Find Academic Supervisors

• Information Visualization
• Visual Analytics
• Human-Computer Interaction
• +8 more

Paolo Buono is Associate Professor at the Department of Computer Science, University of Bari Aldo Moro, Italy. He holds a PhD in Computer Science with specialization in Visual Data Analysis. His research focuses on Information Visualization, Visual Analytics, Human-Computer Interaction, and Mobile Applications. Co-founder and CEO of LARE (2010), a university spinoff providing real-time surgical support through audio-video telestration Member (since 2002) and computer science coordinator at METEA Research Center for environmental protection Visiting scientist at AVIZ (France), University of Maryland (USA), and Fraunhofer IPSI (Germany) His work spans multiple application domains including: Cultural Heritage through interactive exploration systems Healthcare with smart therapeutic devices Environmental Monitoring via CET system IoT-based Smart Interactive Experiences He has contributed to: Dynamic hypergraph visualization techniques End-User Development frameworks (EUDroid) Usability evaluation methodologies Mobile health applications As project leader, he has coordinated: EU-funded VisMaster Coordination Action (2008-2010) Italian Ministry-funded LOGIN project (2014-2015) Apulia Region environmental projects His professional engagements include: Co-chair roles at INTERACT, AVI, IS-EUD conferences Program committee participation in VIS series and HCI conferences Member of ACM, IEEE, and SIGCHI Italy

Fosca GiannottiView profile

Professor

• Mobility Data Mining
• Social Network Analysis
• Privacy-Preserving Data Mining
• +6 more

Fosca Giannotti is a Full Professor at Scuola Normale Superiore in Pisa, Italy, and leads the Pisa KDD Lab - Knowledge Discovery and Data Mining Laboratory, a joint research initiative of the University of Pisa and ISTI-CNR. Founded in 1994, the Pisa KDD Lab is one of the earliest research labs focused on data mining. Giannotti is a pioneering scientist in mobility data mining, social network analysis, and privacy-preserving data mining. Her educational background includes a Master Degree in Computer Science from the University of Pisa (1982) with 110/100 cum laude. She has held numerous visiting positions including at MCC in Austin, CWI Amsterdam, UCLA, and the Barabasi Lab at Northeastern University. Giannotti's research focuses on social mining from big data, encompassing smart cities, human dynamics, social and economic networks, ethics and trust, and diffusion of innovations. She has authored more than 300 papers and coordinated tens of European projects and industrial collaborations. Her current work increasingly centers on Explainable AI (XAI), as evidenced by her prestigious ERC Advanced Grant for the XAI project focused on "Science and technology for the explanation of AI decision making." Her recent publications reveal a strong emphasis on trustworthy AI, with research spanning privacy-preserving techniques, fairness in machine learning, human-AI collaboration frameworks, and medical applications of explainable AI. The breadth of her work demonstrates how data mining principles are being applied across diverse domains from social sciences to healthcare. ERC Advanced Grant for XAI project Premio Internazionale Tecnovisionarie 2021 Intelligenza Artificiale Giannotti has coordinated numerous significant projects including SoBigData (the European research infrastructure on Big Data Analytics and Social Mining), XAI, TAILOR (Foundations of Trustworthy AI), HumanE-AI-Net, and AI4EU. As former coordinator of SoBigData, she led an ecosystem of ten cutting-edge European research centers providing an open platform for interdisciplinary data science. She leads the Pisa KDD Lab, which serves as a hub for research on knowledge discovery and data mining. The lab has been instrumental in developing techniques for mobility data analysis, social network mining, and privacy-preserving data analytics, with applications ranging from smart cities to pandemic response.

• Computer Science
• Cybersecurity
• Network Security
• +4 more

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

• Computer Science
• Artificial Intelligence
• Reinforcement Learning
• +6 more

Eric Eaton is a prominent researcher in Computer Science, specializing in Artificial Intelligence, Reinforcement Learning, and Federated Learning. His work bridges theoretical advancements with practical applications in healthcare, robotics, and educational technology, as evidenced by his collaborations with institutions like the Vector Institute and co-authors such as Marcel Hussing and Amir-massoud Farahmand. Research Focus: Lifelong Learning, Object-Centric Representation, and Algorithmic Fairness Key Contributions: ELLA algorithm, Distributed Continual Learning frameworks, and AI integration in surgical video analysis His recent publications address critical challenges in high update ratio reinforcement learning, federated learning for surgical data, and ethical considerations in algorithmic fairness. These works highlight his interdisciplinary approach, combining AI with healthcare and education. Eaton's leadership in projects like FORLA and Slot-BERT demonstrates innovation in unsupervised learning and temporal coherence. His involvement in the CS2023 curriculum design underscores his commitment to advancing computer science education.

Giampaolo LiuzziView profile

Associate Professor

• Nonlinear Optimization
• Global Optimization
• Mixed Integer Nonlinear Programming
• +3 more

Giampaolo Liuzzi is an Associate Professor at the Department of Computer, Automation, and Management Engineering 'Antonio Ruberti' (DIAG) at Sapienza University of Rome since July 2023. Previously, he was a fixed-term researcher at the same department (July 2020-June 2023) and a Senior Researcher at the Institute of Systems Analysis and Computer Science 'A. Ruberti' of the CNR until July 2020. He teaches Mathematical Programming, Complements of Mathematics, and Mathematical Analysis 2 for various engineering programs at Sapienza University. Dr. Liuzzi's research focuses on Nonlinear Optimization , particularly derivative-free methods for constrained and unconstrained optimization, global optimization, mixed integer nonlinear programming, and applications in operations research and machine learning. His work spans theoretical developments in optimization algorithms as well as practical applications in engineering design, simulation-based optimization, and biomedical systems. He has made significant contributions to derivative-free optimization techniques that don't require gradient information, which is particularly valuable for black-box optimization problems where derivatives are unavailable or expensive to compute. His recent publications (2022-2025) demonstrate a strong focus on advancing derivative-free optimization methods, with particular attention to complexity analysis, convergence properties, and practical implementations for challenging problem classes including nonsmooth, constrained, multi-objective, and mixed-integer optimization problems. His work bridges theoretical computer science with practical engineering applications, with publications appearing in top optimization journals like Optimization Methods & Software, Computational Optimization and Applications, and Journal of Optimization Theory and Applications. Dr. Liuzzi has received significant professional recognition through National Scientific Habilitations for both Associate Professor (2014) and Full Professor (2018) positions in Italy. He is actively involved in the academic community as an administrator of the Derivative-Free Library (DFL), a collection of algorithms and methods for derivative-free optimization developed through collaboration among several prestigious Italian research institutions. As an educator, Dr. Liuzzi has developed comprehensive teaching materials for courses in Mathematical Programming, Complements of Mathematics, and Mathematical Analysis. He is also engaged in academic entrepreneurship as a co-founder of DEIX s.r.l., a Sapienza startup focused on algorithms and industrial software for planning and control of complex systems. Additionally, he organized the 2nd Derivative-Free Optimization Symposium (DFOS'24) in June 2024 in Padua, highlighting his leadership role in this specialized optimization community.

• Wireless Networks
• Internet of Things (IoT)
• Network Protocols
• +9 more

Fabrizio Giuliano is a Researcher at the University of Palermo in the School of Mathematics and Computer Science , focusing on Wireless Networks , Internet of Things (IoT) , and Network Protocols . His academic activities include teaching courses like Computer Networks , Internet of Things , and IoT and Cloud Security to students in Informatics, Biomedical Engineering, and Cyber-Physical Systems programs. Research Interests : Giuliano's work spans Wireless communication (LoRaWAN, Sigfox, WiFi, ZigBee) Smart water distribution systems and energy-autonomous IoT Interference detection and cross-technology coexistence 5G network infrastructure Augmented Reality for accessibility Privacy-preserving smart grid systems Publication Trends : His recent articles (2025–2023) focus on AI integration in IoT testbeds Scalable water distribution monitoring Information-theoretic analysis of fNIRS signals Interference mitigation in LPWANs Context-aware 5G architectures Hybrid VLC/WiFi networks Academic Contributions : Giuliano has edited theses on fNIRS signal analysis and IoT-integrated biosensors , reflecting his interest in biomedical applications of wireless systems.

Massimo Orazio SpataView profile

Research Fellow

• Deep Learning
• Biomedical Engineering
• Computer Science
• +3 more

Massimo Orazio Spata is a Research Fellow in Computer Science at the University of Catania's Department of Mathematics and Computer Sciences, specializing in deep learning applications for biomedical, audio, and biometric systems. He has held roles at STMicroelectronics since 1999, focusing on system integration, image processing, and biomedical device R&D. He teaches courses such as Mobile Programming and Computer Architecture at secondary schools and has advised numerous students on grid computing and middleware projects. Education: PhD in Computer Science (University of Catania, 2008), MSc in Computer Science (University of Catania, 2013), and a teaching certification in Computer Science (University of Catania, 1998). Research interests include deep learning algorithms, biomedical device development, grid scheduling, and cybersecurity. He has authored patents on lab-on-chip systems, bio-computer analysis, and scheduling methods, and his work has been recognized with STMicroelectronics Innovation Awards (2016–2014) and a Cisco CCNA certification. Key collaborations include projects with Google (Mediapipe Objectron for robotics), Huawei (video deblurring), and involvement in the PNRR Horizon HiCONNECTS project (2024–present). He serves on conference committees (e.g., ICAETA 2023) and has developed e-learning systems and CAD tools for STMicroelectronics.

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +9 more

Carlo Masone is a Fixed-term Researcher at the Department of Control and Computer Science (DAUIN), Politecnico di Torino, affiliated with the College of Electronic, Telecommunications, and Physics Engineering. He is also an invited member of the College of Management and Production Engineering and the College of Mathematical Engineering, reflecting his interdisciplinary contributions. His research focuses on artificial intelligence, machine learning, computer vision, and robotics, with significant work in visual place recognition, federated learning, and geospatial AI. His research interests span Artificial Intelligence , Machine Learning , Computer Vision , Robotics , Visual Place Recognition , Federated Learning , Open-Set Segmentation , and Geospatial AI . He has developed methods for uncertainty quantification in ML models for autonomous vehicles and contributed to digital heritage through the MAPP project. The recent publications highlight a strong trend in visual place recognition (e.g., EigenPlaces, MeshVPR), geolocalization of astronaut photography (Earthloc, EarthMatch), and robust segmentation (Mask2Anomaly). There is a clear emphasis on leveraging pre-trained features, federated learning for privacy-preserving recognition, and topological methods in vision. His work bridges robotics, AI, and real-world applications in autonomous systems and cultural heritage. Scientific Awards: Outstanding Reviewer at CVPR (2022, 2023, 2024) IROS JTCF Novel Technology Paper Award (2016) Best Paper Award Finalist at IEEE ICIA (2016) ELLIS Fellow (2024–) He advises PhD students in Artificial Intelligence and Computer and Systems Engineering and leads commercial research projects such as Quantifying Uncertainties in ML Models for Driver-Assisted and Autonomous Vehicles and MAPP - Phygital and Participatory Alpine Museums . He has previously collaborated with the Max Planck Institute for Biological Cybernetics (2014–2017). He teaches courses including Machine Learning for Mathematical Engineering , Robot Learning , and GeoAI , and contributes to programming and data science curricula. He is also a co-inventor on a patent for automated neural network design.

Alessandro LuiginiView profile

Associate Professor

• Graphic and Visual Sciences
• Art and Heritage Education
• Digitization of Cultural Heritage
• +3 more

Alessandro Luigini is an Associate Professor at the Department of Educational Sciences, Faculty of Educational Sciences, Free University of Bozen-Bolzano. His academic roles include serving as Principal Investigator for projects such as VAR.HEE (2018-21) and TTC (2023-2025), and chairing international conferences like IMG2017 and EARTH2018. He founded EARTH_LAB, focusing on digital environments for education, art, and heritage. His research interests span graphic and visual sciences, digital heritage, and immersive serious games for education. He has authored over 130 publications and serves on editorial boards and committees, including the ICCD Administrative Committee and UID board. Education: PhD in Representation and Surveying of Architecture and the Environment from University 'G. d'Annunzio.' Grants: Principal Investigator for projects funded by competitive calls (VAR.HEE, B_DIGITAL, Digital_FEED, TTC). Labs/Teams: EARTH_LAB, leading interdisciplinary research in digital heritage education.

• Computer Networks
• Edge Computing
• Internet of Things (IoT)
• +5 more

Paolo Bellavista is a Full Professor of Distributed and Mobile Systems at the Department of Computer Science - Science and Engineering, Alma Mater Studiorum – University of Bologna. His research focuses on edge computing, federated learning, IoT, digital twins, and blockchain applications. With over 140 journal articles and 200+ conference papers, his work appears in top venues such as ACM Computing Surveys and IEEE Transactions. He serves as Editor-in-Chief of the MDPI Computers Journal and holds editorial roles in IEEE Communications Surveys&Tutorials and ACM Computing Surveys. His contributions span network optimization, cybersecurity, and smart cities, with notable achievements in citation metrics (h-index 46 on Google Scholar). Research interests include distributed systems, vehicular networks, AI-driven security, and QoS-aware edge infrastructures. He has organized major conferences like IEEE Mobile Cloud and ACM ICDCN. Current projects explore federated learning unlearning, digital twin entanglement, and blockchain-based data spaces. His work bridges theoretical foundations with real-world deployments in smart manufacturing and healthcare. Editorial Roles : MDPI Computers (Editor-in-Chief), IEEE Communications Surveys&Tutorials (Associate Editor), ACM Computing Surveys (Editor) Conference Leadership : Technical Program Chair for IEEE Mobile Cloud 2015, General Co-Chair for SCNS 2018 Key Contributions : Over 140 journal papers, 15 special issues as guest editor, and 200+ conference publications His lab develops middleware for edge-cloud continuum applications and collaborates internationally on projects like InAbled Cities. Office hours are held weekly at the University of Bologna’s DISI department.

Massimiliano Lo TurcoView profile

Professor

• 3D modeling
• Reconstructive modeling
• Augmented Reality (AR)
• +9 more

Massimiliano Lo Turco is a Full Professor at the Department of Architecture and Design (DAD) of the Polytechnic University of Turin. Specializing in digital modeling and cultural heritage, he actively contributes to the fields of Building Information Modeling (BIM), Heritage BIM (HBIM), and 3D reconstruction. University: Polytechnic University of Turin Department: Department of Architecture and Design (DAD) Academic Rank: Professor Research interests include: 3D modeling, reconstructive modeling, augmented/virtual reality, descriptive geometry, architectural representation history, digital cultural heritage, and parametric design. His work often bridges computational tools with heritage conservation. Recent publications demonstrate expertise in: HBIM for Baroque facades, digital preservation of Balinese architecture, parametric design education, and AI-BIM integration. These works align with his broader focus on digital strategies for heritage and sustainable architecture. Scientific awards: Effective member of Italian Union for Drawing (2015-) Associate Editor of Dn - Building Information Modeling, Data & Semantics (2018-) Grants and collaborations: Scientific Director for PhD scholarships in architectural heritage, Contract Manager for agreements with ASL Vercelli, Principal Investigator for research with CNR, and leader of multiple commercial and non-commercial projects with institutions like Museo Egizio and LINKS Foundation.

Andrea SgambelluriView profile

Assistant Professor

• Software Defined Networking (SDN)
• Optical Networks
• Network Reliability
• +6 more

Andrea Sgambelluri is an Assistant Professor at the TeCIP Institute of Scuola Superiore Sant'Anna in Pisa, Italy. He holds a Master's degree in Telecommunications Engineering (2007) and a Ph.D. (2015) from the University of Pisa, where he received the 2015 OFC Corning Outstanding Student Paper Competition Grand Prize. His research focuses on Software Defined Networking (SDN) for optical networks, network reliability, and AI applications in telecommunications. Education: M.Sc. and Ph.D. in Telecommunications Engineering (University of Pisa) Current Role: Assistant Professor (RTDB), TeCIP Institute, Scuola Superiore Sant'Anna Previous Role: Postdoctoral Researcher at KTH Royal Institute of Technology (2016) Research interests span SDN protocol extensions, YANG/NETCONF solutions, network telemetry, and Machine Learning techniques for optical network management. Recent publications highlight innovations in free space optics, failure forecasting, and edge orchestration frameworks. Key scientific contributions include experimental evaluations of OTN transceivers, augmented reality latency monitoring, and open-source optical software development. His work integrates AI with network function virtualization (NFV) and real-time monitoring systems. Scientific Award: 2015 OFC Corning Outstanding Student Paper Competition Grand Prize Andrea participates in European research projects on next-generation optical networks and cloud-based orchestration, bridging satellite communication and terrestrial network technologies.

Tommaso ProiettiView profile

Assistant Professor

• Soft Robotics
• Wearable Robotics
• Rehabilitation Robotics
• +3 more

Tommaso Proietti serves as Tenure-Track Assistant Professor at Sant'Anna School of Advanced Studies, leading the Soft NeuroBionics Lab within the Bioelectronics and Bioengineering Area of the Biorobotics Institute. His career spans industrial engineering at General Motors, postdoctoral research at Harvard Biodesign Lab, and prior affiliations with Northwestern University and Sorbonne University. His academic credentials include: B.S. in Control Engineering, Sapienza University of Rome (2010) M.S. in Control Engineering, Sapienza University of Rome (2013) Ph.D. in Robotics Engineering, Sorbonne University (2017) Proietti's research pioneers soft wearable robotics for rehabilitation and human augmentation, with core expertise in physical human-robot interaction , biomechanics , and adaptive control systems . His lab develops inflatable exosuits and sensor technologies targeting upper-limb mobility restoration for stroke survivors, spinal cord injury patients, and industrial workers. Recent work emphasizes clinical validation of wearable systems in real-world environments while optimizing comfort and natural movement. Analysis of his 15 most recent publications (2022-2025) reveals three dominant research trajectories: (1) clinical assessment tools using wearable sensors for neurological rehabilitation, (2) pneumatic soft exosuits for industrial and medical applications, and (3) fundamental advances in human-robot interaction frameworks. His work increasingly bridges engineering innovation with tele-rehabilitation implementation, particularly for stroke recovery and ALS management. Scientific recognition: No awards documented in source materials Academic contributions: No student advising information provided No research grant details disclosed The Soft NeuroBionics Lab under Proietti's direction focuses on creating ultralightweight, textile-integrated robotic systems that provide targeted assistance without restricting natural movement. Current projects include shoulder exosuits for industrial fatigue reduction and pronosupination aids for spinal cord injury, with strong industry-clinical partnerships driving real-world deployment.

• Wireless Systems and Networks
• Internet of Things (IoT)
• Digital Twin
• +9 more

Luciano Bononi is a Full Professor and Deputy Head of the Department of Computer Science and Engineering at the University of Bologna. He holds a PhD in Computer Science (2002) and has been active in academia since 2001, progressing through roles like Researcher, Senior Researcher, Associate Professor (2011), and Full Professor (2020). His research focuses on Wireless Systems, IoT, Digital Twins, Smart Cities, and Mobile Applications , with over 160 peer-reviewed publications and major contributions to EU projects like Arrowhead and IoE. Education: MS (Laurea) in Computer Science, University of Bologna (1997, Summa cum Laude) PhD in Computer Science, University of Bologna (2002) Research Interests: Bononi's work spans Wireless Protocols, IoT Platforms, Digital Twin Integration with AI, Smart Mobility/ Energy Systems, and Edge Computing . He leads the WiLMA Lab and the ALMA-AI CoInnovation Lab , focusing on real-world IoT deployments and smart city solutions. Key Contributions: Coordinated EU projects like Arrowhead (2013-2017) and national initiatives like PNRR-Mobility-Spoke 7 Recipient of 4 Best Paper Awards and top rankings in global scientist databases Editorial roles at 7 journals including Wiley's Wireless Communications and Elsevier's Ad Hoc Networks Organized over 15 international conferences as Chair and participated in 200+ TPC roles Labs & Teams: Directs the WiLMA Lab (Wireless Systems and Mobile Apps) and the ALMA-AI CoInnovation Lab , emphasizing interdisciplinary collaboration between academia and industry.

Alberto GrecoView profile

Research Fellow

• Bioengineering
• Robotics
• Biomedical Signal Processing
• +7 more

Alberto Greco, Ph.D., is a Research Fellow in Bioengineering at the Department of Information Engineering, Faculty of Engineering, University of Pisa, Italy. He obtained his Laurea (2010) and Ph.D. (2015) in Biomedical Engineering and Automatics/Bioengineering from the University of Pisa, with a Visiting Fellowship at the University of Essex (2014). His work integrates biomedical signal processing , machine learning , and physiological modeling with applications in wearable monitoring systems and eye-tracking . Education Biomedical Engineering, University of Pisa (2010) Ph.D. in Automatics, Robotics, and Bioengineering, University of Pisa (2015) Visiting Fellow, University of Essex, UK (2014) His research focuses on autonomic nervous system assessment , central nervous system modeling , and affective computing , particularly through projects like cvxEDA —a convex optimization framework for electrodermal activity processing. He contributes to European research projects and develops smart wearable platforms for physiological data collection. Key application areas include consciousness disorders , mood assessment , and human-robot interaction . His technical expertise spans Bayesian statistics , sparsity-based signal modeling , and multimodal physiological analysis . He is affiliated with the Neuro-Cardiovascular Intelligence Lab and contributes to the TOLIFE project, ComEDA stress assessment tool, and ThermICA thermal response analysis system. His work bridges bioengineering , robotics , and social-emotional interaction domains.