جست‌وجوی استاد و پژوهشگر

Luca Ulrichمشاهده پروفایل

استادیار

• Artificial Intelligence
• Computer Vision
• 3D Graphics
• +۵ مورد دیگر

Luca Ulrich is an Assistant Professor at the Politecnico di Torino , Department of Management and Production Engineering (DIGEP). He obtained a Master’s Degree in Computer Engineering (2016) and a PhD in Management, Production, and Design (2021). Research Interests His work focuses on the synergy between Artificial Intelligence (AI) and Extended Reality (XR) for human-centered applications in healthcare, industrial automation, and cultural heritage. Key areas include facial expression recognition, 3D graphics in biometrics, and adaptive human-AI interfaces. Teaching Roles Course Collaborator for 3D Graphics in Biometric Applications (Biomedical Engineering, 2019-2025) Lecturer for Industrial Technical Drawing (Mechanical, Chemical, and Manufacturing Engineering) Scientific Contributions He leads the SMAIL-AI project (2025-2027) and has co-invented three national patents in sports performance analysis, facial recognition, and surgical simulation. His publications span AI in surgery, lip-reading for vocal rehabilitation, and immersive systems. PhD Students Supervised Antonio Lo Faro (Human-AI Interfaces) Rossella Ruggieri (AI in Complex Environments) Chiara Innocente (Behavior Analysis) Federico Salerno (Surgical Guide Analysis) Giorgia Marullo (Phantom Limb Therapy) Francesca Nonis (Facial Emotion Recognition)

Enrico Vezzettiمشاهده پروفایل

استاد

• 3D Face Analysis
• 3D Scanning
• Computer-Aided Design
• +۱۲ مورد دیگر

Enrico Vezzetti is a Full Professor at the Department of Management and Production Engineering (DIGEP) , Polytechnic University of Turin, Italy. He serves as Coordinator of basic subjects for the 2nd year of Engineering and contributes to doctoral programs in Management and Production Engineering. His research focuses on virtual/digital human behavior analysis for human-centered design , spanning 3D modeling , product lifecycle management (PLM) , and augmented reality (AR) applications in medicine and industry. Research Interests : 3D Face Analysis, Human-Computer Interaction, Product Design, Medical Imaging, Computational Modeling, Industrial Innovation. His recent work explores 3D methodologies for predicting post-surgical facial changes, machine learning in VR environments for stress assessment, and augmented reality systems for orthopedic and maxillofacial surgery. He has developed patented tools for 3D surgical guides and real-time facial expression recognition . He has authored over 100 publications and holds editorial roles in journals like Pattern Recognition and Applied Sciences . His projects include regionally and EU-funded initiatives such as DAS (Design for Augmented Surgery) and Media - Museo Emozionale , focusing on healthcare and cultural preservation. Scientific Awards : Young Researchers - 2011 Award (2011) Polytechnic University of Turin Publications Award (2011, 2012) He leads research groups in 3D Lab and collaborates with institutions on digital twins , smart manufacturing , and medical AI systems , emphasizing cross-fertilization between academia and industry .

• Biomedicine
• Neuroscience
• Advanced Diagnostics

Giulio Musotto is a Part-Time Lecturer at the University of Palermo's School of Medicine and Surgery, specializing in Biomedicine, Neuroscience, and Advanced Diagnostics. His work bridges computational modeling with clinical applications in cardiovascular research. Role: Contract Teacher Institution: University of Palermo His research focuses on thrombus dynamics in atrial fibrillation , using fluid-structure interaction analyses to assess thromboembolic risks. He has also explored spatial cognition in neuroscience and integrated 3D printing into undergraduate neuroscience education. Recent publications highlight his expertise in Computational hemodynamics Patient-specific modeling Cardiac biomechanics through studies on left atrial appendage morphology and mitral regurgitation. Contact: giulio.musotto@unipa.it

• Speech Therapy
• Neuroscience
• Dyslexia
• +۷ مورد دیگر

Bianca Sanfilippo is a contract teacher at the University of Palermo , affiliated with the School of Medicine and Surgery . Her work spans Speech Therapy and Neuroscience , focusing on developmental and learning disorders. Research Interests Speech Therapy interventions for learning disabilities Neurodevelopmental disorders (Down Syndrome, Dyslexia) Executive Function roles in education Home literacy environments Pragmatic communication disorders Key Article Trends 2023 studies emphasize personalized rehabilitation for dyslexia and gesture-language correlations 2022 research explores home literacy, executive functions, and Down syndrome Themes centered on neurocognitive foundations of speech therapy Contact Email: bianca.sanfilippo@unipa.it

• 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

Paolo Baldanمشاهده پروفایل

استاد

• Formal Methods for Software Reliability
• Programming Languages
• Concurrency Theory
• +۶ مورد دیگر

Paolo Baldan is a Professor of Computer Science at the Department of Mathematics of the University of Padova, where he maintains office 6DA6. Previously, he served as an assistant professor at the University of Venice's Computer Science Department and as a PostDoc Researcher at the University of Pisa's Department of Computer Science. His research focuses on Formal Methods for Software Reliability and Programming Languages , with particular expertise in Concurrency Theory, Petri Nets, and Graph Transformation Systems. Professor Baldan has led multiple research projects including the current MUR Project RAP (2023-2025) and previous initiatives like ASPRA (2019-2022) and ANCORE (2015-2016). His publication record spans journal articles, conference papers, and technical reports in theoretical computer science. His recent work examines resource awareness in programming, program analysis techniques, and verification of concurrent systems. The publications demonstrate consistent contributions to formal methods with applications to software reliability. Professor Baldan actively participates in the academic community through conference organization and committee work, including involvement with CALCO, Petri nets conferences, and ICGT. His upcoming commitments include CSL 2026. He teaches courses including Computability , Languages for Concurrency and Distribution , and Algorithms and Data Structures at the University of Padova. Office hours are held Wednesdays 11:00-13:00, requiring advance contact for meetings.

Francesco Ranzatoمشاهده پروفایل

استاد

• Abstract Interpretation
• Programming Languages
• Formal Methods
• +۴ مورد دیگر

Francesco Ranzato is a Full Professor in the Department of Mathematics at the University of Padova, Italy, where he conducts research in theoretical computer science with a focus on abstract interpretation, programming languages, and formal methods. His academic career spans over three decades with continuous contributions to the field, as evidenced by his extensive publication record from 1994 through 2025. Professor Ranzato's research interests center on abstract interpretation theory and its applications to program analysis and verification. In recent years, he has expanded his work to include machine learning verification, particularly focusing on robustness certification of classifiers using abstract interpretation techniques. His work bridges theoretical foundations with practical applications, as demonstrated by multiple open-source software artifacts available on GitHub. His publication record shows a clear evolution from foundational work in abstract domains and completeness properties to practical algorithms for simulation and model checking, and most recently to applications in machine learning security. The 15 most recent publications reveal a strong focus on verifying properties of machine learning models, with particular attention to decision trees, support vector machines, and k-Nearest Neighbors classifiers. Among his notable recognitions are the POPL Distinguished Paper Award, LICS 2021 Best Paper Award, Microsoft Research SEIF award, Amazon Research Award, and the WhatsApp Privacy Aware Program Analysis Award. These awards highlight the significance and impact of his contributions to programming languages and formal methods research. Professor Ranzato maintains active research collaborations, as evidenced by his co-authored publications, and has successfully secured research funding from both academic and industry sources. His work with students and junior researchers is reflected in the numerous joint publications and the development of practical tools for abstract interpretation and machine learning verification. His research group operates through the Department of Mathematics at the University of Padova, with a strong presence in international research communities as shown by his editorial roles (e.g., editing SAS 2017 proceedings) and regular participation in top-tier conferences in programming languages and formal methods.

Annalisa Barlaمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Machine Learning
• Medical Informatics
• +۵ مورد دیگر

Annalisa Barla is an Associate Professor at the Department of Computer Science, Bioengineering, Robotics and Systems Engineering (DIBRIS) at the University of Genoa. She holds an interschool affiliation in mathematical, physical, and natural sciences. Her work bridges AI, bioengineering, and interdisciplinary research in design. Teaching focuses on AI fundamentals, medical AI applications, data visualization, and image processing across master's programs in product design, bioengineering, and computer science. Research interests include AI-driven medical diagnostics (Alzheimer's, epilepsy), network science, and interdisciplinary design analysis. Her research applies machine learning to healthcare, neuroscience, and academic collaboration networks. Notable projects include Alzheimer's detection via deep learning and AI-based redesign of university websites.

• Digital Sociology
• Cybersecurity
• Information Security
• +۴ مورد دیگر

Stefano De Paoli is a Professor of Digital Society at Abertay University's Department of Sociological and Psychological Sciences. His research focuses on the intersection of digital technologies and societal structures, with a particular emphasis on cybersecurity, open science, and qualitative research methodologies. He has published extensively on topics such as penetration testing, large language models in thematic analysis, and collaborative reputation systems. His work bridges theoretical frameworks with empirical studies, often employing participatory design and ethnographic approaches. Recent contributions include exploring the ethical implications of AI-driven research methods and the evolution of cybercrime studies. Key areas of investigation include: Information security practices in organizations Impact of AI on qualitative research methodologies Open science platforms and their evaluation metrics Social innovation and digital collaboration frameworks His research outputs reflect a commitment to interdisciplinary approaches, often combining insights from sociology, computer science, and policy studies. Notably, he has led projects on cybersecurity challenges faced by law enforcement and the design of equitable crowdfunding mechanisms for humanities research.

Mirko Mazzoleniمشاهده پروفایل

دانشیار

• System Identification
• Fault Diagnosis
• Kernel Methods
• +۸ مورد دیگر

Mirko Mazzoleni is an Associate Professor at the Department of Management, Information and Production Engineering, University of Bergamo, Italy. His research focuses on system identification, fault diagnosis, kernel methods, and Industry 4.0 applications. He holds a Master's in Computer Science Engineering (2014) and a Ph.D. in Engineering and Applied Sciences (2018). Before becoming an Associate Professor, he served as an Assistant Professor at the Control and Automation Laboratory (CAL) from 2019 to 2024. His work integrates data science, signal processing, and machine learning to develop robust algorithms for supervisory systems and fault detection in electromechanical actuators. Notable contributions include kernel-based identification methods, visualization tools for classification results (Confusion Star/Gear), and supervision frameworks for industrial equipment. He co-founded AISent srl, applying technological solutions to industry challenges. He teaches courses like Adaptive Learning and Estimation , System Identification , and Advanced Methods for Fault Diagnosis . His research spans aerospace applications (e.g., jamming detection in aircraft actuators), vibration signal analysis, and data-driven control strategies. Recent projects include robust filter design for electromechanical systems and guidelines for industrial supervision solutions.

Alberto Luigi Cologniمشاهده پروفایل

مدرس

• Mechatronics
• Control Systems
• Industrial Automation
• +۵ مورد دیگر

Alberto Luigi Cologni is a Lecturer at the University of Bergamo and Project Manager at e-Novia spa. He holds an MSc in Computer Engineering (2009) and PhD in Mechatronics (2013) from the University of Bergamo. His research focuses on control systems, industrial automation, and mechatronics with applications in polymer processing, robotics, and remote maintenance systems. Key professional roles include Research Assistant at CAL (2014-2015), leading the Touchplant and HOLMES EU-funded projects, and Researcher Assistant at Intellimech (2010). His work spans actuator control, SCADA systems, and embedded software for industrial automation. Research interests emphasize closed-loop control strategies, vibration damping systems, and data-driven approaches in manufacturing processes. He has contributed to over 20 peer-reviewed publications since 2010, addressing topics like anti-sway crane control, modular automation software, and telepresence maintenance systems. His projects often involve collaboration with industrial partners, exemplified by the Cometha and Remote Maintenance systems initiatives. Current teaching includes the Industrial Automation course at University of Bergamo.

• Artificial Intelligence
• Machine Learning
• Neural-Symbolic AI
• +۵ مورد دیگر

Marco Gori is a Full Professor at the Department of Information Engineering and Mathematical Sciences , University of Siena. His research spans Artificial Intelligence , Machine Learning , and Neural-Symbolic AI , with significant contributions to Educational Technology and Knowledge Graphs . He teaches Algorithms and Data Structures for undergraduate Management Engineering and Fundamentals of Machine Learning for graduate Artificial Intelligence and Automation Engineering . His recent work integrates Graph Neural Networks and State-Space Models for tasks like educational quiz generation and interoperable supply chain traceability. His publications highlight trends in Hybrid AI , focusing on interpretable models, cross-language educational tools, and temporal sequence processing. Articles like Grounding Methods for Neural-Symbolic AI and Interpretable-by-design Link Prediction underscore his emphasis on explainability and knowledge integration in AI systems.

Edmondo Trentinمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Neural Networks
• Pattern Recognition
• +۵ مورد دیگر

Edmondo Trentin is an Associate Professor of Artificial Intelligence at the Department of Information Engineering and Mathematics (DIISM), University of Siena, Italy. He chairs the IAPR Technical Committee 3 (Neural Networks & Computational Intelligence) and serves as an Associate Editor for Neural Processing Letters . His research focuses on neural networks, probabilistic models, and their applications in bioinformatics, speech processing, and pattern recognition. Trentin has taught extensively at both undergraduate and graduate levels, including courses on Artificial Intelligence, Neural Networks, and Pattern Recognition. He has advised numerous PhD students and contributed to international conferences and workshops. His work integrates machine learning with statistical methods, emphasizing hybrid models for complex data analysis. Teaching Highlights: Artificial Intelligence (MSc. courses since 2001) Neural Networks for Statistical Pattern Recognition Machine Learning for Graphs Supervised and Unsupervised Learning Research Interests: Connectionist density estimation Probabilistic graphical models Hybrid ANN/HMM systems Bioinformatics applications Professional Activities: Former Vice-Chair of IAPR-TC3 IEEE Computational Intelligence Society Secretary (2005-2006) Organizer of international workshops on neural networks and pattern recognition

• Second Language Acquisition
• Pragmatics
• Sociolinguistics
• +۲ مورد دیگر

Daniele Artoni is an Associate Professor in Slavic Studies at the University of Verona's Department of Foreign Languages and Literatures. He holds a PhD in Linguistics and leads the interdisciplinary research group GIAM, focusing on inclusive foreign language teaching methodologies for Russian and English. His academic responsibilities include coordinating the continuing education course for Russian language teachers (RKI) and serving on multiple departmental committees including the PhD Council for Linguistics. His research explores: Pragmatic competence development in Russian learners Accessible teaching frameworks for visually impaired students Post-Soviet language policy analysis 19th-20th century cultural relations between Russia and the Caucasus He currently directs the PRIN2022 national research project 'SyllaRus' developing Russian language teaching syllabi. As principal investigator, he manages several grants including: 'Verso una Glottodidattica Inclusiva' (2022-present) 'Per una didattica accessibile della lingua russa' (2019-present) He coordinates the GIAM research laboratory which develops blended learning technologies and inclusive pedagogical models for university-level language instruction.