Dr. Gianluca Demartini is a leading researcher in Human-in-the-loop AI Systems with significant contributions to Crowdsourcing , Information Retrieval , and Generative AI applications. His work bridges Machine Learning and Human-Computer Interaction , focusing on Bias Management , Fact-Checking , and Ethical AI . Major Affiliations : L3S Research Center, ScienceWISE platform, and collaborations with institutions like University of Queensland and University of Padua Over 15 years, his research has explored Crowdsourcing Quality Control (Mechanical Cheat 2012), Entity Ranking (2008-2013), and Semantic Search . Recent work (2024-2026) focuses on Generative AI Impacts in domains like Media Literacy , Data Curation , and Visual Analytics . Scientific Recognition : Best Paper Award (Top 1.4%) at ICTIR 2023 Best Short Paper Award (Top 0.6%) at ECIR 2020 Honorable Mention (Top 2%) at CSCW 2020 Best Demo Award at ISWC 2011 3rd Best Paper at LA-WEB 2008 His 15 most recent publications (2024-2026) demonstrate expertise in LLM-based Content Moderation , Immersive Data Visualization , and Trustworthy AI Systems . He has pioneered methods for Bias Detection in Wikipedia (2013), Entity Ranking (2008-2013), and Human-AI Collaboration frameworks. His work consistently addresses ethical challenges in AI for Social Good and Responsible Data Science .
Leonardo Becchetti is a Full Professor at the University of Rome Tor Vergata's Department of Economics and Finance, teaching Microeconomics and Topics in Applied Economics for the 2025-2026 academic year. Based in room P2 S55, he maintains an active research profile with email contact becchetti@economia.uniroma2.it. His research centers on Corporate Finance, Corporate Social Responsibility, and Happiness Economics, extending to Sustainable Development and Ecological Transition. He investigates how economic structures influence well-being through relational goods, generativity, and sustainability frameworks, employing game-theoretic and empirical methodologies to analyze climate action, AI impacts, and cooperative behavior. Analysis of his 2024-2025 publications reveals intensifying focus on ecological transition mechanisms, including renewable energy communities, circular economy governance, and sustainable investment models. His work increasingly integrates climate economics with behavioral insights, examining conditional cooperation in environmental actions and AI's disruption of labor markets. No scientific awards or student advising information is publicly documented. He participates in departmental research initiatives including DEF Seminars and ROBO Seminars, contributing to the university's research centers on economic and social impact.
Fernando Corinto is a Research Fellow at the Department of Electronics and Telecommunications (DET) , Polytechnic University of Turin , and a member of the SmartData@PoliTO Big Data and Data Science Laboratory. He holds a European Doctorate in Electronics and Communications Engineering (2005) and was a Marie Curie Fellow (2004) at University College Dublin, focusing on cardiac fibrillation modeling and chaotic systems. Education : Laurea (2001) and Ph.D. (2005) in Electronics and Communications Engineering from Politecnico di Torino His research spans nonlinear dynamical systems , memristor devices , and complex network modeling , with over 50 publications. Key projects include RECOMMEND (2024–2027) and COSMO (2020–2024), where he served as Scientific Director . His recent work involves memristor-based neuromorphic systems and nonlinear circuit applications in biomedical and industrial contexts. He supervises PhD students Rosanna Cavazzana and Davide Rossetti and teaches Nonlinear Systems for Engineering (Mathematical Engineering) and Memristor-based Neuromorphic Systems (Electrical Engineering). His scientific contributions include the Flux-Charge Analysis Method and Bifurcations without Parameters in memristor circuits. He holds a national/international patent for skin ulcer classification algorithms and has led commercial research projects in biomedical and packaging systems.
Laura Sanità is an Associate Professor in the Department of Computing Sciences at Bocconi University, Milano, Italy. She previously held academic positions at TU Eindhoven (Netherlands) and the University of Waterloo (Canada). Education: Bachelor's in Management Engineering (2003), Università di Roma Tor Vergata Master's in Management Engineering (2005), Università di Roma Tor Vergata PhD in Operations Research (2009), Università Sapienza di Roma Postdoctoral Fellow at EPFL (Switzerland, 2009-2011) Laura's research focuses on discrete mathematics, theoretical computer science, and operations research, with particular emphasis on algorithmic solutions for combinatorial optimization problems. Her work spans approximation algorithms, network design, polyhedral combinatorics, and algorithmic game theory, advancing methodologies for solving complex optimization challenges in theoretical and applied contexts. Her publications demonstrate expertise in network design problems, spanning from fundamental polyhedral characterizations to game-theoretic applications. Key contributions include iterative randomized rounding techniques for Steiner trees, circuit augmentation algorithms, and stabilization approaches for network games. Scientific Awards: NWO-VIDI Award (Netherlands) Discovery Accelerator Supplements Award (NSERC, Canada) Golden Jubilee Research Excellence Award (University of Waterloo) Early Researcher Award (Ontario) Best Paper Award at STOC 2010 Advising & Collaborations: Laura advises PhD students Dylan Hyatt-Denesik and Lucy Verbeck, and collaborates with postdoctoral researchers like Afrouz Jabal Ameli. She has served on program committees and as Associate Editor for top journals including Mathematical Programming, Mathematics of Operations Research, and Operations Research Letters.
Simon Masnou is a Full Professor at Université Claude Bernard Lyon 1, affiliated with the Institut Camille Jordan (CNRS UMR 5208). He holds leadership roles as Head of the 'Applied Mathematics, Statistics' Master's degree and Head of the 'M2 Maths in Action' program. Previously, he served as Director of the Camille Jordan Institute (2018-2022). His research focuses on applied mathematics, image processing, shape optimization, and geometric measure theory, with contributions to variational models, geometric flows, and applications in computer vision and materials science. Education: PhD in Mathematics (1998, Paris Dauphine) and HDR (2008, Paris 6). Research projects include ANR STOIQUES (2024-2028), PEPR PDE-AI (2023-2028), and collaborations with industry on topics like defect prediction in aluminum production and high-dimensional data analysis. Teaching includes courses on linear algebra, optimization, and machine learning at undergraduate and graduate levels. Key contributions span phase field models, varifold-based surface approximation, and image inpainting. He supervises PhD students in geometric variational problems and computational methods. His work bridges theoretical mathematics with industrial challenges, addressing issues in materials science, medical imaging, and cultural heritage preservation.
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 .
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.
Giuseppe Vecchi is a Full Professor at the Department of Electronics and Telecommunications (DET) of Politecnico di Torino , Italy. He leads the Applied Electromagnetics research group and contributes to projects in computational electromagnetics, metamaterials, and biomedical applications of electromagnetic fields. He has been a IEEE Fellow since 2010 and serves on PhD college committees for Electrical, Electronic, and Communications Engineering. Research Interests : Antennas, Applied and Computational Electromagnetics, Metamaterials, Microwave Imaging for medical applications, Nuclear Fusion Reactor Physics. Scientific Leadership : Principal Investigator for projects like METEOR, MTSA, and RESOLVED-K, focusing on terahertz generation, metasurface antennas, and real-time temperature mapping in hyperthermia. Awards : IEEE Fellow (2010), recognizing his contributions to electromagnetic simulations and antenna design. Students : Supervises PhD candidates in advanced antenna engineering, computational electromagnetics, and biomedical applications, including Owais Khan, Francesco Lattanzio, and Sara Paknezhad Panahi. Patents : Holds multiple patents in antenna diagnostics, encrypted metasurface antennas, and microwave soil disinfection systems.
Francesca Marazzi is an Assistant Professor at the University of Rome Tor Vergata's Department of Economics and Finance. She holds affiliations with the CESifo Research Network (as an affiliate), the CESIEG research centre at LUISS Guido Carli University (Deputy Director), and the DEMA P research cluster at Middlesex University, London. Her research focuses on behavioral and experimental economics, particularly exploring dishonest behavior, responsibility avoidance, and health economics issues like women's health and obesity interventions. She teaches courses such as 'Coding for Economic Applications' and 'Research Methods for Social Sciences' at both bachelor's and master's levels. Her work bridges theoretical models with empirical experimentation, addressing topics like corruption, public goods provision, and policy design. Notable contributions include studies on transparency's impact on bribery, pandemic-related behavioral changes, and the effects of soft drink taxation on adolescent health. She actively participates in interdisciplinary projects, such as the CREA initiative integrating AI and mathematics for fairness assertions, and the LongITools exposome analysis in chronic disease research. Marazzi's academic output emphasizes experimental methodologies, with recent focus on pandemic-driven behavioral shifts, financial stability mechanisms, and innovative governance metrics leveraging earth observation data post-wildfires. Her research portfolio reflects a commitment to applied microeconomic analysis with direct societal relevance.
Marco Badami is a Full Professor at the Department of Energy (DENERG) , Polytechnic of Turin. He serves as Scientific Director for national and EU-funded research projects in energy systems and has been a Course Lecturer for Energy Systems and Industrial Use of Energy since 2010. He supervises PhD students in Energetics and Electrical Engineering . Research Interests: His work spans energy systems optimization, machine learning applications for industrial energy efficiency, smart grids, cogeneration scheduling, blockchain-based energy data immutability, and predictive maintenance algorithms for photovoltaic plants. Current projects focus on AI-driven energy audits, optimized control systems for industrial microgrids, and digital twin architectures. Collaborations: He works with Trigenia Srl, Stogit SpA, and international institutions on commercial research contracts. His scientific contributions include 15+ publications on topics like LSTM forecasting for solar energy, deep reinforcement learning for multi-energy systems, and decentralized peer-to-peer energy trading platforms.
Federico Silvestro is a Full Professor at the University of Genoa , affiliated with the Naval, Electrical, Electronic and Telecommunications Engineering Department . His academic roles include being a Course Coordinator, Department Council Member, and Deputy Director of DITEN. His research focuses on Power systems stability and control Cybersecurity in energy networks Electric propulsion for marine applications Optimal energy storage and microgrid design Integration of renewable energy in maritime contexts Recent publications highlight trends in data-driven power system analysis , DC microgrid modeling , cybersecurity for virtual power plants , and advanced energy management strategies for maritime and port systems. Email: federico.silvestro@unige.it He leads the ENET-RT Lab , focusing on real-time power systems simulation and co-simulation platforms for marine and grid applications.
Luigi Bruno is an Associate Professor of Machine Design at the Department of Mechanical, Energy and Management Engineering (DIMEG), University of Calabria. He has held this position since 2014, following 12 years as an Assistant Professor at the same institution and Visiting Professorships at IIT Gandhinagar (2012), University of Alabama at Birmingham (2013-2017), and Free University of Bozen-Bolzano (2021). 1999 : Master's in Mechanical Engineering, University of Calabria (110/110 cum laude) 2003 : PhD in Mechanical Engineering, University of Pisa His research interests span: Experimental Mechanics : Pioneering speckle interferometry for micro-displacement measurement and residual stress analysis. Materials Science : Elastic characterization of anisotropic materials, biomedical applications of soft substrates, and 3D-printed composites. Biomedical Engineering : Mechanical behavior of biological tissues, ocular biomechanics, and dental implant material testing. Recent research trends focus on: Integrating artificial muscles into rehabilitation devices Advancing full-field optical measurement via microCT/DVC Optimizing 3D printed polymer adhesion for industrial components Exploring neuronal biomechanics on soft surfaces Scientific contributions include: CS2007A00010 patent for dual-focus speckle interferometers Deputy Editor of Optics and Lasers in Engineering (2019-present) Guest Editor for special issues on optical methods in experimental mechanics and nanobiotechnology Academic leadership extends to coordinating Mechanical Engineering committees (2021-present), serving on editorial boards, and organizing international conferences like AIAS National Conference (2018). He has secured multiple MIUR research grants and industry collaborations with Alfagomma, 3DNA, and Ferrovie della Calabria. His laboratory, Mechanics of Materials and Structures , supports both research and teaching activities with advanced optical measurement systems and computational tools for mechanical design.
Roberto Garello is a Tenured Associate Professor at the Department of Electronics and Telecommunications (DET) of Politecnico di Torino . He specializes in Communication Systems , Satellite Networks , and Channel Coding , with a focus on 5G/6G Technologies and Non-Terrestrial Networks . His work aligns with the School of Master’s Programmes and Lifelong Learning . Research Interests: Satellite communications systems, Direct-to-Satellite IoT constellations, Mega-constellation services in space, and physical layer advancements for 5G/6G. Teaching: Offers courses like Information Theory for Data Science , Communication and Network Systems , and Space Exploration and Resources , while supervising Applied Signal Processing Laboratory . Projects: Leads initiatives such as DitDSSS (satellite localization), RESTART (future telecommunications), and TESL@ (ICT energy efficiency). Scientific Awards: Received Best Paper Awards at CTRQ 2010 and COCORA 2013. Students: Supervises PhD candidates including Alessandro Compagnoni, Agbotiname Lucky Imoize, and Riccardo Tuninato, focusing on topics like Wireless Communication, Machine Learning, and Non-Terrestrial Networks. Publications: His recent work explores OTFS vs. OFDM, spectrum sensing algorithms, MIMO with cylindrical arrays, and 5G NTN synchronization, reflecting trends in satellite IoT and machine learning integration.
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.
Fabrizio Falchi is a researcher at the Artificial Intelligence for Media and Humanities (AIMH) Lab of the Institute of Information Science and Technologies (ISTI) within Italy's National Research Council (CNR). He also maintains an associate position at the Biorobotics Institute of Scuola Superiore Sant'Anna. His work focuses on developing advanced multimedia retrieval systems, with the VISIONE platform being his most notable contribution, which has won international competitions including the Video Browser Showdown in 2024 and placed second in 2023. Falchi's educational background includes: Ph.D. in Information Engineering from University of Pisa (Italy) Ph.D. in Informatics from Faculty of Informatics of Masaryk University of Brno (Czech Republic) M.B.A. from Scuola Superiore Sant'Anna in Pisa His research spans deep learning, convolutional neural networks, deep features extraction, similarity search algorithms, distributed indexing systems, multimedia information retrieval, computer vision applications, and peer-to-peer systems. Falchi has made significant contributions to fine-grained visual understanding, cross-modal retrieval (particularly image-text matching), and robustness of deep learning systems against adversarial attacks. His work demonstrates a strong focus on practical applications of these technologies, particularly in video retrieval systems and safety monitoring solutions. Analysis of Falchi's recent publications reveals a strong focus on video and image retrieval systems, with the VISIONE platform being central to his work. His research shows increasing emphasis on fine-grained understanding in computer vision, cross-modal retrieval, and addressing practical challenges like cross-resolution face recognition. Recent work demonstrates innovation in making these systems more efficient through techniques like knowledge distillation (ALADIN) and leveraging virtual worlds for training data. His publications consistently bridge theoretical advances with practical applications in surveillance, safety monitoring, and multimedia search. Falchi's work has received significant recognition: Best paper award at CBMI 2024 for 'Is ClLIP the main roadblock for fine-grained open-world perception?' VISIONE 2024 won the Video Browser Showdown competition in Amsterdam VISIONE obtained second place at Video Browser Showdown 2023 in Bergen Best Paper Award for 'Learning Safety Equipment Detection using Virtual Worlds' at CBMI 2019 Falchi collaborates extensively with researchers at ISTI-CNR, particularly within the AIMH Lab. His work on VISIONE involves collaboration with Giuseppe Amato, Paolo Bolettieri, Fabio Carrara, Claudio Gennaro, Nicola Messina, Lucia Vadicamo, and Claudio Vairo. As co-chair of Ital-IA 2023, the 3rd National Conference on Artificial Intelligence, he plays an active role in the academic community. He is a member of ACM (since 2012), the Computer Vision Foundation, the Italian Association for Computer Vision Pattern Recognition and Machine Learning (CVPL), and the CINI Lab on Artificial Intelligence and Intelligent Systems. Falchi is a key member of the Artificial Intelligence for Media and Humanities (AIMH) Lab at ISTI-CNR, where he leads research on video retrieval systems. The lab has developed the award-winning VISIONE platform, which combines multiple scientific results in content-based video retrieval. His team focuses on developing systems that enable users to search for target videos using textual prompts, drawing objects and colors, or images as query examples. The lab's work demonstrates strong interdisciplinary collaboration, bridging computer science with practical applications in media, safety monitoring, and urban environments.
