جست‌وجوی استاد و پژوهشگر

• Data Logistics
• Exascale Computing
• High Performance Computing
• +۷ مورد دیگر

François Bodin is a Professor at University of Rennes 1, actively involved in research at IRISA (Institut de Recherche en Informatique et Systèmes Aléatoires). He leads the Logica research team which focuses on data logistics—developing methods to organize distributed processing chains while considering technical performance, environmental sustainability, data governance, and long-term viability. His work spans multiple interdisciplinary projects including AQMO for air quality monitoring, RUDI for metropolitan open data platforms, and Numpex for Exascale computing. His research interests primarily focus on: Data Logistics and Distributed Processing Systems Exascale and High Performance Computing Sustainable and Energy-Efficient Computing Practices Open Data Platforms for Smart City Applications Parallel Programming and Software Optimization Professor Bodin's recent work demonstrates a strong commitment to reconciling digital performance with environmental sustainability. His projects like AQMO (air quality monitoring) and RUDI (metropolitan data platform) showcase practical applications of his research in urban environments. The Numpex project represents his leadership in preparing French scientific and industrial applications for exascale computing capabilities. Notably, he has made a personal commitment to environmental sustainability by declaring 'For environmental reasons, starting the 01/01/2020 I will not take the plane anymore.' His scientific contributions span several key areas: Exascale computing preparation and software development Metropolitan open data platforms and governance Energy-efficient computing practices Astronomical data processing through the ECLAT laboratory Professor Bodin actively participates in research recruitment and collaborates with various institutions including CNRS, Inria, and industry partners to advance his field. His work bridges theoretical computer science with practical urban and environmental applications, making significant contributions to both academic research and real-world problem solving.

• Quantum Computing
• Machine Learning
• Parallel and Distributed Systems
• +۱ مورد دیگر

Giacomo Vitali is a Ph.D. candidate in Computer and Systems Engineering at the Politecnico di Torino , Department of Control and Computer Science (DAUIN), while also serving as a Lecturer at the same institution. His research focuses on Quantum Computing , Machine Learning , and Parallel and Distributed Systems . Education: M.Sc. in Physics of Fundamental Interactions (2018) from the University of Pisa Research: Pioneering hybrid quantum-classical algorithms for industrial applications, including BBQ-mIS and DEN models for graph problems and quantum hardware optimization Teaching: Contributing to courses on Quantum Hardware Design and Quantum Computing at the M.Sc. level, as well as undergraduate courses in Computer Science

Stefano Querمشاهده پروفایل

دانشیار

• Computer Science
• Electrical Engineering
• Formal Methods
• +۷ مورد دیگر

Stefano Quer is an Associate Professor at the Department of Control and Computer Science (DAUIN), Politecnico di Torino. He holds a PhD in Electronic Engineering from the same institution and has been affiliated with DAUIN since 1996. Researcher (1996-2000) Associate Professor (2000-present) Visiting Faculty at UC Berkeley (1994-1995) Research Interests His work spans Formal Verification BDD/SAT Techniques Embedded Systems Hardware/Software Co-Verification Parallel Computing with applications in VLSI CAD, industrial IoT, and energy-efficient systems. Recent articles focus on GPU-accelerated graph algorithms, wireless sensor calibration, and AI-driven test optimization. Scientific Awards Best Paper Award, IEEE EURO-DAC'94 Academic Contributions Supervised PhD students Lorenzo Cardone and Andrea Calabrese Member of DATE, ICSOFT Technical Program Committees Topical Advisor for Sensors MDPI 60+ publications in IEEE/ACM venues

Giovanni Coppiniمشاهده پروفایل

پژوهشگر

• Oceanography
• Climate Science
• Environmental Engineering
• +۳ مورد دیگر

Giovanni Coppini is a Principal Scientist and Director of the Strategic Program "Global Coasts as a New Frontier" at the Euro-Mediterranean Center on Climate Change (CMCC) Foundation, leading international efforts to develop integrated coastal ocean observation systems and climate adaptation solutions for vulnerable coastal communities. He co-chairs the GlobalCoast Network Memorandum of Understanding under the UN Decade of Ocean Science’s CoastPredict Programme and represents CMCC in the Decade Collaborative Centre for Coastal Resilience. PhD in Environmental Science from the University of Bologna 20+ years in operational oceanography Former director of CMCC’s Global Coastal Ocean and Ocean Predictions Divisions His research focuses on coastal resilience through machine learning applications, oil spill forecasting, search-and-rescue systems, and Digital Twin of the Ocean components. He has contributed to over 80 peer-reviewed publications and led the Mediterranean Monitoring and Forecasting Centre (Med-MFC) of the Copernicus Marine Service since 2015.

• Artificial Intelligence
• Bioinformatics
• Machine Learning
• +۷ مورد دیگر

Enrico Blanzieri is an Associate Professor at the University of Trento's Department of Information Engineering and Computer Science. His research focuses on artificial intelligence, bioinformatics, quantum computing, machine learning, and computational biology. He actively contributes to interdisciplinary projects such as Vitis OneGenE for gene network analysis and quantum machine learning pipelines. His teaching includes courses like Algorithms for Bioinformatics, Quantum Machine Learning, and Data Mining. Blanzieri's work bridges theoretical foundations and practical applications, with notable contributions in quantum annealing-based algorithms, gene network expansion using distributed computing, and socially-competent artificial agents. His research integrates computational methods with biological systems, addressing challenges in precision agriculture and systems biology. His recent publications emphasize quantum machine learning advancements, causal role attribution in gene networks, and ethical AI frameworks for language models. Collaborative projects include the GENE@HOME volunteer computing initiative for bioinformatics tasks. Blanzieri also engages in educational activities, supervising courses that blend theoretical computer science with real-world applications.

Juan David Guerrero Balagueraمشاهده پروفایل

پژوهشگر ارشد

• AI Accelerators
• GPU Reliability
• Fault Tolerance
• +۷ مورد دیگر

Juan David Guerrero Balaguera is a Research Fellow at Politecnico di Torino's Department of Automatic Control and Computer Science (DAUIN), affiliated with the CAD group. He holds a Ph.D. in Computer and Control Engineering from Politecnico di Torino (2024), advised by Prof. Matteo Sonza Reorda and Prof. Ernesto Sanchez. His research focuses on dependable hardware for safety-critical systems, including GPU reliability, fault tolerance, AI accelerators, and functional in-field testing. Prior to his Ph.D., he earned a Master's (2017) and Bachelor's (2013) in Electronics Engineering from Universidad Pedagógica y Tecnológica de Colombia, where he taught digital design, embedded systems, and FPGA-based image processing from 2014 to 2020. His research interests span advanced FPGA design, computational arithmetic for AI, fault effects analysis in GPUs, and reliability assessment of neural networks. Notable contributions include methods for generating self-test libraries (STLs) for GPUs, evaluating fault impacts on TCUs, and enhancing CNN robustness via dropout layer optimization. Education: Ph.D. in Computer and Control Engineering, Politecnico di Torino (2024) M.S. in Electronics Engineering, Universidad Pedagógica y Tecnológica de Colombia (2017) B.S. in Electronics Engineering, Universidad Pedagógica y Tecnológica de Colombia (2013) He has received the Ph.D. Quality Award (2023 and 2024) from Politecnico di Torino and Best Paper recognitions at DATE 2023 and DDECS 2021. His work bridges theoretical fault models with practical GPU testing methodologies, emphasizing real-world applications in AI and edge computing. Current teaching roles include collaborating on GPU programming (Master's level) and computer sciences courses (Automotive Engineering). Research collaborations involve exploring reliability trade-offs in split-computing DNNs and developing fault-aware design flows for AI accelerators.

Antonio Brogiمشاهده پروفایل

استاد

• Service Computing
• Cloud Computing
• Fog Computing
• +۴ مورد دیگر

Antonio Brogi is a Full Professor at the Department of Computer Science, University of Pisa. He leads the Service-Oriented, Cloud and Fog Computing (SOCC) research group and is actively involved in multiple editorial roles, including for Electronics , Heliyon Computer Science , and Journal of Computer Languages . His research focuses on cloud-edge computing, quantum software engineering, and formal methods for distributed systems. He chairs program committees for major conferences like ESOCC, ADAPTIVE, and IEEE ICWS. Research Interests: Service computing, fog computing, quantum software engineering, system coordination, resilience, and sustainability. He has pioneered declarative approaches for managing distributed systems and has contributed to frameworks like ECLYPSE and FREEDA. Teaching: Teaches Cloud Computing (BSc) and Advanced Software Engineering (MSc) at the University of Pisa. Supervises master's and bachelor's theses in related areas. Grants & Projects: Participated in EU-funded initiatives like SeaClouds and national projects DECLware and Through the Fog. Active in industry collaborations for cloud-edge infrastructure optimization.

Mihai Teodor Lazarescuمشاهده پروفایل

دانشیار

• Artificial intelligence
• Capacitive sensors
• Embedded software
• +۱۰ مورد دیگر

Dr. Mihai Teodor Lazarescu is an Associate Professor at the Department of Electronics and Telecommunications (DET), Politecnico di Torino , where he contributes to research and teaching activities. He is also a member of the PolitoBIOMed Lab (Biomedical Engineering Lab) and the Ambient Sensing and Processing research group. Scientific Affiliation: IEEE Member (2019-present) Editorial Roles: Guest Editor for SENSORS, ELECTRONICS, and ACM Transactions on Embedded Computing Systems His research interests focus on hardware acceleration for machine learning algorithms, particularly using FPGAs for data center and embedded applications. He works on high-level synthesis optimization flows, capacitive sensor design for indoor monitoring, and low-power embedded systems . His work intersects Internet of Things , Wireless Sensor Networks , and Machine Learning with applications in human localization, environmental monitoring, and industrial automation. Recent publications demonstrate expertise in neural network optimization , DSP resource sharing , and multi-FPGA allocation . His teaching spans Applied Electronics , Digital Electronic Design , and Embedded Systems Optimization across bachelor's and master's programs in Electronic Engineering and Computer Engineering . Patents: Noise cancellation for single-plate capacitive sensors Capacitive sensor for space change detection Projects: Scientific Manager for Horizon 2020-S2RJU project (2018)

• Operational Research
• Optimization Methods
• Logistics and Supply Chain Management
• +۷ مورد دیگر

Manuel Iori is a Full Professor at the Department of Engineering Sciences and Methods, University of Modena and Reggio Emilia (UNIMORE), Italy. His primary research focuses on operational research, optimization methods, and logistics systems. He specializes in vehicle routing problems, scheduling algorithms, and decision support systems with applications in industrial automation, healthcare, and service industries. Iori is actively involved in teaching advanced optimization courses for engineering students, emphasizing practical applications in data-driven decision-making and simulation. Research Interests: His work addresses complex optimization challenges such as multi-trip vehicle routing with time windows, scheduling under resource constraints, and tool switching in manufacturing systems. He integrates machine learning and metaheuristics to develop innovative solutions for logistics, production planning, and healthcare operations. Collaborations with industry partners (e.g., pharmaceutical distributors, printing companies) ensure practical relevance of his research. Teaching: Iori teaches courses like Optimization Methods for Data-Driven Engineering Processes , Models for Logistics and Production Optimization , and Methods and Algorithms for Optimization in Digital Industries . These courses combine theoretical foundations with hands-on labs using tools like Python, Xpress, and Anylogic. Key Contributions: He developed decision support systems for multi-trip routing in pharmaceutical distribution and supplier selection in facility management. His research on satellite scheduling and attended home delivery systems advances both theoretical and applied domains. As a member of CIRRELT (Canada), he collaborates on logistics optimization projects. Professional Activities: Iori’s work is reflected in over 80 peer-reviewed publications and contributions to conferences. He advises graduate students on optimization challenges and serves as a reviewer for top journals in operations research.

• Cryptography
• Coding Theory
• Algebra
• +۳ مورد دیگر

Alessio Meneghetti is a Professor at the Department of Mathematics, University of Trento. His research focuses on cryptography, coding theory, and information security, with applications to post-quantum cryptography, blockchain protocols, and secure distributed systems. He teaches courses such as Coding Theory and Applications, Cryptography, and Programming Lab, emphasizing practical implementations in Java and theoretical foundations. His work spans cryptographic primitives like threshold signatures, quantum-resistant algorithms, and consensus mechanisms. Key contributions include protocols like COB for Byzantine agreement and frameworks for group action-based multi-signatures. He has also explored quantum random number generation and linear codes' weight distributions. Publications highlight advancements in threshold cryptography, distributed key generation, and post-quantum signature schemes. His teaching integrates programming practices with mathematical rigor, preparing students for applied cryptography and computational mathematics.

• Hydraulics
• Computational Fluid Dynamics
• Turbulence Modeling
• +۶ مورد دیگر

Enrico Napoli is a Full Professor in the College of Engineering at the University of Palermo, where he has been since 2001 (promoted from Associate Professor). He conducts research in numerical modeling of incompressible fluid flows with applications across civil, environmental, and industrial engineering domains, particularly focusing on turbulence analysis. He developed the PANORMUS open-source software (with finite-volume and SPH modules) for 3D hydrodynamic simulations, fully parallelized via MPI libraries and distributed as free software. As a delegate for the Rector's Program and Strategic Plan implementation, he also serves on the University's Academic Senate since 2009. Graduated Magna Cum Laude in Civil Hydraulic Engineering (1993) at University of Palermo His research covers: (1) 3D hydrodynamic modeling using finite-volume and SPH methods for free-surface and confined flows; (2) Development of PANORMUS open-source software (including hybrid FVM-SPH capabilities); (3) Water distribution network modeling with characteristic method applications; (4) Turbulence analysis in environmental and engineering contexts; (5) Biomedical fluid dynamics applications including cardiovascular FSI and thrombus formation. His computational work addresses both fundamental fluid mechanics and applied problems like desalination technologies , water quality management , and pollutant dispersion . Scientific activities include: Computational Advancements : Developed PANORMUS software with multi-domain parallelization and deformable wall capabilities Environmental Applications : Studied Augusta Harbour hydrodynamics, Stagnone Lagoon circulation, and urban stormwater pollution Biomedical Research : Modeled thrombus formation in cardiovascular systems using SPH Engineering Solutions : Analyzed energy recovery systems with PAT technology and flow regulation via PRVs

Sandro Luigi Fioreمشاهده پروفایل

دانشیار

• Data Science
• Big Data
• Scientific Data Management
• +۱۳ مورد دیگر

Sandro Luigi Fiore is an Associate Professor in the Department of Information Engineering and Computer Science at the University of Trento, Italy. He has held academic positions at the University of Salento and visiting scientist roles at the University of Chicago and Lawrence Livermore National Laboratory. His research integrates data science, big data, and high-performance computing with climate informatics and open science. Education: Ph.D. in Innovative Materials and Technologies, University of Lecce, 2004 Master of Science in Computer Engineering (with honors), University of Lecce, 2001 His research interests span Data Science, Big Data, Scientific Data Management, Artificial Intelligence, and Distributed/Cloud/Parallel Computing , with a strong application focus on Climate Change and Open Science . He develops FAIR-enabled data analytics solutions and contributes to large-scale data infrastructures such as ESGF, EOSC-hub, and INDIGO-DataCloud. His work emphasizes provenance, reproducibility, and interoperability in scientific computing. The articles reflect a consistent trajectory in large-scale scientific data systems , evolving from Grid-DBMS and parallel computing to modern applications in climate informatics, AI, and FAIR data. Key themes include distributed data management, middleware, exascale software, and reproducible workflows in HPC environments. Scientific Awards: Earth System Grid Federation Team Award (2017) UNIDATA Community Equipment Award (2011) Best Student Paper Award, ITCC2003 Fiore has advised on and led multiple national and European projects including EOSC-hub, IS-ENES, and BARRACUDA (RDA-Europe3). He actively supports the adoption of FAIR data principles in scientific repositories, advising on data policies, architecture, provenance, and interoperability. He is a member of the FAIR Champions group and serves on the Advisory Board of FAIRsFAIR. He is involved in key research teams and projects such as the Earth System Grid Federation (ESGF) , Globus Lab (University of Chicago) , and PCMDI/LLNL . His work contributes to climate model intercomparison (CMIP5/6) and the development of next-generation data infrastructure for open science.

Stefano Caselliمشاهده پروفایل

استاد

• Autonomous Robotics
• Real-Time Systems
• Parallel and Distributed Computing
• +۴ مورد دیگر

Stefano Caselli is a Full Professor of Computer Engineering at the School of Engineering , University of Parma , Italy. He teaches courses in operating systems, real-time systems, digital design, and robotics. His academic journey includes a Laurea in Electronic Engineering (1982) and a Ph.D. in Computer and Electronic Engineering (1987) from the University of Bologna, followed by a visiting scholar position at the University of Florida's Machine Intelligence Laboratory (1989-1990). Current Role: Full Professor, Department of Information Engineering Leadership: Former Chairman of Electronic, Computer, and Telecommunications Engineering degree programs (2000-2006), currently Vice-Chairman of the Ph.D. school in Information Technology and director of a French-Italian double-degree exchange program. Research Focus : His work spans autonomous robotic systems , real-time architectures , human-robot interaction , and edge-to-cloud computing . He has led EU-funded projects like VAALID (2015-2020) and regional initiatives such as AERTECH (2015-2020), emphasizing robotics in industrial automation and rehabilitation. Publications & Collaborations : With over 100 papers in top journals and conferences (e.g., IEEE ICRA, IROS), he explores robotics, precision agriculture, and sensor integration. His Robotics Laboratory (co-founded in 1992) collaborates with local companies on industrial automation solutions. Teaching & Administration : He has served on scientific committees for IEEE ICRA and IROS conferences and is a member of IEEE and ACM . Office hours are conducted via Teams during the pandemic, with physical meetings resuming in Building 1, University of Parma.

Luca Spalazziمشاهده پروفایل

دانشیار

• Computer Science
• Cybersecurity
• Blockchain Technology
• +۵ مورد دیگر

Luca Spalazzi is an Associate Professor at the Department of Information Engineering , Università Politecnica delle Marche , Italy. His research spans multiple domains including cybersecurity , blockchain technology , machine learning , and telerehabilitation systems for Parkinson's disease. He applies formal methods to software verification and security analysis, with a focus on real-time systems and distributed architectures . Key research areas: Cybersecurity, Blockchain, Machine Learning, IoT, Formal Verification Recent work: Blockchain-based sustainable supply chains, Zero-Knowledge Proofs, Smartphone health monitoring His publications (2013-2025) demonstrate expertise in malware detection , smart contract verification , and AI-driven health solutions . Articles include BRAIN 2024 workshop organization and RAPIDO system for Parkinson's telerehabilitation.

Loris Belcastroمشاهده پروفایل

پژوهشگر

• cloud computing
• edge computing
• big data
• +۴ مورد دیگر

Loris Belcastro, PhD, is a researcher in computer engineering at the University of Calabria, Italy, affiliated with the Department of Electronics, Computer Science and System Sciences (DIMES). He earned his PhD in Information and Communication Engineering from the same institution and serves on editorial boards for journals like the Journal of Supercomputing and SN Computer Science. In 2024, he obtained the Italian National Academic Qualification as Associate Professor in Computer Engineering. His research focuses on cloud and edge computing big data analytics machine learning social media analysis high performance computing parallel/distributed data analysis His recent publications highlight trends in edge-cloud continuum integration, distributed machine learning, and scalable big data analysis. He has contributed to frameworks for urban mobility prediction, industrial IoT applications, and HPC optimization through libraries like ParSoDA-Py. He has served as guest editor for journals such as Future Generation Computer Systems and Sensors, reflecting his expertise in distributed systems and data analysis.