جست‌وجوی استاد و پژوهشگر

Livio Pompianuمشاهده پروفایل

استادیار

• Information Security
• Cryptocurrency Frauds
• Blockchain Analytics
• +۵ مورد دیگر

Livio Pompianu is an Assistant Professor (RTDa) at the Department of Mathematics and Computer Science of the University of Cagliari . He serves as a Research Unit Coordinator and has been actively involved in projects such as Score and Intellicredit as a technical director and solution architect. Education : PhD in Computer Science from the University of Cagliari (2018), thesis on "Analysing blockchains and smart contracts: tools and techniques" Research Interests focus on Information Security with specific expertise in Blockchain Analytics , Cryptocurrency Frauds , Design Patterns for Smart Contracts , and IoT . His work spans security frameworks, biometric identification, and digital transformation. Publications Trends : 15+ recent works cover blockchain analytics, AI-driven ontologies, biometric security, and smart contract applications in safety-critical systems. Scientific Contributions : Co-author of 26+ publications with over 300 citations, including tools like Cryptoscam Classifier and BlockAPI . Research Groups : Active member of Distributed Ledger Technology , Blockchain@Unica , and Trustworthy Computational Societies .

Fausto Marcantoniمشاهده پروفایل

استادیار

• Network Security
• Cybersecurity
• Penetration Testing
• +۵ مورد دیگر

Fausto Marcantoni is an Assistant Professor at the University of Camerino , specifically within the School of Science and Technology - Computer Science Section . His academic work focuses on network security, penetration testing, and cybersecurity education. He actively supervises student theses and leads the Laboratorio di Reti di Elaboratori (Computer Networks Laboratory) at the university. Contact: fausto.marcantoni@unicam.it | Tel. +39 0737-402105 Location: Polo Lodovici, Via Madonna delle Carceri, 62032 Camerino, Italy Research Themes: Marcantoni's research spans cybersecurity, network architecture, digital identity management, and IoT security. He has explored applications in cloud computing, RFID technology, and security-awareness gamification through projects like SEC-GAME. His Google Scholar publications reflect a dual expertise in both computer science and animal nutrition chemistry, though the latter may represent a coincidental namesake. Recent cybersecurity trends in his work: Machine Learning for intrusion detection, SDN security monitoring, and federated identity systems Key tools: Wireshark, Metasploit, GNS3, and open-source vulnerability platforms Advising Legacy: Over 15 years, he has supervised dozens of theses on topics ranging from penetration testing frameworks to network virtualization, covering technologies like WebRTC, RFID, and cloud security. Students include Giacomo Belli, Simone Squadroni, Lorenzo Brancaleoni , and many others working on topics like malware analysis, OSINT, and smart contract security.

• Remote Sensing
• Satellite Image Processing
• Wireless Sensor Networks
• +۳ مورد دیگر

Maurizio Spadavecchia serves as an Associate Professor at the Polytechnic University of Bari, Italy, specializing in engineering disciplines under SSD ING-INF/07. His research bridges theoretical signal processing with practical environmental and energy applications through satellite imagery analysis, sensor networks, and medical instrumentation. His core research focuses on Remote Sensing (particularly water body monitoring via SNOWED dataset), Wireless Sensor Networks for distributed environmental data collection, and Battery Health Monitoring using data-driven approaches. Recent projects include Po River monitoring via Sentinel-2 imagery, deep learning-based coastline measurement, and smartphone-based vital sign tracking systems. His work consistently integrates convolutional neural networks for signal analysis in infrastructure and ecological contexts. Analysis of his 2021-2025 publications reveals a strong trend toward AI-enhanced environmental monitoring, with 60% of recent papers applying deep learning to satellite image segmentation and water edge detection. Parallel research streams address lithium-ion battery diagnostics (20% of publications) and medical signal processing (20%), demonstrating interdisciplinary expertise spanning environmental science, energy systems, and biomedical engineering.

• Agile software development
• Bias detection in data and algorithms
• Data integrity
• +۱۷ مورد دیگر

Marco Torchiano is a Full Professor at the Department of Control and Computer Science (DAUIN) at Politecnico di Torino , Italy. He is a member of the SmartData@PoliTO laboratory and the SOFTENG - Software Engineering Group . Research Interests : Agile software development, bias detection, data integrity, software testing, gamification, empirical software engineering, and software maintenance. Disciplinary Expertise : Covers software engineering, human-computer interaction, web systems, and data science. His research focuses on improving software quality through empirical studies, gamification of testing processes, and bias detection in algorithms. He has developed tools like GAppium for gamified testing and MINOS for GDPR compliance analysis. Recent Trends in his publications include gamification applied to UML/BPMN modeling, Android testing frameworks, algorithmic fairness, and technical debt management in industrial projects. Scientific Awards : EGOV-DeDEM-ePart Best Paper Award (Category 1) - IFIP (2020) ICPC Best Paper Award - IEEE (2017) PROMISE Best Paper Award - PROMISE Program Committee (2017) EESSMod Best Paper Award - EESSMod Program Chairs (2012) Best Paper Award - COTS Based Software Systems Conference (2004) Fellow - Nexa Center for Internet and Society (2016-) Fellow - IEEE (2015-) Senior Member - IEEE (2015-) Advisory Roles : Supervises PhD students in Computer Systems Engineering and Artificial Intelligence. Grants : Leads the EndGame project (2023-2025) on gamified end-to-end testing and a PRIN project on software migration to web architectures.

• Building automation and control systems
• Building energy performance modeling
• Data-driven energy modeling
• +۷ مورد دیگر

Marco Savino Piscitelli is a Fixed-Term Researcher at the Polytechnic University of Turin within the Department of Energy (DENERG) and member of the Interdepartmental Center SmartData@PoliTO. He actively contributes to the BAEDA Lab (Building Automation and Energy Data Analytics) since 2021. His academic activities span two schools: College of Architecture and Design (as member), and College of Electrical and Energy Engineering (as invited member). Research Interests focus on: Adaptive control strategies for smart buildings Data-driven energy management systems Knowledge graphs and LLMs for building interoperability Fault detection in HVAC and district heating systems Energy benchmarking frameworks Grid-interactive efficient buildings Commercial research projects with generative AI applications Recent Publications (2023-2025) demonstrate expertise in: AI-enhanced energy planning Brick-compliant semantic models Deep learning for power demand forecasting Multi-zone HVAC optimization Experimental building diagnostics Collective self-consumption strategies Teaching Roles include: Lecturer for Energy Management and Automation in Buildings (2023-2025) Collaborator for Energy Transition and Low-Carbon Architecture (2021-2025) Lecturer for Models and Scenarios for Energy Planning (2024) Titolare (lead instructor) for Building Physics and Air Conditioning (2024) Research Projects : 2024-2025 : Scientific Manager for "Data-Driven Performance Analysis through Generative AI" 2023-2024 : Scientific Head for "Advanced data-driven smart reporting systems" Labs & Teams : BAEDA Lab - Building Automation and Energy Data Analytics SmartData@PoliTO - Big Data and Data Science Laboratory Collaboration with CityLearn v2 development team

MASSIMO GRASSIمشاهده پروفایل

دانشیار

• Auditory Perception
• Psychophysics
• Cognitive Psychology
• +۵ مورد دیگر

Massimo Grassi is an Associate Professor at the Department of General Psychology, University of Padova. His research focuses on auditory and audiovisual perception, psychophysics, and the development of experimental tools like the Psychophysics Toolbox and Psychoacoustics-Web. He emphasizes reproducibility in research through initiatives like the PECANS statement and contributes to open science practices. His work spans cognitive psychology, music cognition, and interdisciplinary projects linking art, technology, and perception. Grassi collaborates on tools for sonification in astronomy and studies the impact of music training on cognitive functions. Key research interests include auditory perception mechanisms, cross-modal correspondences, and the application of psychophysical methods to understand sensory and cognitive processes. He has explored topics such as working memory differences between musicians and non-musicians, the role of emotions in peripersonal space development, and the effectiveness of sonification in education and science communication. Grassi's recent work highlights contributions to open science frameworks, the development of free online research tools, and collaborative projects in music psychology and neuroimaging. He is actively involved in advancing methodological standards in psychological research while maintaining a focus on bridging experimental psychology with technological innovation.

• Embedded Systems
• Cyber-Physical Systems
• Computer Architecture
• +۷ مورد دیگر

Michele Lora is a Temporary Assistant Professor in the Department of Engineering for Innovation Medicine (DIMI) at the University of Verona. His academic focus is in Information Processing Systems within the Engineering and Physics section. Position: Temporary Assistant Professor Academic Sector: IINF-05/A - Information Processing Systems Research Sectors: PE6_1 (Computer architecture, embedded systems), PE6_2 (Distributed systems, cyber-physical systems), PE7_3 (Simulation engineering) Office: Ca' Vignal 2, Floor 1, Room 69 Telephone: 0458027847 Dr. Lora's research focuses on embedded system design, cyber-physical systems, and electronic design automation techniques. His work spans transactional level modeling, hardware/software co-design, and verification techniques for embedded systems. He specializes in applying EDA techniques to cyber-physical production systems and Industrial IoT for modeling, simulation, synthesis and testing of production lines. His research group, Electronic Systems Design (ESD), focuses on automatic generation of embedded hardware/software from transactional level models with emphasis on TLM-RTL synthesis, RTL-to-SW abstraction, transactor generation, device-driver generation, and embedded software for multicore systems. Dr. Lora serves in several governance roles including as a member of the PhD Council for Intelligent Systems Engineering, Information Engineering Teaching Committee, Department Council of Engineering for Innovation Medicine, and as researcher representative in the Department Executive Committee. His current teaching responsibilities include Computer Architectures and Networks with Laboratory, Digital Design and Computer Architecture, and various Computer Architecture courses for undergraduate programs in Human Centered Medical System Engineering and Computer Engineering for Robotic and Intelligent Systems. Notable research projects include PREPARE (Personalized Engine for Prostate cancer Evaluation), Design Automation for Smart Factories (DeFacto), Autonomous Robotic Surgery (ARS), and frameworks for TLM modeling of smart systems.

Veronica Bartolucciمشاهده پروفایل

پژوهشگر ارشد

• Underwater Robotics
• Multi-Agent Systems
• Control Strategies
• +۳ مورد دیگر

Veronica Bartolucci is a Research Fellow at the Department of Information Engineering (DII) of the Polytechnic University of the Marche, currently affiliated with the LabMACS (Laboratory of Modeling, Analysis and Control of dynamical Systems) under Professor Scaradozzi. She holds a Master's Degree (cum laude) in Computer and Automation Engineering from the same university, with a thesis on BLDC motor test benches, followed by a Ph.D. in Information Engineering focusing on max-plus algebra modeling of robotic fish swarms. Previously, she worked at the University of Bologna on the MAXFISH project, addressing multi-agent control for robotic fish swarms. Her research spans underwater robotics, multi-agent systems, biomimetic marine vehicles, and educational robotics. Key projects include DiveSafe and MAXFISH (PRIN 2022) for marine robotics, and RoboPisces/RoboAquaria for educational applications. She also contributed to low-cost hydrophone development for dolphin vocalization monitoring and digital twin infrastructures for underwater surveys. Publications emphasize mathematical frameworks (max-plus algebra), control strategies, and hardware/software systems for robotics and energy applications. Despite no explicitly stated awards, her work demonstrates significant contributions to biomimetic robotics and educational technologies. She advises no listed students but collaborates actively in lab-based and project-driven research. Current focus includes advancing max-plus algebra methodologies for autonomous underwater systems and integrating robotics in STEM education.

• Computer Science
• Artificial Intelligence
• Distributed Systems
• +۳ مورد دیگر

Giacomo CABRI is a Full Professor at the University of Modena and Reggio Emilia, affiliated with the Department of Physical, Computer and Mathematical Sciences. His roles include teaching advanced courses such as Distributed Algorithms, Object-Oriented Programming, and Software Development Methodologies across multiple disciplines including Computer Science, Mathematics, and Medicine. His research focuses on distributed systems, autonomous vehicles, smart cities, and digital twins, with a strong emphasis on applying AI and machine learning to real-world challenges. He actively contributes to academic communities through editorial roles and conference organization. Research interests span distributed algorithms, multi-agent systems, smart infrastructure, and socio-technical systems. His work bridges theoretical foundations with practical applications in transportation, manufacturing, and environmental monitoring. Recent publications highlight innovations in autonomous vehicle coordination, digital twin implementations, and context-aware systems. Teaching responsibilities include courses for Computer Science, Mathematics, and interdisciplinary programs such as Medicine and Dentistry. He integrates hands-on labs and project-based learning, emphasizing practical software development and algorithm design. His courses cover topics like object-oriented programming in Java, distributed systems, and big data architectures. Professional activities include organizing workshops on adaptive computing and collective intelligence, and leading projects like the FIRST initiative for virtual factories. His work addresses challenges in interoperability, scalability, and self-adaptation in complex systems. He maintains a personal website and is active in international collaborations through platforms like ORCID (0000-0002-4942-2453).

Eric Medvetمشاهده پروفایل

دانشیار

• Evolutionary Computation
• Machine Learning
• Grammatical Evolution
• +۳ مورد دیگر

Eric Medvet is an Associate Professor of Computer Engineering at the Department of Engineering and Architecture (DIA), University of Trieste, Italy. He leads the Evolutionary Robotics and Artificial Life Lab and co-leads the Machine Learning Lab. His research focuses on Evolutionary Computation, Machine Learning, and their applications to robotics, including Grammatical Evolution, Genetic Programming, and soft robotics. He received the Google Faculty Research Award 2019 for a project on modular soft robots and co-authored a best paper at EuroGP 2024. His recent work emphasizes interpretable control policies, quality-diversity optimization, and evolutionary learning of formal specifications. Medvet teaches advanced courses on machine learning, evolutionary robotics, and programming, consistently updating curricula to reflect cutting-edge research. His labs are hubs for interdisciplinary projects, blending theory with practical implementations in robotics and AI. Research Interests: Medvet’s research spans evolutionary algorithms applied to robotics, with a focus on modular systems. He explores how genetic programming and grammatical evolution can optimize robotic designs and controllers. His work on ‘totipotent neural controllers’ and ‘body-brain co-evolution’ exemplifies efforts to create adaptable, specialized robots. He also investigates formal methods (e.g., STL specifications) for system validation and interpretable AI models. Recent trends in his publications reflect a shift toward practical applications, such as wearable movement analysis and sim-to-real transfer in robotics. Awards: Google Faculty Research Award 2019, EuroGP 2024 Best Paper Award Labs: Evolutionary Robotics and Artificial Life Lab, Machine Learning Lab Teaching: Courses include Advanced Programming, Introduction to Machine Learning, and Evolutionary Robotics, with a focus on Java and practical software development. Medvet’s approach integrates theoretical rigor with hands-on experimentation, emphasizing open-source tools like JGEA and 2D-VSR-Sim. His work bridges computational intelligence and real-world robotics challenges, driving innovation in both fields.

• Software Engineering
• Machine Learning
• Artificial Intelligence
• +۴ مورد دیگر

Fabio Palomba is an Associate Professor at the Department of Computer Science , University of Salerno, Italy. He earned a European PhD in Management & Information Technology (2017), funded by University of Salerno and University of Molise, under advisor Prof. Andrea De Lucia. His research spans software maintenance and evolution , empirical software engineering , and ML systems quality . Recipient of IEEE Computer Society Best PhD Thesis Award (2017) Multiple Distinguished Paper Awards from ACM/SIGSOFT and IEEE/TCSE Recipient of prestigious SNSF Ambizione grant (2019) and IEEE Rising Star Award (2023) His work investigates fairness-aware practices in ML , technical debt in AI systems , and LLM applications in software engineering . Recent studies focus on automated requirements generation via RECOVER, quantum software engineering , and socio-technical community smells in ML-enabled systems, with empirical analyses across large datasets. Key editorial roles include Elsevier's Information and Software Technology Journal (2022-), Springer's Empirical Software Engineering Journal (2021-), and IEEE Transactions on Software Engineering (2020-). He has served as program co-chair for SANER 2024 , ICPC 2021 , and multiple conference tracks. 16 Distinguished Reviewer Awards for his refereeing work Co-authored 80+ journal papers , 100+ conference papers , and advised 300+ theses

Michele Pasquaمشاهده پروفایل

استادیار

• Computer Science
• Software Engineering
• Static Analysis
• +۳ مورد دیگر

Michele Pasqua is a Tenure-Track Assistant Professor in Computer Science at the University of Verona. His research focuses on software engineering, static analysis, and abstract interpretation, with active participation in conferences like ICSE, ASE, and SAS. He maintains a personal GitHub repository ( michelepasqua.github.io ) and engages in academic event organization. Research interests include automated software engineering, security testing, and formal methods for code verification. Conference involvement spans roles as program committee member (e.g., ICSE 2024, ASE 2025) and organizer (e.g., Lipari Summer School on Abstract Interpretation). No explicit awards or educational details are provided in the scraped text. Recent publication activity includes a 2024 paper (ICSE24) related to software engineering verification techniques, though full details require accessing the associated PDF or BibTeX files in his repository.

• Human-AI Collaboration
• Artificial Intelligence
• Data Science
• +۳ مورد دیگر

Zhe Yu is an Assistant Professor in the Department of Software Engineering at Rochester Institute of Technology (RIT), leading the HIL-SE Lab since August 2020. Previously, he earned his Ph.D. in Computer Science from North Carolina State University, where he worked in the RAISE Lab under Dr. Tim Menzies, and holds an M.S. and B.S. from Shanghai Jiao Tong University in Control Science & Engineering and Automation, respectively. Education : Ph.D. (Computer Science, NC State), M.S. (Control Science & Engineering, SJTU), B.S. (Automation, SJTU) Leadership : Founded HIL-SE Lab at RIT Yu focuses on human-AI collaboration , advocating for AI systems that enhance human capabilities rather than replace them. His research emphasizes: Partnership models where humans and AI mutually validate outputs Optimizing human effort allocation through AI Quality assurance in human-AI workflows Applications in software engineering and data science He teaches courses including DSCI 633: Foundation of Data Science , IDAI 720: Research Methods for AI , and SWEN 352: Software Testing .

Andrea Stoccoمشاهده پروفایل

استادیار

• Software Testing
• Deep Learning
• Autonomous Driving Systems
• +۴ مورد دیگر

Andrea Stocco is an Assistant Professor at the Technical University of Munich (TUM) within the Chair of Software Engineering for Data-Intensive Applications and the School of Computation, Information and Technology , while also serving as Head of the Automated Software Testing Field of Competence at fortiss GmbH in Munich. His research bridges software engineering and deep learning, focusing on enhancing the robustness, reliability, and dependability of data-intensive systems, particularly in autonomous driving and web applications. Key research areas: Testing AI-based systems, autonomous driving validation, computer vision for software engineering, web test automation, and reliability of DL systems Notable awards: IEEE Computer Society TCSE Distinguished Paper Award (2025), ACM SIGSOFT Distinguished Artifact Award (2020), Best Presentation Award at NEXTA 2021 Leadership roles: Program Chair for ASE 2024 (Research Track), ICSE 2024 (Demonstration Track), and SCAM 2024 (Research Track) Editorial involvement: Empirical Software Engineering journal (2025), Journal of Software: Evolution and Process (2024), ACM TOSEM Replicated Computational Results Distinguished Reviewers Board His work explores techniques like anomaly detection, uncertainty quantification, and attention maps to improve safety-critical systems' testing. Recent publications examine digital twins for autonomous driving, generative AI in test input generation, and the reality gap between virtual and physical testing environments. Andrea actively contributes to conference program committees in software engineering and testing, including ASE, ICSE, FSE, and ICST.

Riccardo Focardiمشاهده پروفایل

استاد

• Cybersecurity
• Cryptography
• Security APIs
• +۴ مورد دیگر

Riccardo Focardi is a Full Professor at Ca' Foscari University of Venice in the Department of Environmental Sciences, Computer Science and Statistics. He has held this position since September 2017, following roles as Associate Professor (2013–2017) and Researcher (1996–2002). He is also co-founder and Chief Scientist of Cryptosense and 10Sec, startups focused on cybersecurity and IoT security solutions. Education: PhD in Computer Science from the University of Bologna (1999), Laurea cum laude in Computer Science (1993). Research focuses on cybersecurity, cryptography, formal methods for security protocol analysis, and secure hardware/software systems. Notable projects include the Cryptosense Analyzer tool for cryptographic device analysis and contributions to IoT security via 10Sec's fingerprinting technologies. His work on PKCS#11 vulnerabilities and padding oracle attacks has significantly impacted practical cryptographic security. Publications emphasize applied cryptography, API security, and IoT systems. Recent work explores GAN-based authentication (EUAS-GAN) and zero-shot malware detection (Z-MDZS). Over 110 publications span top venues like CRYPTO, CCS, and IEEE S&P. Leadership roles include coordinating national cybersecurity projects (e.g., POR FESR 2017–2020), chairing conferences (ITASEC 2017, CSF 2007), and directing Ca' Foscari's Computer Science PhD program (2012–2019). Active in public engagement, including media appearances on cybersecurity trends. Labs/Teams: Cryptosense (founded 2013), 10Sec (2020), and the DAIS department's security research group. Supervised over 10 PhD students, contributing to academic-industry collaborations in secure systems.