جست‌وجوی استاد و پژوهشگر

Francesco Liberatiمشاهده پروفایل

دانشیار

• Control theory
• Model predictive control
• Cyber-physical systems
• +۱ مورد دیگر

Francesco Liberati is an Associate Professor in Automatic Control at Sapienza University of Rome, Department of Computer, Control and Management Engineering (DIAG). His research focuses on cyber-physical systems, model predictive control (MPC), and hybrid MPC-deep learning algorithms with applications to power systems, traffic control, and task scheduling. PhD in Systems Engineering from Sapienza University (2015) Assistant Professor (RTD-B) at Sapienza University (2021-2024) Assistant Professor (RTD-A) at eCampus University (2015-2017) Liberati’s work combines theoretical advancements in control theory with real-world implementations in smart grids and transportation systems. He has pioneered approaches integrating MPC with reinforcement learning for large-scale optimization problems, particularly in electric vehicle (EV) charging and grid reconfiguration. His recent publications emphasize: Stochastic and economic MPC for renewable energy storage Decentralized control algorithms for EV charging Cyber-physical security in microgrids and smart infrastructure Hybrid AI-control solutions for traffic and industrial systems Scientific recognition includes: 2021 Best Paper Award, IEEE World AI IoT Congress (AIIoT) 2021 Networked Systems Best Paper Award He serves as Associate Editor for Advanced Control for Applications (Wiley) and on the Editorial Board of Smart Cities (MDPI). His applied research spans European Commission H2020 projects and collaborations with industry partners in energy and transportation sectors.

Andrea Vitalettiمشاهده پروفایل

دانشیار

• Blockchain Technologies
• Internet of Things (IoT)
• Smart Environments
• +۷ مورد دیگر

Andrea Vitaletti is an Associate Professor at Sapienza University of Rome , affiliated with the Department of Computer Engineering, Automatics and Management Antonio Ruberti (DIAG) in the College of Engineering. His academic career spans over two decades of research in networking and algorithmic topics. PhD in Computer Science, Sapienza University of Rome (1998–2002) Assistant Professor (Ricercatore) at Sapienza (2007–2019) Co-founder of spin-offs WSENSE (2012–2019) and WLAB (2002–2016) Research Interests focus on decentralized systems , particularly blockchain technologies , Internet of Things (IoT) , federated machine learning , and data privacy . His work bridges theoretical algorithmic research with practical implementations in wireless sensor networks and distributed ledger systems. Scientific Contributions include over 90 publications, 2 patents, and leadership in the EU FET OPEN project PLEASED. His applied research has been recognized with multiple awards: 2000: Wonderland Contest - Media and Communication 2002: Simagine Innovation Prize 2004: Simagine Bronze Award 2007: Premio Perotto Top Prize 2012: Italiacamp Winner He leads the Wireless Sensor Networks lab at DIAG, supervising 2 PhD students, 1 post-doc, and 5 master students. His teaching portfolio includes courses on IoT, blockchain, cybersecurity, and digital entrepreneurship since 2000.

• Sensor network data analysis
• Crowdsourced data analysis from citizen science initiatives
• Statistical modeling and analysis of spatio-temporal data
• +۳ مورد دیگر

Francesco Finazzi is a full professor of statistics (SECS-S/02) at the Department of Economics of the University of Bergamo and maintains a research affiliation with the School of Mathematics and Statistics at the University of Glasgow. He is internationally recognized as the founder of the Earthquake Network citizen science initiative (www.sismo.app), which pioneered the first globally implemented smartphone-based seismic early warning system. His research expertise spans sensor network data analysis, crowdsourced data from citizen science initiatives, statistical modeling of spatio-temporal data, and parallel scientific software development. He has made significant contributions to developing statistical methodologies for earthquake parameter estimation using smartphone sensor networks and has advanced techniques for analyzing environmental time series data. His recent publications reveal a strong research trajectory focused on earthquake early warning systems, spatio-temporal environmental modeling, and statistical approaches to crowdsourced seismic data. His work uniquely bridges statistics, seismology, and computer science to develop practical, real-world early warning solutions that leverage mobile technology and citizen participation. Finazzi has secured substantial research funding as Principal Investigator for the University of Bergamo in major Horizon 2020 projects, including RISE (Real-time earthquake risk reduction for a ReSilient Europe, 2019-2023, €8,000,000) and TURNkey (Towards more Earthquake-resilient Urban Societies through a Multi-sensor-based Information System, 2019-2022, €7,999,948). He leads the Earthquake Network initiative, a groundbreaking citizen science project that has created the first operational smartphone-based seismic early warning system worldwide. This platform not only provides early warnings but also facilitates rapid impact assessment and supports search and rescue operations following seismic events.

Debora Nozzaمشاهده پروفایل

استادیار

• Natural Language Processing
• Hate Speech Detection
• Ethics in NLP
• +۴ مورد دیگر

Debora Nozza is an Assistant Professor in Computing Sciences at Bocconi University , where she leads research on ethics in Natural Language Processing with a focus on hate speech detection and algorithmic bias in multilingual contexts. She was awarded a €1.5 million ERC Starting Grant (2023) for her project PERSONAE , exploring personalized and subjective approaches to NLP. Previously, she secured a €120,000 Fondazione Cariplo Grant (2019) for the MONICA project analyzing Italian responses to the pandemic. Education: PhD in Computer Science (2018), University of Milano Bicocca Her research spans hate speech detection , gender bias in language models , and computational social science . She organizes key workshops like the Workshop on Online Abuse and Harms (WOAH) and Gender Bias in NLP (GeBNLP) at ACL conferences, and co-led shared tasks including HODI (Homotransphobia Detection in Italian) and HatEval (hate speech against immigrants). Recent publications address actionable bias metrics , gender pronoun handling in translation , and large-scale stereotype amplification via text-to-image generation . Her work combines model interpretability , cross-lingual frameworks , and social impact analysis to tackle systemic biases. Scientific Awards: ERC Starting Grant (2023) Fondazione Cariplo Grant (2019) She actively participates in international conferences, including keynotes at ECCV 2024 and WASSA 2024 , and collaborates with groups like MilaNLP and ACL workshops .

• Chemical Sensors
• Measurement Systems
• Circuits and Systems Design
• +۴ مورد دیگر

Valerio Vignoli is an Associate Professor of Electronics at the University of Siena's Department of Information Engineering and Mathematics since 2005. He holds a Laurea in Electronic Engineering (1989) and a Ph.D. in Nondestructive Testing (1994) from the University of Florence. His research focuses on chemical sensors, measurement systems, and circuits for ICT applications. He has pioneered low-cost IoT sensor solutions for environmental monitoring, healthcare, and industrial safety. Notable projects include magnetic contaminant detection systems, wearable health monitors for hazardous environments, and QCM-based biosensors for on-site diagnostics. His work integrates interdisciplinary approaches, such as applying machine learning to sensor signal processing and developing energy-efficient self-powered sensor nodes. He has contributed to advancing photoacoustic gas sensing, entropy estimation for secure random number generation, and wearables for occupational safety. His research emphasizes practical applications, including smart agriculture CO₂ monitoring and real-time worker health tracking. Dr. Vignoli has designed innovative systems like the remotely controlled test bench for ultrasonic anemometers and self-tunable chaotic TRNGs. His publications span sensor design, environmental technology, and hardware security, reflecting a commitment to bridging theoretical advancements with real-world implementation challenges.

• Sensor Technology
• Environmental Monitoring
• IoT Systems
• +۳ مورد دیگر

Ada Fort is an Associate Professor in the Department of Information Engineering and Mathematics at the University of Siena, Italy. Her research focuses on advanced sensor systems, including environmental monitoring, biomedical instrumentation, and IoT applications. She holds a Laurea in Electronic Engineering (1989) and a Ph.D. in Nondestructive Testing (1992) from the University of Florence. Key research areas include wearable sensors for air quality monitoring, magnetic detection of contaminants, and QCM-based biosensors. Her work integrates machine learning for signal processing and fault detection in industrial and environmental systems. Notable projects involve self-sufficient IoT nodes powered by solar energy and low-cost sensor networks for agriculture and healthcare. Publications highlight innovations in sensor design, data imputation for environmental monitoring, and entropy-based security systems. Her contributions span interdisciplinary fields, linking engineering principles with applications in healthcare, agriculture, and climate science.

Marcello Pelilloمشاهده پروفایل

استاد

• Computer Science
• Machine Learning
• Pattern Recognition
• +۷ مورد دیگر

Marcello Pelillo is a **Full Professor** at the Department of Environmental Sciences, Computer Science and Statistics at Ca' Foscari University of Venice. His research focuses on machine learning, pattern recognition, computer vision, and adversarial machine learning. He has contributed significantly to graph-based methods, clustering algorithms, and security in machine learning systems. Pelillo is affiliated with the European Center for Living Technology (ECLT) and the Research Institute for Complexity Communications . His work spans theoretical advancements in graph theory and practical applications in cultural heritage digitization, climate science (e.g., ice core analysis), and AI security. Recent projects include entropy-guided graph clustering, backdoor poisoning defenses, and benchmark datasets for puzzle-solving tasks. Publications emphasize interdisciplinary applications, such as AI-assisted historical document digitization and energy-latency attacks in networks. He has supervised multiple collaborative projects involving institutions like the Research Institute for Complexity and the European Interuniversity Research Center.

• Electronic Design Automation
• Energy Efficient Electronic Systems
• Low Power Design
• +۱۲ مورد دیگر

Andrea Calimera 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 SmartData@PoliTO - Big Data and Data Science Laboratory. He is actively involved in teaching and research, contributing to doctoral programs and undergraduate and graduate courses in computer engineering and data science. Full Professor (L.240), Polytechnic University of Turin Department of Control and Computer Science (DAUIN) Member, SmartData@PoliTO - Big Data and Data Science Laboratory Member, College of Computer, Film and Mechatronics Engineering His research interests center on electronic design automation, energy-efficient electronic systems, and low-power design, with strong connections to artificial intelligence, embedded systems, and IoT. His work bridges hardware and software optimization for intelligent edge devices. The recent publications (2023–2025) reflect a focused trend on federated learning, secure and efficient AI deployment on edge devices, and low-power embedded systems. Topics include robust evaluation in federated learning, resource management under label skew, homomorphic encryption for private tensor operations, pipeline optimization for keyword spotting, and side-channel attacks via DVFS for neural network fingerprinting—highlighting expertise in both performance and security of AI systems on constrained hardware. Andrea Calimera supervises PhD and master's students and leads research projects funded by competitive and commercial grants. He has contributed to national and international patents on low-power depth estimation and single-image signal processing. Scientific Director, SENSEI Project (2017–2019): Energy-efficient machine learning on chip for IoT Scientific Director, Commercial Project (2020–2022): Design tools for AI on energy-efficient embedded mobile devices Supervision of PhD student Erich Malan (ongoing, since 2022) on distributed and federated learning over IoT networks Supervision of Bachelor's student Chen Xie (2020–2024) on synthesis of smart sensors He teaches courses such as High-Level Synthesis (PhD), Synthesis and Optimization of Digital Systems, Machine Learning for IoT, and Efficient Computing for Artificial Intelligence across Computer Engineering and Data Science programs. His research group is EDA - Electronic Design Automation (DAUIN), which focuses on hardware-software co-design for intelligent systems.

Vittorio Curriمشاهده پروفایل

استاد

• Optical Communications
• Optical Networks
• Multi-band Optical Networks
• +۱۲ مورد دیگر

Vittorio Curri is a Full Professor in Optical Communications and Networking at the Department of Electronics and Telecommunications (DET) of Politecnico di Torino , Italy. He is a founding member of the OptCom Group and PhotonLab and leads the PLANET research team. His work spans optical network modeling, AI-assisted control, open-source software (GNPy), and environmental sensing via optical fiber. He has led numerous EU and industry-funded projects and is a key figure in open optical networking. Research Interests: Multi-band optical transmission in single-mode fibers Physical layer aware networking Machine learning and AI for optical network optimization Environmental sensing using optical network telemetry Open and disaggregated optical networks Digital twin development (GNPy project) WDM and coherent transmission modeling The recent publications reflect a strong trend toward integrating AI and machine learning with digital twin technologies for real-time network control, anomaly detection, and performance optimization. There is a clear focus on wideband, multi-band, and converged metro-access networks , with modeling efforts extending to filtering effects, polarization, and nonlinear impairments. The research is highly applied, with strong industry collaboration and open-source contributions. Scientific Awards: Concorso "Galileo Feraris" (2002) JLT Best Paper Award (2014, 2015) FFABR 2017 Research Grant Advising and Grants: Prof. Curri has supervised 25 PhD students and numerous postdocs. He has served as Principal Investigator on major projects including WON (EU H2020) , ALLEGRO , NESTOR , RESTART , SENSEI , and SCIPIO . He leads the GNPy open-source project under TIP and has extensive collaborations with Synopsys, Open Fiber, INFINERA, and CESNET. His research is funded by EU programs (Horizon Europe, H2020), PNRR, and multiple industrial contracts. Labs and Teams: He leads the PLANET (Physical Layer Aware NETworking) team, a subgroup of the OptCom Group at PoliTo. The team focuses on simulation, modeling, and AI-driven control of next-generation optical networks. They collaborate closely with the LINKS Foundation and international partners including Soochow University and CESNET .

Angelo Feraudoمشاهده پروفایل

پژوهشگر ارشد

• Vehicular Networks
• Cloud Computing
• 5G Networks
• +۳ مورد دیگر

Angelo Feraudo is a Research Fellow at the Department of Computer Science and Engineering of the University of Bologna. He is currently pursuing a PhD in Computer Science, focusing on vehicular computing and service continuity in vehicular networks. His academic path includes a Master's degree in Computer Engineering (University of Bologna) and research experience at the Computer Laboratory of Cambridge University. PhD Researcher (Nov 2021 - present) Research Fellow (Apr 2021 - Oct 2021) Visitor at University of Cambridge (Sept 2020 - Jan 2021) His research intersects emerging technologies like vehicular ad hoc networks (VANETs), vehicular cloud computing, 5G/Mobile Edge Computing (MEC), O-RAN standards, and IoT security. Key projects include: Vehicular computing research (2021-present) Resilient Water Emilia-Romagna dashboard (2021-present) MUD standard extensions for IoT security (2020) Distributed federated learning at Cambridge (2019-2020) Bluetooth vulnerability analysis (2018-2019) Technical expertise spans multiple programming languages ( Java, C, Python, C++, JavaScript ) and systems engineering. Publications address critical IoT security frameworks, federated learning implementations, and device fingerprinting methodologies.

Francesca Nonisمشاهده پروفایل

استادیار

• Facial Expression Recognition
• Deep Learning
• Human-Computer Interaction
• +۶ مورد دیگر

Francesca Nonis is an Assistant Professor and Fixed-term researcher at Politecnico di Torino's Department of Management and Production Engineering (DIGEP). She is an invited member of both the College of Architecture and Design and the College of Mechanical, Aerospace, and Automotive Engineering. As part of the 3D LAB research group, she contributes to cutting-edge research in human-computer interaction applications and 3D data visualization. Dr. Nonis specializes in Facial Expression Recognition (FER) using Deep Learning techniques, with a focus on 3D data applications for human-computer interaction. Her research spans multiple domains including virtual reality, affective computing, and cultural heritage preservation. She has developed methodologies for real-time facial expression recognition and has contributed to building spontaneous 3D facial expression databases that have advanced the field of emotion recognition. Her recent publications reveal a strong trend toward interdisciplinary research that bridges computer science, psychology, and cultural applications. She has made significant contributions to metaverse platforms for cultural heritage preservation, user engagement studies using EEG in museum settings, and the development of affective virtual reality environments. Her work consistently applies advanced computer vision and deep learning techniques to solve real-world problems in human-computer interaction. Dr. Nonis has co-authored a national patent titled "Methodology for real-time facial expression recognition" with Federica Marcolin, Luca Ulrich, and Enrico Vezzetti. Her teaching portfolio includes Industrial Technical Drawing and Modeling Design courses across multiple engineering disciplines including Aerospace Engineering, Mechanical Engineering, Chemical and Food Engineering, and Design and Communication programs. As a core member of the 3D LAB research group, Dr. Nonis collaborates on projects involving facial morphology studies, innovative surgical guides, augmented reality applications, and e-learning solutions. The lab's work leverages 3D sensors, augmented and virtual reality, and machine learning techniques to develop applications for medical, security, and marketing domains.

• Computer Science
• Cybersecurity
• Network Security
• +۴ مورد دیگر

Mauro Andreolini is a University Researcher at the Department of Physical, Computer and Mathematical Sciences, University of Modena and Reggio Emilia. He teaches Operating Systems and Secure Software Development courses within the Computer Science degree program. His research focuses on Cybersecurity , Network Security , Machine Learning in Security , and Cloud Computing . His recent publications analyze Data Privacy through geohashing and clustering, Adversarial Attacks in cybersecurity, and Moving Target Defense architectures. He has also contributed to frameworks for Automated Security Assessments using deductive reasoning and Realistic Botnet Detection benchmarks. Andreolini's work addresses Graph Neural Networks in intrusion detection, n-Gram Analysis for automotive network security, and Side-Channel Vulnerabilities in USB devices. He collaborates with researchers like Artioli, Ferretti, Marchetti, and Colajanni on projects spanning Adversarial Machine Learning , Secure Software Development , and Cloud-Based Monitoring .

• Naval Engineering
• Marine Propulsion
• Hybrid Propulsion Systems
• +۶ مورد دیگر

Raphael Zaccone serves as an Associate Professor in the Department of Naval, Electrical, Electronic and Telecommunications Engineering at the University of Genoa, where he is an active member of the department board. He teaches core courses including Military Ships (NAVI MILITARI), Naval Propulsion (PROPULSIONE NAVALE), and Naval Plants (IMPIANTI NAVALI) for the Naval Engineering degree program, as well as Ship Plants and System Safety for Maritime Science and Technology students. His research centers on sustainable maritime innovation, with primary focus areas in hybrid propulsion systems, alternative fuels (particularly methanol conversions), ship safety protocols, and autonomous navigation technologies. Key specialties include energy management strategies for reducing environmental impact, structural solutions for yacht refits, and collision avoidance algorithms compliant with international maritime regulations. His work bridges theoretical modeling with practical engineering applications to address critical challenges in modern naval architecture. Recent publications (2023-2025) reveal a pronounced trend toward maritime cybersecurity and AI-driven safety systems, with significant emphasis on LiDAR-based situational awareness, battery storage optimization for naval vessels, and evaluation frameworks for alternative marine fuels. Approximately 40% of his current work addresses autonomous ship navigation challenges, while 30% focuses on decarbonization through methanol propulsion and waste heat recovery systems, demonstrating strategic alignment with global maritime sustainability initiatives.

Corrado Loglisciمشاهده پروفایل

استادیار

• Temporal Data Mining
• Temporal Learning
• Textual Data Mining
• +۱۳ مورد دیگر

Corrado Loglisci is an Assistant Professor at the Department of Computer Science, University of Bari Aldo Moro, Italy. His research focuses on Temporal Data Mining , Machine Learning , and Quantum Computing , with applications in bioinformatics, medical informatics, and cybersecurity. He earned his Ph.D. in Computer Science with a thesis on temporal projection in longitudinal data. Research Highlights : Temporal Learning, Textual Data Mining, Quantum-Classical Hybrid Systems Collaborations : IRSTEA Research Institute (France), Aristotle University of Thessaloniki (Greece) His publications address dynamic network analysis , emotion detection in social media , and quantum-enhanced classification . He contributes to program committees and journal editorial work, including a special issue on Mining Complex Patterns in the Journal of Intelligent Information Systems . Notable contributions include the jKarma framework for change detection and studies on concept drift robustness in intrusion detection systems. His work spans European/National research projects, leveraging machine learning for tasks like mobile crowd sensing trustworthiness prediction (2020) and investor behavior analysis (2023-2025).

• Internet of Things (IoT)
• Structural Health Monitoring (SHM)
• Microwave Imaging
• +۵ مورد دیگر

Igor Bisio is a Full Professor at the Department of Naval, Electrical, Electronics, and Telecommunications Engineering (DITEN) at Università di Genova. His research focuses on IoT-driven structural health monitoring, microwave imaging for biomedical applications, and wireless surveillance systems. Teaches courses on telecommunications, IoT, and machine learning Pioneers low-cost IoT solutions for SHM and post-stroke rehabilitation Develops microwave tomography techniques for pediatric stroke diagnostics Advances privacy-preserving Wi-Fi-based crowd monitoring Recent research trends include edge AI integration, compressive sensing for vibration analysis, and multi-class object tracking in aerial scenes. He also explores UAV-based monitoring systems, WiFi fingerprinting for localization, and Banach space inversion models for electromagnetic imaging. His work spans interdisciplinary domains combining electrical engineering, biomedical applications, and wireless network security.