediction and waste management sustainability. Publication Trends: His 2023-2025 publications reveal intensified focus on river bifurcation mechanics, permafrost-affected Arctic streams, and machine learning for meander migration prediction. Key themes include sediment partitioning in deltas, climate change impacts on fluvial systems, and life-cycle assessment of waste-to-energy technologies, reflecting growing interdisciplinary integration with environmental engineering. Scientific Recognition: Wiley-Blackwell Award for best paper in Earth Surface Processes and Landforms (2010) Academic Leadership: Tubino coordinates the Environmental Fluid Mechanics and Morphodynamics Research Group (GIAMT) and has directed Trento's PhD program in Environmental Engineering (2000-2007). He has secured numerous research grants for environmental impact studies, fluvial modeling projects, and international collaborations including dual-degree programs with Karlsruhe University. Research Infrastructure: Leads the GIAMT group specializing in experimental flume studies, numerical modeling of river systems, and field investigations of braided and meandering rivers, with recent expansions into AI-driven morphodynamic prediction and climate change impact assessment.

• Marine Renewable Energy
• Offshore Engineering
• Fluid-Structure Interaction
• +5 more

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.

• 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.

• Aerospace Engineering
• Aeroelasticity
• Fluid-Structure Interaction
• +3 more

Prof. Mastroddi Franco is a Full Professor at the Department of Mechanical and Aerospace Engineering (DIMA) of Sapienza University of Rome, affiliated with the Faculty of Civil and Industrial Engineering. His expertise spans aerospace engineering, aeroelasticity, and multidisciplinary design optimization. He contributes to training programs such as the 2nd-level Master's in 'Satellites and Orbiting Platforms' and 'Energy Efficiency and Renewable Energy Sources'. His research focuses on fluid-structure interactions, sloshing dynamics in aircraft tanks, and sustainable aircraft design. He has led studies on green aviation technologies, launch vehicle aerodynamics, and numerical modeling techniques like Smoothed Particle Hydrodynamics (SPH). Research Interests: Aeroelastic Stability and Response Hydrogen-Powered Aircraft Systems Neural Network Applications in Fluid Dynamics Green Energy Integration in Aviation Reduced-Order Modeling for Complex Systems Publications highlight contributions to sloshing dynamics, hybrid aircraft design, and computational methods for hypersonic systems. Awards: None explicitly mentioned. Grants and advisory roles include participation in the 'Premio Liviu Librescu' thesis award committee (2010). He collaborates on projects involving structural damping models and multi-objective optimization for aerospace systems.

• Structural Engineering
• Earthquake Engineering
• Structural Dynamics
• +8 more

Rosario Ceravolo is a Full Professor in the Department of Structural, Building and Geotechnical Engineering (DISEG) at the Polytechnic University of Turin , where he conducts cutting-edge research in structural dynamics, earthquake engineering, and structural health monitoring with a focus on architectural heritage. He is a member of the Interdepartmental Center R3C (Responsible Risk Resilience Center) and the University Quality Assurance Committee, reflecting his leadership in academic and research governance. His research interests include: Dynamic identification of structures Seismic assessment and protection of cultural heritage Structural health monitoring (SHM) Natech (natural-technological) risk Earthquake engineering and structural control His recent publications demonstrate a strong trend toward integrating advanced computational techniques, satellite data, and experimental monitoring for assessing historical and modern structures. Key themes include modal tracking, digital twinning, ferrocement durability, and data fusion for heritage conservation. His work bridges civil engineering and heritage science, often involving interdisciplinary collaborations. Scientific Awards and Recognitions: Keeping it Modern Implementation Grant, Getty Foundation (2019) Fellow, ICOMOS (2024–) Fellow, ISCARSAH (2014–) Fellow, American Society of Civil Engineers (1999–) Evaluator, Rita Levi Montalcini Program (2018) Advising and Grants: He supervises multiple PhD students in architectural and civil engineering programs and leads several major research initiatives, including EU-funded and national projects such as REcube (Erasmus+), OPTIMISE, SAT4SHM, and CAMELOT. He serves as Scientific Director for numerous research contracts with public and private institutions, including long-term monitoring projects at the Vicoforte Sanctuary and Torino Esposizioni. Research Labs and Teams: He leads activities in the Dynamics and Seismic Laboratory (DISEG) and is involved in research networks such as ICOMOS-ISCARSAH and IASS-WG17, fostering international collaboration in structural analysis and heritage conservation.

Patrizia SaviView profile

Associate Professor

• GNSS Reflectometry
• Microwave Characterization of Materials
• Graphene Nanoplatelets
• +3 more

Patrizia Savi is a Tenured Associate Professor at the Polytechnic University of Turin within the Department of Electronics and Telecommunications. She actively participates in the Power Electronics Innovation Center (PEIC) and serves as a Senior Member of IEEE and the International Union of Radio Science . Teaching: She has been the Titolare del corso for 'Campi Elettromagnetici' (Electromagnetic Fields) since 2019-2021 at the Polytechnic University of Turin. Key Collaborations: Works with researchers across Italy and international institutions on projects involving GNSS-R for environmental monitoring. Research Interests: Her work focuses on GNSS Reflectometry for soil moisture retrieval, carbon-based composites (graphene, biochar, nanotubes) for microwave applications, and graphene tunable devices including biosensors. She also explores electromagnetic shielding using sustainable materials. Recent Publication Trends: Recent work emphasizes machine learning integration with GNSS-R data, biochar composite shielding in construction materials, and graphene-based biosensors for glucose and HRP detection. Key applications span climate action , environmental monitoring , and medical diagnostics . Scientific Awards: IEEE Fellow (2016-) IEEE Senior Member (2016-) International Union of Radio Science Senior Member (2024-) Advising: Supervises PhD students Simone Gaetano Ballaera and Fabio Peinetti , focusing on graphene sensors and tunable devices.