جست‌وجوی استاد و پژوهشگر

• Big data
• Data science
• Data analytics
• +۱۲ مورد دیگر

Paolo Garza is an Associate Professor in the Department of Control and Computer Science (DAUIN) at the Polytechnic University of Turin, where he also serves as Coordinator of the College of Computer, Film and Mechatronics Engineering. He is a member of the DBDM research group and the SmartData@PoliTO laboratory, and actively contributes to academic governance through roles in teaching coordination and PhD program committees. Education: Bachelor’s in Computer Engineering, Polytechnic University of Turin (2001) PhD in Computer and Systems Engineering, Polytechnic University of Turin (2005) His research centers on data science, big data analytics, data mining, and machine learning , with applications in emergency management, real-time communications, Earth observation, and cybersecurity. He has led and participated in numerous national and commercial research projects, including AI4CTI and NODES (PNRR), and has collaborated with industry partners like Cisco Systems. His work bridges theoretical algorithm development and practical deployment in critical systems. The recent publications reflect a strong trend toward multimodal AI, crisis informatics, and intelligent networking . Articles span computer vision for environmental monitoring (e.g., burned area detection, canopy estimation), ML for real-time communication quality, multimodal document understanding, and crisis response systems. His team leverages deep learning, transformers, and vision-language models across diverse domains. Scientific Service: Associate Editor, Knowledge and Information Systems (2024–) Associate Editor, Expert Systems with Applications (2022–) General Co-Chair, IEEE AICT Conferences (2022, 2023) He mentors several PhD students and leads funded research initiatives focused on AI for sustainable industry and cyber threat intelligence. His teaching includes graduate courses on big data processing, distributed architectures, and data science lab methods. He has also directed commercial training programs and research contracts in machine learning and cybersecurity. Research Labs & Teams: DBDM - Database and Data Mining Group (DAUIN) SmartData@PoliTO - Big Data and Data Science Laboratory LAB 5 - Research Laboratory (DAUIN)

Alfredo Bensoمشاهده پروفایل

استاد

• Bioinformatics
• Systems Biology
• Artificial Intelligence
• +۱۶ مورد دیگر

Alfredo Benso is a Full Professor in the Department of Control and Computer Science (DAUIN) at the Polytechnic University of Turin, where he is also a member of the Interdepartmental Center PolitoBIOMed Lab - Biomedical Engineering Lab. He has been continuously involved in the Doctoral College for Computer and Systems Engineering since 2008, guiding PhD education across numerous cycles. His academic roles span teaching and research leadership in bioinformatics, systems biology, and computer engineering. Research interests: Bioinformatics and computational biology Systems biology and gene regulatory networks Artificial intelligence and machine learning in biomedicine Molecular modeling and multiscale simulation Biological database systems and data integration Health informatics and public health modeling His recent publications reflect a strong trend in applying AI and machine learning to biological and medical challenges, including protein function prediction, Alzheimer’s and Multiple Sclerosis modeling, food fraud detection, and viral genome analysis. These works span journals and conferences in bioinformatics, computational biology, and biomedical engineering, demonstrating interdisciplinary innovation. Scientific Awards: BIOINFORMATICS 2014 BEST PAPER AWARD (INSTICC, United Kingdom) Advising and Grants: He supervises PhD students, including Sofia Ostellino, and leads major research initiatives such as the BIGMECH (2023–2025) and FISHUB (2016–2018) projects. He has served as Scientific Director for collaborative agreements with public administrations and as Principal Investigator on EU, national (PRIN), and regional research grants focused on bioinformatics, space systems, and reliable digital technologies. Labs and Teams: He is a key member of the SBG - System Biology Group (DAUIN) and contributes to PolitoBIOMed Lab, fostering collaborative research in biomedical engineering and computational biology.

Massimo Mecellaمشاهده پروفایل

استاد

• Service-Oriented Computing
• Business Process Management
• Process Mining
• +۱۲ مورد دیگر

Massimo Mecella serves as Full Professor at Sapienza University of Rome's Faculty of Information Engineering, Computer Science and Statistics, where he leads the Processes, Services and Software Management research group and participates in the CINI National Cyber Security Lab. His academic foundation stems from a PhD in Computer Engineering earned at Sapienza in 2002. His research expertise spans service-oriented computing, business process management, and cyber-physical systems with emphasis on service composition, process mining, and adaptive distributed architectures. Key technical domains include IoT integration, digital twin development, and security frameworks for complex software ecosystems. Recent publications (2024-2025) demonstrate a pronounced shift toward Large Language Model (LLM) integration in business processes and smart manufacturing. Dominant themes include LLM-driven process modeling, multimodal quality control systems, and digital twin implementations for energy management and production optimization. Methodological innovations focus on retrieval-augmented generation (RAG) for service discovery and fuzzy cognitive maturity assessments. His distinguished recognition includes: ICSOC 2013 Most Influential Paper Award (2003-2012 decade) 2017 Best Paper Award As research group leader, Mecella directs projects in smart manufacturing, process mining, and cyber-physical security, with funding typically sourced from EU initiatives and industry partnerships in aerospace, healthcare, and energy sectors. His team maintains active collaborations with aerospace manufacturers through the MICS SPOKE8 project and develops frameworks like SAMBA for human-in-the-loop manufacturing systems. The Processes, Services and Software Management group operates within Sapienza's engineering faculty infrastructure, utilizing specialized labs for CPS/IoT testing and digital twin simulation, with strong ties to the CINI Cyber Security Lab for security validation.

Antonio Pietrabissaمشاهده پروفایل

دانشیار

• Networked Systems
• Time-delay Systems
• Non-cooperative Control
• +۴ مورد دیگر

Antonio Pietrabissa is an Associate Professor at the Department of Computer, Control, and Management Engineering “Antonio Ruberti” (DIAG) of the University of Rome Sapienza, where he earned his degree in Electronics Engineering (2000) and PhD in Systems Engineering (2004). He has been teaching Automatic Control and Process Automation since 2010 and holds the National Scientific Qualification as Full Professor in Systems and Control Engineering (09/G1). Research interests include networked systems, robust control, Markov decision processes, and deep reinforcement learning. His work spans telecommunications, biomedical applications, and space systems, with a focus on federated learning and decentralized control. He has authored ~70 journal papers (Scopus h-index 22) and co-invented a patent for model predictive control in motor disability assistance. Awards include the 2021 Cybersecurity Award and ETRI Journal Best Paper. Current projects are NANCY (6G networks) and CADUCEO (AI-driven medical diagnostics). He is also CEO of Sapienza startup Automation Intelligence and Control (AICO), commercializing AI solutions for space, telecom, and biomedical sectors.

• Machine Learning
• Computer Vision
• Federated Learning
• +۳ مورد دیگر

Riccardo Zaccone is a Ph.D. candidate in Computer and Systems Engineering at Politecnico di Torino’s Department of Control and Computer Science (DAUIN), specializing in machine learning and computer vision. He also serves as an external lecturer and teaching assistant, contributing to courses in Machine Learning, Deep Learning, and Algorithms and Data Structures for Computer Science Engineering. Education : Ph.D. in Computer and Systems Engineering (2022–2025), Politecnico di Torino. His research focuses on Federated Learning and Visual Place Recognition, addressing challenges in communication efficiency, distributed training, and cross-domain adaptation. Recent work includes Communication-efficient Federated Learning with Heavy-Ball Momentum (2025) MeshVPR for 3D-based Urban Navigation (2025) Distributed CosPlace Training for Large-Scale Localization (2024) He collaborates with the VANDAL laboratory on multimodal learning applications and has co-authored publications in top-tier venues like ECCV, Frontiers in Robotics and AI, and ICPR.

• Applied artificial intelligence
• Artificial intelligence
• Deep learning
• +۶ مورد دیگر

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.

• Software Engineering
• Formal Methods
• Software Architectures
• +۷ مورد دیگر

Patrizia Scandurra is an Associate Professor at the Department of Management, Information and Production Engineering, University of Bergamo, Italy. Her academic appointment in Computer Science (01/B1) spans from 2022 to 2033. She previously held roles as a researcher at the University of Bergamo (2009-2017) and postdoctoral fellow at the University of Milan (2006-2008). She earned her PhD in Computer Science (2006) and Bachelor's degree (2002) from the University of Catania. Research Focus : Software architectures and formal methods for modeling, validation, and verification of software-intensive systems. Specializations : Runtime analysis of self-adaptive, autonomous, and uncertain systems including IoT-Edge-Cloud applications, embedded systems, and system-on-chip. Collaborations : STMicroelectronics, Atego, Bialetti, and ENEA. Conference Involvement : Program/organizing committees for ICSE, ASE, ISSRE, ICSA, ECSA, SEAMS@ICSE, ABZ, SA-TTA@SAC, FAACS@ECSA. Research Projects : Model-driven development for robotics, adaptive architectures for pervasive systems, big data in smart cities, and digital twins for medical systems. Notable Contributions : Development of the ASMETA formal method community tools and frameworks for rigorous system design. She has published over 100 peer-reviewed works in international journals and conferences.

Francesco Ragusaمشاهده پروفایل

پژوهشگر ارشد

• Computer Vision
• Pattern Recognition
• Machine Learning
• +۵ مورد دیگر

Francesco Ragusa is a Research Fellow at the University of Catania, Italy, holding an Industrial Doctorate in Computer Science (2021). He spent part of his PhD at the University of Hertfordshire, UK. His work focuses on First Person (Egocentric) Vision, including Human-Object Interaction, Industrial Applications, and Augmented Reality. He co-founded NEXT VISION s.r.l., an academic spin-off from the University of Catania since 2021. Key projects include the MECCANO dataset for industrial human-object interactions and the EGO-EXO4D initiative analyzing skilled human activity from multi-perspective views. Research interests span Computer Vision, Pattern Recognition, and Machine Learning. He contributed to seminal datasets like MECCANO and ENIGMA-51, advancing understanding of human behavior in industrial settings. His work emphasizes practical applications, such as wearable assistive systems and visual navigation solutions. Ragusa has delivered tutorials at major conferences (e.g., ICIAP, VISIGRAPP) on First Person Vision’s history, challenges, and trends. He actively promotes industrial collaborations and has secured grants including PNRR MUR (Code E63C22001940006) and EU funding under Next Generation EU. His teaching and professional activities include organizing workshops on egocentric vision for AI-driven assistants and industrial safety systems. Current research directions involve multimodal synthetic data utilization, gaze-based interaction analysis, and cross-modal fusion for human-robot collaboration.

Debora Nozzaمشاهده پروفایل

استادیار

• Natural Language Processing
• Hate Speech Detection
• Algorithmic Bias
• +۶ مورد دیگر

Debora Nozza is an Assistant Professor in Computing Sciences at Bocconi University, where she leads research at the intersection of Natural Language Processing, ethics, and social impact. Her work focuses on detecting and countering hate speech, understanding algorithmic bias, and examining how people use large language models in everyday contexts. Education: PhD in Computer Science, 2018, University of Milano Bicocca Dr. Nozza's research centers on ethical challenges in Natural Language Processing, with particular emphasis on hate speech detection across multilingual contexts and bias mitigation in language technologies. Her work bridges technical NLP methods with social science perspectives, examining how language models interact with societal structures and cultural contexts. She has made significant contributions to understanding gender bias in machine translation and developing methods for more equitable language technologies. Her recent publications reveal a strong focus on practical applications of NLP for social good, with an increasing emphasis on evaluating and mitigating bias in multimodal systems and large language models. Her research spans technical methodology development, dataset creation for under-resourced languages, and critical analysis of evaluation metrics in bias research. Scientific Awards: €1.5 million ERC Starting Grant (2023) for research on personalized and subjective approaches to Natural Language Processing €120,000 grant from Fondazione Cariplo for the MONICA project on monitoring Italian measures in response to COVID-19 Dr. Nozza actively contributes to the NLP community through her leadership in the MilaNLP group. She has secured significant research funding that supports multiple researchers working on NLP for social impact. Her work has practical implications for social media platforms, policymakers, and organizations developing language technologies. She co-leads the MilaNLP research group at Bocconi University, which focuses on Natural Language Processing with social impact. The group has been active in major NLP conferences, organizing workshops on online abuse and gender bias, and contributing to shared tasks that advance the field's understanding of hate speech and bias in multilingual contexts.

• Computational Logic
• Answer Set Programming
• Bioinformatics
• +۶ مورد دیگر

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

Manfredo Atzoriمشاهده پروفایل

دانشیار

• Machine Learning
• Biomedical Data Analysis
• Computer Vision
• +۴ مورد دیگر

Manfredo Atzori serves as Associate Professor at the Department of Neuroscience, University of Padova, and has been a research scientist at the Institute of Information Systems of the University of Applied Sciences Western Switzerland (HES-SO Valais) since 2011. Education M.Sc. in Physics, University of Padova, 2006 Ph.D. in Bioengineering, University of Padova, 2009 Research Focus Dr. Atzori pioneers machine learning applications for biomedical multimodal data analysis. His work spans convolutional neural networks for surface electromyography (a field he helped establish globally in 2015), computer-aided cancer diagnosis in biopsies, and 3D-printed robotic prosthetic hands controlled via machine learning. He leads the Horizon 2020 ExaMode project for weakly-supervised knowledge discovery in digital pathology, integrating text and image analysis for medical diagnostics. Research Leadership As Scientific Coordinator of the Horizon 2020 ExaMode project (2019-present), he manages a seven-partner consortium advancing multimodal medical data analysis. He previously coordinated the Hasler Foundation's ProHand project for 3D-printed prosthetics and led the MeganePro Project (2016-2019), which investigated eye-hand coordination in robotic prostheses and neurocognitive effects of amputations using multimodal datasets. Since 2011, he has curated the Ninapro database—a globally utilized resource with thousands of users for robotic hand prosthesis research. Professional Recognition With over 80 peer-reviewed publications exceeding 2,000 citations, Dr. Atzori frequently presents as an invited speaker at international conferences. He serves on the editorial board of Scientific Data (Nature Publishing Group), reflecting his standing in computational biomedical research.

• Remote Sensing
• Machine Learning
• Image Processing
• +۴ مورد دیگر

Martina Pastorino is a Researcher in the Department of Naval, Electrical, Electronic, and Telecommunications Engineering (DITEN) at the University of Genoa. Her work focuses on integrating machine learning with probabilistic graphical models for advanced remote sensing image analysis , particularly in multiresolution classification using satellite and UAV data. She teaches courses on Machine Learning for Pattern Recognition and Remote Sensing in master’s programs related to Internet and Multimedia Engineering and Energy Engineering . Research Interests : Remote Sensing, Machine Learning, Image Segmentation, Data Fusion, Hyperspectral Imaging, UAV Applications. Key Techniques : CNN-MRF Hybrids, CRFNet, Probabilistic Graphical Modeling, Multiresolution Analysis. Her recent publications explore applications in wildfire mapping , urban land-use analysis , and hyperspectral-panchromatic fusion , with a focus on improving semantic segmentation accuracy through hybrid deep learning frameworks. She is available for office hours on request via email at martina.pastorino@unige.it .

Giovanni Maria Farinellaمشاهده پروفایل

استاد

• First Person (Egocentric) Vision
• Computer Vision
• Pattern Recognition
• +۱ مورد دیگر

Giovanni Maria Farinella is a Full Professor at the Department of Mathematics and Computer Science, University of Catania, Italy. He is the Founder Member of the IPLAB Research Group at University of Catania since 2005, an Associate Member of the Computer Vision and Robotics Research Group at University of Cambridge since 2006, and an Associate Member of the Italian National Research Council since 2018. He serves as Scientific Advisor of the NVIDIA AI Technology Centre and board member of the CINI Laboratory of Artificial Intelligence and Intelligent Systems. Dr. Farinella obtained his degree in Computer Science (summa cum laude) from the University of Catania in 2004 and was awarded a Doctor of Philosophy (Computer Vision) from the same institution in 2008. He has obtained the National Scientific Qualification to Associate Professor in 2013-2014 and to Full Professor in 2018. His primary research interests focus on First Person (Egocentric) Vision, Computer Vision, Pattern Recognition, and Machine Learning. Dr. Farinella has pioneered research in egocentric video analysis, object interaction detection, activity recognition, and scene understanding from a first-person perspective. His work bridges theoretical computer vision with practical applications in industrial settings, healthcare, and cultural heritage sites. His recent publications demonstrate a clear trajectory toward more sophisticated, real-time egocentric vision systems capable of understanding complex human activities, anticipating actions, and detecting procedural mistakes through integration of visual analysis, gaze tracking, and large language models. Dr. Farinella has published extensively in top-tier computer vision venues, with his most recent work focusing on egocentric action anticipation, mistake detection in procedural tasks, and the integration of multimodal large language models with visual understanding. His research shows strong emphasis on practical industrial applications while advancing fundamental computer vision techniques. PAMI Mark Everingham Prize 2017 Intel's 2022 Outstanding Researcher Award Dr. Farinella has served as Associate Editor for IEEE Transactions on Pattern Analysis and Machine Intelligence, Pattern Recognition - Elsevier, and International Journal of Computer Vision. He has held leadership roles as Area Chair for CVPR 2020/21/22/23, ICCV 2017/19/21/23, ECCV 2020, and as Program Chair of ECCV 2022. He founded and directs the International Computer Vision Summer School (since 2006) and the Medical Imaging Summer School (since 2014). As PI of the EGO4D project, he helped create one of the largest egocentric video datasets with over 3,670 hours of footage from 923 participants across 74 locations worldwide. His IPLAB research group leads multiple significant projects including VALUE, ENIGMA, and FIPEVIS, with strong industry collaborations.

• Computational Fluid Dynamics
• Chemical Engineering
• Porous Media
• +۷ مورد دیگر

Gianluca Boccardo is an Associate Professor at the Department of Applied Science and Technology (DISAT) at Polytechnic University of Turin, where he conducts research at the intersection of computational fluid dynamics, deep learning, and porous media applications. His work bridges theoretical chemical process development with practical industrial applications in energy systems and sustainable engineering. His research interests span multiple domains of engineering and computational science: Computational Fluid Dynamics for complex engineering systems Deep learning applications in chemical process modeling Multiscale modeling of transport phenomena in porous media Energy processes engineering and sustainable technologies Fluid mechanics applications in industrial contexts Analysis of his recent publications reveals a strong trend toward integrating machine learning techniques with traditional computational methods to solve challenging problems in chemical engineering. His work particularly focuses on applying these hybrid approaches to porous media systems, pharmaceutical processes, and energy storage technologies, demonstrating a commitment to both theoretical advancement and practical industrial application. Professor Boccardo actively supervises numerous PhD students working on cutting-edge research topics and leads significant research initiatives including the MULTIPHASE Erasmus Mundus Joint Master program and the BATCAT Battery Cell Assembly Twin project. His research group receives funding from both competitive EU grants and commercial contracts with industry partners. He is an active member of the Molecular Engineering Lab (MolE) and the Multiscale Modeling research group at DISAT, where his team develops innovative approaches to modeling complex chemical processes and developing sustainable engineering solutions.

• Biometric Recognition
• Presentation Attack Detection
• Deepfake Forensics
• +۵ مورد دیگر

Giulia Orrù is an Assistant Professor of Computer Engineering at the University of Cagliari, Italy, affiliated with the Department of Electrical and Electronic Engineering. She holds an M.S. and Ph.D. in Electronic Engineering and Computer Science from the same institution. Her research focuses on biometric recognition, presentation attack detection, deepfake forensics, and cybersecurity. She is a core member of the Pattern Recognition and Applications Laboratory (PRA lab), contributing to projects like BullyBuster (anti-bullying detection systems) and LivDet competitions (fingerprint liveness detection). Dr. Orrù has authored numerous publications in top-tier conferences and journals, with a strong emphasis on advancing secure authentication systems and combating adversarial attacks in biometrics. She actively serves as a referee for pattern recognition and cybersecurity venues. Teaching activities include courses such as Technologies for Information Security and Artificial Intelligence and Security . Research interests span multimodal biometrics, 3D face reconstruction for surveillance, AI-driven anti-bullying systems, and deepfake detection algorithms. Her work bridges theoretical advancements (e.g., diffusion models for anomaly detection) with real-world applications like forensic recognition and crowd analysis. Notable projects include the Synthetic Data for Face Recognition (SdFR) initiative and contributions to the Face Deepfake Detection Challenge. Dr. Orrù's lab explores cutting-edge techniques in EEG-based personal recognition and vulnerability analysis of medical AI systems. She maintains active participation in international research networks and has developed open-source tools for evaluating biometric system resilience against spoofing attacks.