Find Academic Supervisors

Barbara RussoView profile

Professor

• Machine Learning
• Software Engineering
• Systems Reliability
• +4 more

Barbara Russo is a Full Professor at the Faculty of Computer Science of the Free University of Bozen-Bolzano, Italy. She is a member of the International Software Engineering Research Network (ISERN) and has held visiting researcher positions at the Max-Planck Institute for Mathematics (Germany) and the University of Liverpool (UK). Her research focuses on Machine Learning in Software Engineering, Software Reliability/Testing, and Systems Engineering. She founded and coordinated the Software and Systems Engineering (SwSE) research group (2014–2017) and is involved in initiatives like the European Masters Program in Software Engineering (EMSE). Awarded the 2007 Best Public-Private Collaboration Award for establishing a dual BSc program in Computer Science. Established a makerspace (now FabLab) at her faculty and contributed to projects like the Euregio Trustworthy AI Lab. Research spans DevOps processes, embedded systems vulnerability, and collaborative AI assurance. Her work emphasizes empirical software engineering and practical industry collaboration, with notable contributions to scalability testing, performance modeling, and vulnerability detection.

• Database Systems
• Assistive Technology
• Smart Home Systems
• +5 more

Sara Comai is an Associate Professor at the Politecnico di Milano , affiliated with the Department of Electronics, Information and Bioengineering . She coordinates the Assistive Technology Group (ATG) and leads the MEP (Maps for Easy Paths) project. Research Focus : Database systems, smart home technologies, indoor localization, and assistive solutions for elderly/dementia patients Recent Trends : 2025-2023 publications highlight Occupancy detection via Wi-Fi/infrared sensors Behavior classification for Alzheimer's patients Wearable/RFID-based health monitoring Human-robot collaboration in agriculture Adaptive machine learning for land use segmentation

• Gastroenterology
• Endoscopy Techniques
• Oncological Endoscopy
• +3 more

Prof. Alessandro Repici is a Full Professor of Gastroenterology at Humanitas University Medical School and Director of the Digestive Endoscopy Unit at Humanitas Research Hospital in Milan, Italy. He specializes in advanced endoscopic techniques, including ERCP, diagnostic EUS, ESD, and stenting, with a focus on gastrointestinal malignancies and innovative endoscopic therapies. His academic career includes professorships at the University of Turin (2000–2005) and visiting roles at Georgetown University (2016) and the Mayo Clinic (2017). Educations: MD from University of Messina (1990), fellowships at Molinette Hospital (Turin), Centre Chirurgical de l'Alma (Paris), Universitatskliniken (Tubingen), and Wellseley Hospital (Toronto). Research: Over 50 studies on endoscopic innovations, including FDA/EMA-approved devices. Lead roles in international collaborations with institutions like the University of Rotterdam and Mayo Clinic. Leadership: Chair of the Italian Society of Digestive Endoscopy’s Strategic Team (2012), member of World Gastroenterology’s Publication Committee, and editorial board roles in journals like Gastrointestinal Endoscopy . He founded webendoscopy.com and organizes the IMAGE live endoscopy course. His work emphasizes AI integration in endoscopy and microbiota research in IBD.

• Multi-criteria analysis
• Urban planning
• Sustainable development
• +5 more

Francesca Abastante is an Associate Professor at the Polytechnic University of Turin (DIST Department) and member of the R3C Interdepartmental Centre. She holds a PhD in Regional and Urban Studies (2013) and specializes in Multicriteria Decision Analysis (MCDA) applied to urban and territorial projects. Her research focuses on integrating MCDA with financial analytics and visualization tools to support real-time decision-making in sustainable development. Key roles include scientific management of national projects (Chiomonte SMART, BIG/OPEN DATA) and participation in EU initiatives (SCORE, GLOSSA). She teaches courses in urban economics, real estate valuation, and project feasibility analysis at Politecnico di Torino. She serves on editorial boards for journals like *International Journal of Sustainable Development and Planning* and is an active member of professional societies (SIEV, MCDM). Her work emphasizes urban sustainability, climate action (SDGs 11 & 13), spatial analysis, and resilience planning. Projects involve evaluating low-carbon transitions, neighborhood regeneration, and SDG implementation frameworks using innovative methodologies like WebGIS platforms and participatory serious games.

Samanta RosatiView profile

Assistant Professor

• Biomedical Engineering
• Medical Imaging
• Machine Learning in Healthcare
• +5 more

Samanta Rosati is an Assistant Professor at the Department of Electronics and Telecommunications at the Polytechnic University of Turin. She holds a Master’s Degree and Ph.D. in Biomedical Engineering from the same institution. Her research focuses on biomedical data interpretation, signal processing, and medical device software development. Key areas include radiomics, AI for CAD systems, and clinical process modeling. Education: Ph.D. in Biomedical Engineering (2014), Politecnico di Torino Master’s Degree in Biomedical Engineering (2010), Politecnico di Torino Research Interests: Medical imaging analysis (e.g., CT/MRI segmentation) Machine learning applications in healthcare Wearable sensor systems for telemedicine Clinical workload modeling Current Projects: Development of a wearable multi-sensor array for heart failure monitoring AI-driven systems for personalized chemotherapy prediction Telemedicine frameworks for heart failure management Grants & Advising: Actively supervises projects on medical device software certification and hernia repair outcomes analysis. Collaborates on multi-center studies for cancer treatment response prediction. Labs/Teams: Leads projects in medical AI and wearable technology within the Department’s biomedical engineering group, focusing on bridging clinical needs with engineering solutions.

• Autonomous Driving Systems
• Software Reliability Engineering
• Hardware Fault Tolerance
• +3 more

Jacopo Sini is a Research Fellow at the Department of Automatic Control and Computer Science (DAUIN) of the Polytechnic University of Turin. His research focuses on safety-critical automotive systems, software reliability engineering, and emotion recognition. He collaborates on Master's courses related to model-based software design and autonomous vehicles. He is affiliated with the CAD - Electronic CAD & Reliability Group, contributing to projects involving ISO26262 compliance, hardware fault tolerance, and simulation methodologies. His work includes developing real-time driver monitoring systems and enhancing social acceptance of autonomous vehicles through emotion analysis. Key research outputs include studies on control flow checking for automotive embedded systems, emotion recognition algorithms, and test benches for hardware failure diagnostics. Recent publications explore Rust programming language safety features and AR-based educational platforms.

Luca ArditoView profile

Associate Professor

• Software Engineering
• Mobile Computing
• Gamification in Education
• +3 more

Luca Ardito is an Associate Professor at the Department of Control and Computer Engineering (DAUIN) of Politecnico di Torino. His research focuses on software engineering methodologies, mobile computing, and gamification strategies in education and testing. His work integrates technical domains such as Android development, GUI testing automation, energy efficiency in software systems, and IoT security. Ardito is a core member of the SoftEng research group, contributing to projects like SIFIS-home for privacy-preserving smart home systems. Research Interests: Advanced GUI testing techniques for Android and web applications Application of gamification in software education and quality assurance Energy-aware software development and green computing practices Certification frameworks for IoT device firmware and cybersecurity His recent work emphasizes empirical studies on gamification in UML modeling education, Kotlin adoption in Android ecosystems, and innovative approaches to firmware certification. Ardito has pioneered tools like Umlegend for gamified UML learning and Bipmin for BPMN education. Grants & Collaborations: Leading multidisciplinary projects combining computer science with agriculture (e.g., UAV-based hazelnut tree characterization) Active in industry partnerships for mobile testing frameworks (e.g., TOGGLE library) Labs & Teams: Core contributor to Politecnico's SoftEng Research Group , collaborating on projects like SIFIS-home (FP7/ERC-funded).

Pier Luca LanziView profile

Professor

• Artificial Intelligence
• Machine Learning
• Multiagent Systems
• +7 more

Pier Luca Lanzi is a Full Professor at Politecnico di Milano, affiliated with the Department of Electronics, Information, and Bioengineering (DEIB). He leads the Artificial Intelligence and Robotics Lab (AIRLab), focusing on interdisciplinary research at the intersection of AI, robotics, and human-centric technologies. His work emphasizes applications in gaming, healthcare, and education, leveraging machine learning, evolutionary algorithms, and virtual reality. Education: Not explicitly stated in the provided texts. Affiliations: Director of the AIRLab; core member of DEIB. His research interests span artificial intelligence, multiagent systems, procedural content generation for games, serious games for rehabilitation, and AI-driven medical imaging. He explores how AI can enhance learning experiences (e.g., VR classrooms for physics and history) and improve therapeutic outcomes through interactive frameworks like the IGER system for stroke rehabilitation. Notable contributions include frameworks for automated level design in games (e.g., DOOM level generation via GANs), AI-assisted diagnostic imaging systems, and exergaming solutions for juvenile arthritis patients. His work often bridges computational intelligence with real-world applications, emphasizing human-centered design. Advising & Grants: While no specific grant details are provided, his prolific publication record suggests sustained research activity. Students and collaborators include prominent names in AI and robotics, though formal advisee名单 are not listed here. Labs/Teams: Directs the AIRLab, which develops cutting-edge technologies in AI, robotics, and human-technology interaction. Collaborates with industry and academic partners on projects ranging from VR educational tools to medical exergames.

Paola BellisView profile

Assistant Professor

• Innovation Management
• Organizational Behavior
• Design-Driven Innovation
• +4 more

Paola Bellis is a Junior Assistant Professor in Management Engineering at Politecnico di Milano's School of Management, specializing in innovation dynamics and collaborative sensemaking. She coordinates IDeaLs, a Politecnico di Milano and Center for Creative Leadership initiative involving 8 companies to explore organizational innovation engagement. Previously, she served as Product Manager at illycaffè's Global Marketing division. Education: Paola holds a PhD, MSc, and BSc in Management Engineering from Politecnico di Milano. Research Interests: Paola focuses on pairs dynamics in innovation, strategic innovation management, and digital transformation. Her work examines how collaborative relationships (e.g., pairs) drive organizational innovation, resilience, and vision creation. Key themes include design-driven innovation, leadership practices, and the intersection of AI with innovation processes. Teaching: She teaches 'Comportamento Organizzativo' (Organizational Behavior) and contributes to MBA/EMBA programs, emphasizing Innovation, Design & Project Management (IDPM). Grants & Service: While specific grants are unlisted, her IDeaLs platform reflects significant collaborative research funding. She actively contributes to academic service through course development and platform coordination. Labs/Teams: IDeaLs serves as her primary research nexus, blending academic and corporate partnerships to address innovation challenges.

Jessica GliozzoView profile

Research Fellow

• Bioinformatics
• Machine Learning
• Deep Learning
• +3 more

Jessica Gliozzo is a research fellow in bioinformatics at the IRCCS Ca' Granda – Ospedale Maggiore Policlinico of Milan and collaborates with the AnacletoLab (Bioinformatics and Computational Biology laboratory). She holds a BSc in Medical Biotechnology from the University of Milan (2014) and an MSc in Molecular Biotechnology and Bioinformatics from the same institution (2016). Her primary research interests include: Bioinformatics Machine Learning Deep Learning applications in genomics Analysis of Next Generation Sequencing data Dr. Gliozzo's current research focuses on the analysis of Next Generation Sequencing (NGS) data from patients affected by primitive hematopoietic proliferative disorders of the skin. She is actively developing deep learning neural networks for the prediction and prioritization of regulatory variants in human diseases and creating network-based semi-supervised models to predict patients' clinical outcomes by leveraging heterogeneous biological data. Her recent publications demonstrate a strong trend toward integrating multi-omics data, developing knowledge graphs for RNA interactions, and applying advanced machine learning techniques to clinical problems, particularly in cancer research and genomic analysis. Her work spans computational biology, medical informatics, and artificial intelligence applications in healthcare, with a particular emphasis on dimensionality reduction techniques, network-based approaches, and resource-efficient computational methods. Network-based patient similarity analysis RNA knowledge graph construction Resource-limited medical image processing Large language models for protein science Multi-omics data integration Dr. Gliozzo has maintained extensive collaborations with researchers including Giorgio Valentini, Elena Casiraghi, Marco Mesiti, and Alessandro Petrini across numerous publications in reputable journals such as BMC Bioinformatics, Scientific Reports, and Frontiers in Bioinformatics, demonstrating consistent research productivity from 2017 through 2025.

• Computer Networks
• Edge Computing
• Digital Twins
• +4 more

Armir Bujari is an Associate Professor at the Department of Computer Science within the Faculty of Science and Engineering at the University of Bologna. His research focuses on advanced networking, edge computing, digital twins, and blockchain applications. He holds a scientific disciplinary sector specialization in Information Processing Systems (IINF-05/A). Key research areas include: Edge and cloud computing architectures IoT and smart systems integration Blockchain-enabled data ecosystems Urban and industrial digital twins Disaster communication protocols Recent publications emphasize innovative solutions in federated learning, QUIC protocol optimization for satellite networks, and digital twin applications in logistics and smart cities. His work bridges theoretical advancements with practical implementations in 5G/6G networks, disaster response systems, and sustainable energy grids. Office location: 1st floor, Palazzina ex-scuderie, Viale Risorgimento 2, Bologna. Reception hours are typically Mondays 3-5 PM, with flexible scheduling via email.

• Explainable AI
• Personal Data Mining
• Clustering
• +7 more

Riccardo Guidotti is an Assistant Professor (RTD-B) at the Department of Computer Science, University of Pisa, and a member of the Knowledge Discovery and Data Mining Laboratory (KDDLab), a joint research group with the Information Science and Technology Institute of the National Research Council (ISTI-CNR) in Pisa, Italy. His research spans explainable AI, personal data mining, clustering, and transactional data analysis. PhD in Computer Science, University of Pisa Master's Degree in Computer Science, University of Pisa (110/110 cum laude) Bachelor's Degree in Computer Science, University of Pisa (110/110 cum laude) His research interests include Explainable AI , Personal Data Mining , Clustering , and Transactional Data Analysis . He focuses on making AI systems interpretable and understandable, especially through local and global explanation techniques applied to behavioral and mobility data. His work bridges theoretical models with real-world applications in retail, mobility, and social networks. The recent publications highlight a strong trend in explainability of black-box models , with emphasis on rule-based and exemplar-driven methods. His work extends to temporal pattern discovery , privacy risk assessment , and software engineering analytics , demonstrating interdisciplinary reach across AI, data science, and human-centric systems. Scientific awards received: IBM Fellowship Award (2014) ISTI Young Researcher Award (2016, 2017, 2018, 2019) Next Generation Data Scientist Award (NGDS 2018) He has contributed to teaching courses such as Data Mining, Logic Programming, and Advanced Data Mining topics. He has been involved in major EU-funded projects including SoBigData++, XAI, AI4EU, and HumanE-AI-Net, where he contributes to advancing explainable and ethical AI. He collaborates extensively within the KDDLab, focusing on knowledge discovery and data-driven decision-making. His lab work emphasizes scalable, interpretable, and socially aware data mining systems.

Pansanella ValentinaView profile

Research Fellow

• Complex Networks
• Network Diffusion Dynamics
• Algorithmic Bias
• +6 more

Valentina Pansanella is a Research Fellow at the National Research Council of Italy (ISTI-CNR), specializing in computational network science and diffusion dynamics. Her work bridges theoretical models with practical applications in social and epidemiological contexts. Her research focuses on complex network analysis , particularly examining algorithmic bias , information diffusion , and homophily measurement in dynamic networks. Key contributions include developing computational frameworks like NDlib and CDLIB for modeling diffusion processes and community detection. Her work frequently employs agent-based simulations and Python-based tooling to analyze contagion patterns in social and biological systems. Analysis of her publication trends reveals consistent focus on network topology effects (2017-2022), evolving from foundational diffusion models to specialized applications in fake news perception (2020) and epidemic modeling (2020). Recent work demonstrates increasing sophistication in path-aware homophily metrics (2021) and topology-aware bias modeling (2022). As part of the KDD Lab research ecosystem, she collaborates extensively with Gianni Rossetti and Letizia Milli on network science tool development. Her technical contributions center on creating open-source libraries that enable reproducible network analysis across academic and applied domains.

• Literary Criticism
• Comparative Literature
• Narratology
• +2 more

Beatrice STASI is a Full Professor of Literary Criticism and Comparative Literature at the University of Salento, affiliated with the Department of Humanities. Her research centers on the poetics of authors like Leopardi, Pirandello, and Svevo, alongside the theory and practice of literary translation. She teaches courses in Literary Criticism, Narratology, Comparative Literature, and Literary Translation across undergraduate and graduate programs, including the Modern Languages and Communication Sciences curricula. Her research explores interdisciplinary connections between myth, archetypes, and literary themes, with a focus on ethical and aesthetic dimensions of narrative. She emphasizes collaborative learning through seminars and group projects, integrating digital pedagogy for thematic analysis and textual interpretation.

• Data Mining
• Process Mining
• Knowledge Representation
• +5 more

Antonella Guzzo is an Assistant Professor (ING-INF/05) at the Faculty of Engineering, University of Calabria, affiliated with the Department of Electronic Informatics and Systems (DEIS). Her research spans Data Mining, Process Mining, Federated Learning, and Knowledge Representation, with applications in Cyber Security and Bioinformatics. Laurea (2000) and Ph.D. (2004) in System Engineering and Computer Science from University of Calabria Her research integrates advanced techniques like graph mining, outlier detection, and AI-driven process discovery. She contributes to projects like TOCAI.it, PROMIS, and OpenKnowTech, focusing on knowledge-oriented technologies and logistics optimization. Recent publications highlight Federated Learning for healthcare, Green AI, and IoT security. She is a member of the IEEE Task Force on Process Mining and serves as a reviewer for journals such as Data and Knowledge Engineering. Antonella collaborates with labs including the Artificial Intelligence and Data Science Laboratory and Cyber Security Laboratory at DIMES.