Find Academic Supervisors

• Information Visualization
• Visual Analytics
• Human-Computer Interaction
• +8 more

Paolo Buono is Associate Professor at the Department of Computer Science, University of Bari Aldo Moro, Italy. He holds a PhD in Computer Science with specialization in Visual Data Analysis. His research focuses on Information Visualization, Visual Analytics, Human-Computer Interaction, and Mobile Applications. Co-founder and CEO of LARE (2010), a university spinoff providing real-time surgical support through audio-video telestration Member (since 2002) and computer science coordinator at METEA Research Center for environmental protection Visiting scientist at AVIZ (France), University of Maryland (USA), and Fraunhofer IPSI (Germany) His work spans multiple application domains including: Cultural Heritage through interactive exploration systems Healthcare with smart therapeutic devices Environmental Monitoring via CET system IoT-based Smart Interactive Experiences He has contributed to: Dynamic hypergraph visualization techniques End-User Development frameworks (EUDroid) Usability evaluation methodologies Mobile health applications As project leader, he has coordinated: EU-funded VisMaster Coordination Action (2008-2010) Italian Ministry-funded LOGIN project (2014-2015) Apulia Region environmental projects His professional engagements include: Co-chair roles at INTERACT, AVI, IS-EUD conferences Program committee participation in VIS series and HCI conferences Member of ACM, IEEE, and SIGCHI Italy

Luca SchenatoView profile

Professor

• Control Systems
• Distributed Optimization
• Federated Learning
• +5 more

Luca Schenato is a Full Professor in the Department of Information Engineering at the University of Padova. His research focuses on distributed control systems, federated learning, multi-agent optimization, and wireless communication protocols. He has extensive experience in developing algorithms for cyber-physical systems, with applications in robotics, smart grids, and sensor networks. Education and Appointments section lists his academic journey but lacks explicit details. He has held positions related to control systems and information engineering throughout his career. Research interests include: Design of resilient wireless control systems Federated learning architectures for edge computing Distributed optimization under communication constraints Robotics and multi-agent coordination Smart energy management systems His recent publications (2021–2025) demonstrate a strong focus on: Over-the-air federated learning innovations High-speed wireless control systems (e.g., 1 kHz Wi-Fi control) Resilient distributed optimization algorithms Human-centric building automation He has contributed to numerous projects related to networked control systems and has organized conferences like ECC13. His work emphasizes bridging theoretical control principles with practical industrial applications.

• Distributed Systems
• Computer Networks
• Middleware
• +13 more

Antonio Corradi is a Full Professor of Computer Networks and Infrastructures supporting Cloud and Big Data at the University of Bologna's School of Engineering, within the Department of Computer Science - Science and Engineering. His roles include President of the regional CLUSTER RER for service innovation, President of the Alma Mater FAM Foundation, and Director of the UNIBO High Studies Center in Buenos Aires. He previously served as Director of the DISI department (2018–2021) and International Delegate for Latin America (2014–2018). His research focuses on distributed systems, middleware for pervasive computing, cloud solutions, mobile systems, smart cities, Industry 4.0/5.0, and 5G communication standards. Education: Laurea cum laude in Electrical Engineering (University of Bologna, 1979) and a Master's in Computer Engineering from Cornell University (1981, supported by a Fulbright-Hayes grant). He joined the University of Bologna as a Researcher in 1983 and became Full Professor in 2000. Research interests span distributed/parallel systems, middleware for mobile agent systems, cloud computing, smart city monitoring, and Industry 4.0 protocols. He emphasizes QoS-aware solutions, edge computing, and IoT integration. His work includes designing frameworks for big geospatial data and novel architectures for serverless and fog computing environments. Selected scientific awards include the 1980 'Cavalieri del Lavoro' prize for his thesis. He actively contributes to institutional duties, including the CCIB (Computer Services Centre of the Engineering School) and CINI Bologna University Section (Italian Interuniversity Consortium). In advising and grants: He coordinates PhD programs and has led projects funded by MIUR, CNR, and European initiatives. Notable collaborations include industry grants with Jakala, OTConsulting, ENAV-Sicta, and the Zefiro Consortium. His projects address challenges in energy efficiency, smart manufacturing, and healthcare management during crises. Labs/Teams: Developed platforms like SOMA and REDMAN middleware. Involved in initiatives such as ParticipAct (mobile crowdsensing), COLOMBO (vehicular traffic monitoring), and the Audit4Cloud platform for cloud performance auditing.

• 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.

• Applied artificial intelligence
• Artificial intelligence
• Deep learning
• +6 more

Flavio Giobergia is a Researcher at the Department of Control and Computer Science (DAUIN) within Politecnico di Torino . His work spans applied artificial intelligence , with a focus on deep learning and machine learning applications. Research Interests : Machine learning under limited label availability, LLM-assisted code refactoring, subgroup performance analysis in ASR models, exoplanet atmospheric reconstruction, and predictive maintenance systems. Teaching : Course owner for Data Science and Machine Learning Lab and Large Language Models at Politecnico di Torino. Projects : Scientific head for the MAD – STANDARD BANKING project (2025–2026) and ImEDA (2023–2024), focusing on anomaly detection and model efficiency. Publications : 15+ recent works on topics including machine unlearning benchmarks, synthetic data for hallucination detection, and drift detection limitations, presented at top conferences like KDD, Interspeech, and IEEE AICT. Collaborations : Active in the SmartData@PoliTO center and co-author with Elena Baralis, Alkis Koudounas, and others.

Massimo Orazio SpataView profile

Research Fellow

• Deep Learning
• Biomedical Engineering
• Computer Science
• +3 more

Massimo Orazio Spata is a Research Fellow in Computer Science at the University of Catania's Department of Mathematics and Computer Sciences, specializing in deep learning applications for biomedical, audio, and biometric systems. He has held roles at STMicroelectronics since 1999, focusing on system integration, image processing, and biomedical device R&D. He teaches courses such as Mobile Programming and Computer Architecture at secondary schools and has advised numerous students on grid computing and middleware projects. Education: PhD in Computer Science (University of Catania, 2008), MSc in Computer Science (University of Catania, 2013), and a teaching certification in Computer Science (University of Catania, 1998). Research interests include deep learning algorithms, biomedical device development, grid scheduling, and cybersecurity. He has authored patents on lab-on-chip systems, bio-computer analysis, and scheduling methods, and his work has been recognized with STMicroelectronics Innovation Awards (2016–2014) and a Cisco CCNA certification. Key collaborations include projects with Google (Mediapipe Objectron for robotics), Huawei (video deblurring), and involvement in the PNRR Horizon HiCONNECTS project (2024–present). He serves on conference committees (e.g., ICAETA 2023) and has developed e-learning systems and CAD tools for STMicroelectronics.

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +9 more

Carlo Masone is a Fixed-term Researcher at the Department of Control and Computer Science (DAUIN), Politecnico di Torino, affiliated with the College of Electronic, Telecommunications, and Physics Engineering. He is also an invited member of the College of Management and Production Engineering and the College of Mathematical Engineering, reflecting his interdisciplinary contributions. His research focuses on artificial intelligence, machine learning, computer vision, and robotics, with significant work in visual place recognition, federated learning, and geospatial AI. His research interests span Artificial Intelligence , Machine Learning , Computer Vision , Robotics , Visual Place Recognition , Federated Learning , Open-Set Segmentation , and Geospatial AI . He has developed methods for uncertainty quantification in ML models for autonomous vehicles and contributed to digital heritage through the MAPP project. The recent publications highlight a strong trend in visual place recognition (e.g., EigenPlaces, MeshVPR), geolocalization of astronaut photography (Earthloc, EarthMatch), and robust segmentation (Mask2Anomaly). There is a clear emphasis on leveraging pre-trained features, federated learning for privacy-preserving recognition, and topological methods in vision. His work bridges robotics, AI, and real-world applications in autonomous systems and cultural heritage. Scientific Awards: Outstanding Reviewer at CVPR (2022, 2023, 2024) IROS JTCF Novel Technology Paper Award (2016) Best Paper Award Finalist at IEEE ICIA (2016) ELLIS Fellow (2024–) He advises PhD students in Artificial Intelligence and Computer and Systems Engineering and leads commercial research projects such as Quantifying Uncertainties in ML Models for Driver-Assisted and Autonomous Vehicles and MAPP - Phygital and Participatory Alpine Museums . He has previously collaborated with the Max Planck Institute for Biological Cybernetics (2014–2017). He teaches courses including Machine Learning for Mathematical Engineering , Robot Learning , and GeoAI , and contributes to programming and data science curricula. He is also a co-inventor on a patent for automated neural network design.

Iacopo ColonnelliView profile

Assistant Professor

• Scientific Workflow Systems
• High-Performance Computing
• Cloud Computing
• +6 more

Iacopo Colonnelli is an Assistant Professor (RTDA) at the University of Turin's Computer Science Department and a member of the Alpha Research Group (Parallel Computing) and CINI HPC Key Technologies and Tools lab. He has established himself as a leading researcher in scientific workflow systems, bridging cloud computing and high-performance computing environments. His research focuses on workflow modeling and management in heterogeneous distributed architectures, with significant contributions through open-source tools including StreamFlow (a container-native workflow management system), Jupyter Workflow, and CAPIO (middleware for I/O streaming). These tools enable hybrid workflows execution on cloud-HPC infrastructures and have gained recognition through multiple European projects and initiatives. Colonnelli's publication record shows consistent output in top venues related to parallel and distributed computing, with recent work focusing on federated learning, confidential computing, and workflow standardization. His most recent publications (2024-2026) demonstrate strong engagement with cutting-edge challenges in cross-facility federated learning, workflow representation languages, and performance evaluation of confidential computing for bioinformatics applications. Scientific Awards: ITADATA 2023 Best PhD Thesis Award for 'Workflow models for heterogeneous distributed systems' StreamFlow selected as one of the three exploitable results of the EUPEX European project (2023) StreamFlow selected as an exploring technology by the EC Innovation Radar initiative (2023) 'Distributed Workflows With Jupyter' selected as Fall 2022 Editor's Choice by Future Generation Computer Systems journal HPC-Europa3 grant recipient for Barcelona Supercomputing Center visit (2019) HiPEAC grant recipient for ACACES 2019 Summer School (2019) As an active contributor to research infrastructure, Colonnelli serves as a member of the CWL Technical Team and founder of the CWL4HPC Working Group. He has organized multiple international conferences including PDP 2025 as program chair and CWLCon 2024. His service extends to numerous program committees for major HPC conferences and journals, demonstrating his standing in the international research community. Colonnelli leads significant contributions to multiple European research projects including Space Center of Excellence, European Pilot, EUPEX, TEXTAROSSA, ACROSS, DeepHealth, and HPC4AI, focusing on advancing HPC and AI technologies for scientific applications.

• Computational Logic
• Answer Set Programming
• Bioinformatics
• +6 more

Alessandro Dal Palu' is an Associate Professor at the Department of Mathematical, Physical, and Computer Sciences at University of Parma. He holds a PhD in Computer Science from University of Udine and has been with University of Parma since 2005, transitioning from Researcher to Associate Professor in 2014. His teaching portfolio includes courses on Computer Architecture, Constraint Programming, and Algorithms & Data Structures. His research spans computational logic, bioinformatics, and GPU computing. Notable achievements include the 2007 GULP award for his Ph.D. thesis and the ICLP 2010 best paper award. He has led Italian INdAM-GNCS research projects on GPU applications (2011) and Logic Programming in cancer genomics (2016). Recent publications focus on explainable AI frameworks, bioinformatics applications, and sustainable logistics solutions. His work integrates Answer Set Programming with biomedical challenges like protein structure analysis and cancer genome evolution. He chairs the International Conference on Logic Programming (ICLP 2018) and has organized multiple international workshops on constraint programming. 2007 GULP Award ICLP 2010 Best Paper PI for INdAM-GNCS projects (2011, 2016) Program Committee member for international conferences

• Data Logistics
• Exascale Computing
• High Performance Computing
• +7 more

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.

• High Performance Computing
• Grid Computing
• Cloud Computing
• +7 more

Giovanni Aloisio is a Full Professor of Information Processing Systems at the Department of Innovation Engineering, University of Salento, Italy. He is a leading figure at the Euro-Mediterranean Center on Climate Change (CMCC), where he serves as Director of the Supercomputing Center and Director of the Scientific Computing and Operations (SCO) Division. He is also a member of CMCC’s Governance bodies, including the Strategic Council and Executive Committee. His research focuses on High Performance Computing (HPC) , grid and cloud computing , and distributed data management . He has played a pivotal role in major European and international initiatives such as the European Grid Forum (Egrid), the EU FP7 IS-ENES projects, the European Exascale Software Initiative (EESI), and the International Exascale Software Project (IESP). His work bridges advanced computing infrastructure with Earth system modeling and climate science. Recent publications highlight a strong trend toward integrating HPC simulations , big data analytics , and machine learning in climate science. His team develops tools like PyOphidia for scalable data analytics and explores AI-driven methods for weather and climate modeling, pandemic forecasting, and environmental data downscaling. The research spans interdisciplinary domains including climate modeling, epidemiology, and environmental health. He has authored over 100 peer-reviewed journal articles. His leadership in EU-funded projects and international working groups, such as the ENES HPC Task Force and the WCES Working Group, reflects his significant contributions to the scientific community. He leads the HPC laboratory at the University of Salento and oversees advanced computing operations at CMCC. His work supports large-scale scientific workflows, climate data spaces within the European Open Science Cloud, and the convergence of HPC, AI, and data analytics.

• Quantum Computing
• Machine Learning
• Parallel and Distributed Systems
• +1 more

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 QuerView profile

Associate Professor

• Computer Science
• Electrical Engineering
• Formal Methods
• +7 more

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

• Numerical Analysis
• Machine Learning
• Computational Mathematics
• +4 more

Elena Toscano is a researcher in the Department of Mathematics and Computer Science at the University of Palermo. She specializes in numerical analysis, machine learning, and computational mathematics, with a focus on mesh-free methods like Smoothed Particle Hydrodynamics (SPH) and applications to physics, engineering, and interdisciplinary fields. Teaching: Numerical Analysis (Master's in Informatics and Mathematics, 2025/2026) Research Areas: Signal/image processing, SPH consistency restoration, genetic algorithms for tomography, and mathematical-literary collaborations (e.g., Oulipo). Her publications span computational physics, machine learning, and mathematical modeling, emphasizing numerical stability and interdisciplinary innovation.

Ritamaria BucciarelliView profile

Adjunct Professor

• Natural Language Processing
• Computational Linguistics
• Digital Humanities
• +3 more

Ritamaria Bucciarelli is an Adjunct Professor at Ca' Foscari University of Venice, affiliated with the Department of Comparative Linguistic and Cultural Studies (DSLCC) and the Research Institute for Digital and Cultural Heritage. She holds a PhD in Language Sciences (2008) and multiple advanced degrees in Literature, Pedagogy, and Natural Sciences. Her research focuses on Natural Language Processing (NLP), Digital Intelligence, and computational linguistics, with projects involving quantum physics applications and digital text analysis. She has taught Italian linguistics and language courses internationally, including at the University of Pisa and LUISS Guido Carli. Her work includes developing tools like Acro Word and Type Race for automated text generation and translation. Awards include the ESB Level 3 English certification with Distinction (2019) and recognition as top-performing in an online teaching course (2002). She has led research teams in Italy and France, collaborating on projects such as sentiment analysis and digital text cloud workshops. Bucciarelli also served as a MIUR inspector for secondary schools and has extensive experience in blended learning and e-learning platform management.