Find Academic Supervisors

• Social Network Analysis
• Network Science
• Data Science
• +7 more

Giacomo Fiumara is an Associate Professor at the University of Messina, Department of Mathematical and Computer Sciences, Physical Sciences and Earth Sciences. He holds academic rank since October 2021. Previously, he served as a Permanent Researcher (2008–2021) and secondary school teacher (1997–2008). He earned a Doctorate in Physics (1993) and a Degree in Physics (1989), both from the University of Messina. He is an associate member of the Accademia Peloritana dei Pericolanti and qualified as an associate professor in INF/01 and ING-INF/05 sectors. His research focuses on social network analysis, network science, data science, criminal networks, knowledge representation, bioinformatics, and computational modeling. He has supervised over 170 theses and advised PhD students in Mathematics and Computational Sciences. Key collaborations include work with Prof. Pasquale De Meo on criminal networks and complex systems, and international projects with institutions in the US, UK, China, and Australia. Teaching includes courses on Algorithms, Data Structures, Bioinformatics, and Machine Learning across Computer Science, Engineering, and Medical programs since 2000. He also contributed to international programs at Lviv Polytechnic, Birzeit University, Cluj-Napoca, and Murcia. His editorial roles include Associate Editor of IEEE Access and Academic Editor of Complexity. He holds a patent for predictive analysis of criminal organizations' social structures and has received FFABR research funding. Key awards include FFABR funding (2017) and recognition in the FFABR Unime 2020 II edition. He organized conferences like Crimenet 2014 and participated in high-profile events such as the 2022 Complex Networks conference in Palermo, presenting on quantum walks for criminal network analysis.

• Computer Vision
• Deep Learning
• Robotics
• +9 more

Giuseppe Bruno Averta is a Fixed-term Researcher at the Department of Control and Computer Science (DAUIN), Polytechnic University of Turin, and a member of the Interdepartmental Center SmartData@PoliTO - Big Data and Data Science Laboratory. He is affiliated with the College of Computer, Film and Mechatronics Engineering and contributes to national and international research in artificial intelligence and robotics. Averta has held a Visiting Researcher position at the Massachusetts Institute of Technology (MIT) from January to June 2019. His research interests include Computer Vision, Deep Learning, Robotics, Neural Architecture Search, Egocentric Vision, Embodied Intelligence (Edge/Tiny ML), and Human-Robot Collaboration . His work is aligned with ERC sectors in Artificial Intelligence, Machine Learning, and Robotics, and contributes to UN SDGs such as Good Health and Well-being, Industry Innovation and Infrastructure, and Responsible Consumption and Production. The recent publication trends highlight his focus on vision-language models (e.g., CLIP), egocentric action recognition, efficient neural architectures (e.g., BiSeNet, MaskFormer), and robust deep learning. His research bridges theoretical advances with practical robotics applications, including grasping and manipulation. Scientific Awards and Recognitions: Georges Giralt PhD Award (euRobotics AISBL, 2021) Wiley Best Reviewer (Wiley, Italy, 2021) Best Paper Award, ICUMT 2015 (2017) Fellow, ELLIS Network of Excellence (2022–) Fellow, DAAD AInet (2022–) DAAD AInet Fellowship Advising and Grants : Averta supervises multiple PhD students in the Artificial Intelligence and Computer and Systems Engineering doctoral programs at Politecnico di Torino. He is involved in teaching at both the master’s and doctoral levels, including courses on Robot Learning and Machine Learning and Deep Learning. He is also a co-inventor on a national and international patent for a method and algorithm for the automatic design of neural networks through machine learning, indicating active research funding and innovation. Labs and Research Groups : He is a member of the SmartData@PoliTO center and contributes to research in the VANDAL PoliTO lab (as indicated by his student Davide Buoso). His work is deeply integrated with teams working on egocentric vision, embodied AI, and neural architecture search.

• CAD tools
• Digital architectures
• Emerging technologies
• +9 more

Giovanna Turvani is an Associate Professor at the Department of Electronics and Telecommunications (DET) at Politecnico di Torino, with affiliations in both the College of Electronic, Telecommunications and Physics Engineering and the College of Computer, Film, and Mechatronics Engineering. Scientific Branch: IINF-01/A - Electronics ERC Sectors: PE7_4, PE7_11, PE6_1, PE6_14, PE7_3 SDG Goals: Quality Education, Gender Equality, Affordable Energy, Industry Innovation Her research focuses on advanced electronics and quantum technologies, including: Logic-in-memory computing Quantum computing architectures Microwave imaging for medical and agricultural applications CAD tools for emerging nanotechnologies Embedded systems for bee health monitoring IoT solutions for bio-waste valorization Publications show strong expertise in quantum computing, nanocomputing, and microwave imaging, with recent trends emphasizing quantum optimization frameworks, in-memory architectures, and IoT-based agricultural technologies. She supervises PhD students in areas like quantum machine learning algorithms, predictive on-board systems, and quantum hardware design. Collaborations span multiple disciplines, including medical device development and agricultural electronics. Patents include innovations in microwave imaging, racetrack memory logic functions, and in-memory computing devices.

Andrea SantilliView profile

Researcher

• Natural Language Processing
• Representation Learning
• Machine Intelligence
• +10 more

Andrea Santilli is a Research Scientist at Nous Research and holds a PhD in Computer Science from GLADIA at Sapienza University of Rome. His research focuses on large language models (LLMs), robustness, reliability, and multimodal learning. He previously worked at Apple MLR, Hugging Face’s BigScience, and Pi School. He earned his MSc and BSc in Computer Science from Tor Vergata University and Sapienza. Education: PhD in Computer Science, Sapienza University of Rome (2024) MSc in Computer Science, University of Roma Tor Vergata (2020) BSc in Computer Science, University of Roma Tor Vergata (2018) Research Interests: Santilli’s work spans LLM robustness , mechanistic interpretability , multimodal neural databases , and instruction-tuning . He introduced Parallel Jacobi Decoding and contributed to projects like BLOOM, Camoscio, and Fauno. His research bridges syntax-aware NLP, privacy-preserving LLMs, and cross-modal alignment. Publications: His work includes advancements in 3D-text latent space alignment (CVPR 2025), evolutionary merging (ICML 2025), and efficient decoding (ACL 2023). Over 15+ peer-reviewed papers span venues like ACL, CVPR, and ICLR. Awards: Received the Emanuele Pianta Award for his MSc thesis on continual language learning with syntax-based episodic memory. Grants & Projects: Winner of ‘Machine Learning Algorithms for Translation’ grant (2022), developing Parallel Decoding Co-PI for ‘Multimodal AI for 3D Analysis’ (2021) with Ecole Polytechnique Labs & Teams: Active in GLADIA (Sapienza), Apple MLR, and Hugging Face’s BigScience initiative. Core contributor to open-source projects like PromptSource and BLOOM.

• Software Engineering
• Artificial Intelligence
• AI Trustworthiness Assessment (SE4AI)
• +5 more

Gias Uddin is an Associate Professor at York University's Lassonde School of Engineering and an Adjunct Professor at the University of Calgary . His research bridges Software Engineering (SE) and Artificial Intelligence (AI) , focusing on AI Trustworthiness Assessment (SE4AI) and AI-Driven Productivity Tools (AI4SE) . PhD in Software Engineering & AI, McGill University (2018) MSc in Software Engineering, Queen’s University (2008) BSc in Computer Science & Engineering, Bangladesh University of Engineering and Technology (2004) His research explores: Metamorphic Relations for LLM Hallucination Detection AI-Enhanced Software Documentation Foundational Models for Runtime System Modernization Developer-Centric AI Tooling Recent article trends show expertise in LLM Trustworthiness , Low-Code Platforms , and IoT Developer Communities . Awards include Distinguished Paper at FSE 2025 , multiple IBM Champion recognitions, and York Research Award . He leads the Data Intensive Software Analytics (DISA) Lab and mentors PhD students in SE-AI Intersections .

Gabriella CasalinoView profile

Assistant Professor

• Computational Intelligence
• eHealth
• Data Stream Mining
• +5 more

Gabriella Casalino is an Assistant Professor at the University of Bari Aldo Moro, Department of Computer Science, and a key researcher at CILAB - Computational Intelligence Lab. Her work focuses on Computational Intelligence methods for interpretable data analysis, particularly in eHealth, Data Stream Mining, and eXplainable Artificial Intelligence (XAI) within medical and educational domains. She has contributed to innovative approaches in smartphone-based health monitoring, fuzzy logic applications, and remote vital sign detection via photoplethysmography. Education : Ph.D. in Computer Science, with advanced training at institutions like Universitat de Girona and Université de Mons. Research Trends : Recent publications highlight applications of evolving granular computing, neuro-fuzzy systems, and explainable AI in hypertension prediction, bipolar disorder monitoring, and educational data analysis. Key subfields include remote health monitoring, medical data streams, and hybrid AI models. Grants : Research funded by AIRC (Italian Cancer Research Foundation), focusing on computational methods for healthcare challenges. Labs & Collaborations : Active in CILAB, collaborating on projects involving mHealth solutions, cardiovascular risk assessment, and intelligent educational systems.

• Machine Learning
• Data Mining
• Bioinformatics
• +11 more

Andrea Passerini is a Full Professor in the Department of Information Engineering and Computer Science at the University of Trento, Italy, where he also serves as Coordinator of the PhD programme in Information Engineering and Computer Science (Ministerial Decree 45/2013). His academic footprint spans multiple departments including Mathematics, Sociology, Cellular Biology, and Industrial Engineering, reflecting deep interdisciplinary engagement across computational sciences and life sciences. His research centers on Machine Learning and Data Mining with specialized expertise in Neuro-Symbolic AI , Probabilistic Reasoning , and Statistical Relational Learning . He pioneers methods for graph-based learning, medical AI applications, and explainable systems, with significant contributions to bioinformatics (particularly RNA-protein interactions) and healthcare diagnostics. His work bridges theoretical rigor with practical implementations in critical domains. Analysis of his 2025 publications reveals dominant trends in neuro-symbolic integration for graph data, human-AI collaboration in medical decision-making, and robust recommender systems. His research increasingly focuses on interpretable AI for high-stakes applications like surgical planning and physician support, while advancing foundational techniques in graph neural networks and concept-based modeling. As PhD programme Coordinator, Professor Passerini mentors doctoral candidates across AI and computer science disciplines. His collaborative network extends to medical researchers at CIBIO (Cellular, Computational and Integrative Biology department) and industrial partners, though specific lab structures aren't documented in available materials. Current projects emphasize medical AI validation, temporal network modeling, and LLM integration with structured reasoning frameworks.

Diana Gratiela BerbecaruView profile

Associate Professor

• Cybersecurity
• Authentication
• Authorization
• +12 more

Diana Gratiela Berbecaru is an External Collaborator and External Lecturer at the Department of Control and Computer Science (DAUIN), Politecnico di Torino, where she contributes to teaching and research in cybersecurity and digital identity. She is affiliated with the TORSEC Security Group and actively participates in EU-funded research projects such as Q-FENCE, focusing on quantum-resistant cryptography. She teaches core courses including Security and Privacy for Digital Identity Frameworks and Information Systems Security , and has been recognized with the Italian national scientific habilitation as Associate Professor in 2025, affirming her academic standing. Full Name: Diana Gratiela Berbecaru University: Politecnico di Torino Department: Department of Control and Computer Science (DAUIN) Academic Rank: Associate Professor (habilitated) Teaching Status: Part-time External Lecturer Email: diana.berbecaru@polito.it Her research focuses on cybersecurity, identity management, and trusted computing, with specific interests in authentication, authorization, data privacy, network security, and trusted computing in distributed and IoT environments. She investigates practical implementations of digital identity systems using the eIDAS infrastructure, certificate validation, TLS security, and post-quantum cryptography. Her work bridges theoretical security models with real-world deployment challenges. Her recent publications (2022–2025) reflect a strong focus on TLS security, X.509 certificate analysis, anomaly detection using AI, remote attestation for IoT, and post-quantum migration strategies. These works are published in high-impact venues such as IEEE Access, IEEE ISCC, and ARES, indicating active and influential contributions to the cybersecurity research community. The research trend shows a consistent emphasis on practical tools and frameworks for enhancing trust and security in digital systems. Scientific Awards and Recognition: Italian National Scientific Habilitation as Associate Professor (Abilitazione Scientifica Nazionale, II fascia), 2025 She serves as an Associate Editor for IEEE Transactions on Network and Service Management and IEEE Access , and as a Guest Editor for Electronics and Computer Networks . She chairs and co-chairs international workshops such as TrustAICyberSec and IMTrustSec, and is a frequent member of program committees for major conferences including ARES, IDC, and ISCC. These roles demonstrate her active engagement in academic leadership and knowledge dissemination. Labs and Research Groups: TORSEC - Security Group (DAUIN): Core research group focusing on cybersecurity, trusted systems, and digital identity.

• Artificial intelligence
• Biomedical signal processing
• Human movement analysis
• +12 more

Marco Ghislieri is an Assistant Professor at the Department of Electronics and Telecommunications (DET) of Politecnico di Torino, Italy. He is a member of the Interdepartmental Center PolitoBIOMed Lab and teaches in the Biomedical Engineering program, including courses like Neuroengineering and Design of Programmable Biomedical Devices . His research spans Artificial Intelligence, Biomedical Signal Processing, Neuroscience, and Rehabilitation Engineering . PhD in Bioengineering and Medical-Surgical Sciences (2017-2021) at Politecnico di Torino Thesis: Muscle Synergy Assessment during Cyclic and Non-Cyclic Movements His research focuses on muscle synergy analysis in Parkinson’s Disease (PD) patients post- Deep Brain Stimulation (DBS) , AI-driven gait analysis for fall prevention, and wearable sensor applications for stress-cognitive decline monitoring. He leads the S-CoDe and OMNIA-PARK projects, and contributes to PRIN as a team member. Recent publications highlight advancements in machine learning for intraoperative DBS targeting , statistical gait analysis , and neurorehabilitation tools . He serves as Associate Editor for Scientific Reports and Applied Bionics and Biomechanics , and Guest Editor for Frontiers in Neural Circuits . Awards include the Carlo J. De Luca Award (2022) , GNB Doctoral Award (2022) , and the Best Poster Award at M. Grattarola Summer School (2022) . He supervises Fabrizio Sciscenti (PhD candidate) and collaborates on neuroengineering and biomedical device design courses. His work addresses Goal 3 (Good Health) and Goal 4 (Quality Education) of the UN SDGs.

Anh Nguyen Nguyen DucView profile

Professor

• Software Startup
• Software Processes and Practices
• Software Engineering Education
• +6 more

Dr. Anh Nguyen Nguyen Duc serves as Full Professor at the University of South-Eastern Norway and the Norwegian University of Science and Technology (NTNU), with visiting scholar positions across Norwegian, Finnish, Italian, and Vietnamese institutions. His academic work centers on software engineering with emphasis on human, process, and ecosystem dimensions of development. Education: MS: Technical University of Kaiserslautern and Blekinge Institute of Technology (double degree) PhD: Norwegian University of Science and Technology Research fingerprint analysis reveals dominant focus on software startups (27%), supplemented by software processes (6%) and engineering education (5%). His expertise spans cybersecurity, global software development, business-driven methodologies, and software analytics, consistently addressing human-organizational challenges in dynamic development environments. Recent publications (2024-2025) demonstrate accelerating integration of AI in software engineering, particularly through large language models for startup assistance, generative AI adoption frameworks, and autonomous agent systems. Concurrently, he investigates risk management in software ventures and fairness in educational ML applications, reflecting interdisciplinary work bridging software engineering with business, AI ethics, and educational technology.

Rocco OLIVETOView profile

Professor

• Software Engineering
• Artificial Intelligence
• Machine Learning
• +7 more

Prof. Rocco OLIVETO is a Full Professor at the University of Molise, affiliated with the School of Biosciences and Territory. His research spans software engineering, artificial intelligence, cybersecurity, and healthcare technology. He focuses on empirical studies of developer practices, AI-driven code analysis, vulnerability detection in smart contracts, and human-centric computing. His work also addresses challenges in game development, mobile app optimization, and wearable health monitoring systems. Notable research areas include code readability assessment, machine learning applications in healthcare diagnostics, and the effectiveness of AI tools like GitHub Copilot. He has contributed to projects like QualAI (continuous quality improvement for AI systems) and 2Vita-B (cognitive and physical rehabilitation systems). His empirical studies often bridge academic research with real-world developer workflows, emphasizing practical applicability. Prof. Oliveto's recent work explores topics such as automated gameplay analysis for game debugging, detection of engagement issues in video games, and robust methods for identifying security vulnerabilities. He has also investigated Dockerfile quality, developer frustration metrics, and the ethical implications of AI in administrative document simplification.

Silvia BonomiView profile

Associate Professor

• Cybersecurity
• Distributed Systems
• Blockchain
• +8 more

Dr. Silvia Bonomi serves as an Associate Professor in the Department of Computer, Control and Management Engineering at Sapienza University of Rome, where she has held academic positions since 2006. Her career progression includes Research Fellow (2010-2011), Tenure Track Assistant Professor (2016-2019), and current Associate Professor appointment since 2019. She maintains her office in Room B114 and is actively engaged in research and teaching within the university's engineering faculty. Her educational background includes: PhD in Computer Engineering, Sapienza University of Rome and Institut de Formation Supérieure en Informatique et Communication (IFSIC/IRISA), Rennes, France (completed under advisors Prof. Roberto Baldoni and Prof. Michel Raynal) Dr. Bonomi's research critically examines dynamic distributed systems where entities autonomously join and leave networks, with applications spanning VANETs, airborne networks, social networks, and distributed cloud services. She pioneers work in Byzantine fault tolerance for mobile environments, blockchain security with emphasis on smart contract vulnerability analysis, and resilient cybersecurity frameworks integrating human factors. Her investigations into publish-subscribe systems focus on quality-of-service enhancements, while her peer-to-peer systems research addresses fundamental connectivity challenges in large-scale decentralized environments. This interdisciplinary approach bridges theoretical distributed computing with practical cybersecurity applications. Analysis of her 15 most recent publications (2021-2024) reveals dominant trends in blockchain security (particularly smart contract vulnerability taxonomies and analysis tool efficacy) and fault-tolerant distributed systems (reliable communication under Byzantine faults in dynamic networks). Her work increasingly integrates human factors into cybersecurity models and develops visual analytics for business-centric risk assessment. Publications span top venues including IEEE CSR, OPODIS, SAFECOMP, and journals like Computers & Security, demonstrating consistent contributions to both theoretical foundations and practical cybersecurity implementations.

Marco PiconeView profile

Associate Professor

• Distributed Systems
• Internet of Things
• Edge Computing
• +3 more

Marco Picone is an Associate Professor at the Department of Sciences and Methods for Engineering (DISMI) of the University of Modena and Reggio Emilia. He leads the Distributed and Pervasive Intelligence (DIPI) Group and holds a PhD in Information Technology from the University of Parma. His postdoctoral research at the University of Parma (2012-2015) and a visiting scholar position at the University of Cambridge (2011) further enriched his expertise. He is nationally qualified as an Associate Professor by MIUR (2020). Education: PhD in Information Technology, University of Parma (Italy) M.Sc. (cum Laude) in Computer Engineering, University of Parma Visiting Researcher, NetOS Group, University of Cambridge (UK) His research focuses on Distributed Systems , IoT , Edge Computing , and Digital Twins , emphasizing their applications in smart industries and cities. He has supervised postdocs (e.g., Matteo Martinelli) and PhD students (e.g., Enrico Rossini) on topics like Digital Twin Continuum and Edge-Cloud Systems. Teaching spans courses on Intelligent IoT , Distributed IoT Software Architectures , and Edge Computing , with a focus on lab-based learning and industry-relevant projects. He actively contributes to open-source frameworks like the White Label Digital Twin (WLDT) and collaborates on initiatives such as the Web of Digital Twins (WoDT). Research collaborations include projects on smart city data fusion, livestock waste management, and Industry 5.0 human-centric systems. His work bridges theoretical advancements with practical implementations in cyber-physical environments.

Alexander KocianView profile

Assistant Professor

• Machine Learning
• Internet-of-Things (IoT)
• Agro Informatics
• +3 more

Alexander Kocian is an Assistant Professor at the Department of Computer Science, University of Pisa. He holds a Ph.D. in Electrical and Electronic Engineering from Aalborg University (Denmark) and a Master's in Electrical Engineering from TU Vienna (Austria). His research focuses on Machine Learning, IoT, Agro Informatics, Health Informatics, and Real-time embedded systems. He has led major projects like AGRITECH (€40M funded by PNRR) and FuorisuoloSmart, advancing smart agriculture and healthcare technologies. Dr. Kocian serves as IEEE Senior Member (since 2024) and EAI Fellow (since 2022). He is Associate Editor of IEEE Access (2025–present), and Editorial Board member of Stats (2019–present) and Signals (2020–present). He has organized conferences like the EAI Int. Conf. on Intelligent Transport Systems (INTSYS) as General Chair (2024) and Steering Committee Member (2023). His work includes 50+ peer-reviewed publications, 4 patents, and contributions to telemedicine platforms like TESHEALTH (ESA-funded). Key projects span precision farming, IoT-based greenhouses, and AI-driven healthcare solutions. Current efforts emphasize data spaces for agritech and health informatics interoperability.

Andrea MaurinoView profile

Professor

• Data Science
• Knowledge Graphs
• Machine Learning
• +5 more

Andrea Maurino is a Full Professor at the University of Milano-Bicocca and leads the Insid&s LAB. His research focuses on data quality, knowledge graphs, machine learning, and their applications in healthcare, finance, urban planning, and organizational analysis. He explores cutting-edge techniques like Large Language Models (LLMs) for decision support systems and semantic annotation of tabular data. Key research interests include improving data quality frameworks for large RDF datasets, developing enterprise knowledge graphs for organizational insights, and applying AI to social media analysis and hate speech detection. His work bridges theoretical advancements with real-world applications such as smart city mobility prediction and nutritional strategies for healthy aging. Notable contributions include scalable tools like ABSTAT-HD for knowledge graph profiling and the 3d-clost mobility prediction model. Maurino’s interdisciplinary approach integrates data science with fields like psychology (ICD-11 decision support) and environmental science (ESG activity detection in financial texts). His lab collaborates on projects like Food NET, combining nutrition science with social network analysis. While no formal awards are listed here, his prolific publication record reflects sustained innovation in data-driven methodologies.