Dr. Simone Torsani is an Associate Professor at the Department of Modern Languages and Cultures, University of Genova. His work bridges computational linguistics, translation studies, and educational technology through research, teaching, and institutional leadership roles. His research focuses on AI applications in language education Computational linguistics for plurilingualism Machine translation and post-editing EdTech solutions for inclusive education Recent publications examine generative AI's role in grammar instruction and special educational needs inclusion through technology. He actively contributes to university governance as Member of the Scientific Council of the University Service Center for Simulation and Advanced Training (SIMAV) Member of the CLAT Commission for curriculum development His teaching portfolio includes courses on language teaching, computational linguistics, and AI applications in translation studies.
Cristina Cheroni is a computational biologist with over 15 years of experience in neurobiology, currently serving as Senior Manager of the Cell Reference Brain Atlas Scientific Service Unit (CEREBRA) at Human Technopole since October 2022. Prior to this, she was a Senior Computational Biologist in Prof. Testa's research group (2017–2022), focusing on neurodevelopmental disorders linked to genetic lesions or environmental chemicals. PhD in Biomolecular and Life Sciences from the Molecular Neurobiology Laboratory at the M. Negri Institute for Pharmacological Research (focused on amyotrophic lateral sclerosis) Research at the National Institute of Molecular Genetics integrating clinical and experimental omics data Current work on single-cell resolution datasets and cerebral organoids Her research spans computational biology applied to molecular neurobiology, with a focus on neurodevelopmental disorders like Williams-Beuren syndrome and autism. She employs brain organoids and integrative omics approaches to dissect genetic and environmental influences on neurogenesis and social behavior. Recent publications highlight her contributions to understanding GTF2I dosage effects in 7q11.23 disorders, CHD8 haploinsufficiency in autism, and benchmarking brain organoid models. Her work intersects neuroscience, genetics, and environmental science, emphasizing translational insights into neurodevelopmental mechanisms. As no formal awards, grants, or student mentoring details are explicitly provided in the text, these aspects remain unlisted. Her affiliations include M. Negri Institute, National Institute of Molecular Genetics, and Human Technopole.
Maurizio Rebaudengo is a Full Professor at the Department of Control and Computer Science (DAUIN) of the Polytechnic University of Turin. He is a member of the PIC4SeR Interdepartmental Center for Service Robotics and holds expertise in embedded systems, fault tolerance, and sensor network applications. Research Interests: Embedded systems, fault tolerance, precision agriculture, RFID technology, wireless sensor networks, and system dependability Scientific Awards: Ramamoorthy Best Paper Award (1997) Leadership Roles: Program Chair for the 4th International EURASIP Workshop on RFID, Committee Member for Public Administration Agreements (2020-2024) Projects: Scientific Director for HONEY (Hybrid ONline tEchnologY for particle therapy), FDM (Food Digital Monitoring), IDEM (Internet of Data for Environmental Monitoring), and OPLON (Healthy Longevity Opportunities). Teaching: Course lecturer for Electronic Calculators, Computer Science, Systems Programming, and Cybersecurity at both undergraduate and postgraduate levels. His work spans IoT applications in agriculture and healthcare, focusing on low-cost sensor networks , RFID-based traceability , and cyber-physical system resilience . Recent publications emphasize particulate matter monitoring and secure communication protocols in wireless environments.
Walter Didimo is a Full Professor of Computer Engineering at the University of Perugia, with a career spanning over two decades. His expertise lies in Graph Drawing, Network Visualization, and Algorithm Engineering, contributing to advancements in Computational Geometry and Big Data. Researcher in Graph Algorithms (1996-2000) Assistant Professor (2001-2004), Associate Professor (2005-2024), Full Professor (2024-) Director of Research Unit CINI (2019-2022) His research focuses on hybrid graph visualization models (e.g., ChordLink), distributed graph processing (e.g., GiViP), and practical applications in cultural heritage (e.g., CHIP) and web analytics (e.g., COWA). Recent work includes scalable algorithms for heterogeneous networked data and visual analytics for genomics (GGB Consortium). Scientific Awards: Best Paper Award - Track 2, Graph Drawing 2021 He has been instrumental in technology transfer, co-founding Vis4 Srl (2009) and contributing to the GGB Consortium. His editorial roles include Associate Editor of IEEE Access and guest editorships for CGTA and JGAA.
Andrea Bottino is an Associate Professor at the Department of Control and Computer Engineering (DAUIN) at the Polytechnic University of Turin. He has been actively involved in the Computer Graphics and Vision Group and leads various VR@POLITO initiatives. Chair of the Master HUMANAIZE program Coordinator of multiple Machine Learning for Vision and Multimedia courses Research Focus : Augmented and Virtual Reality for education and safety Computer Vision with applications to medical imaging and kinship analysis Human-Computer Interaction in immersive environments Multimodal Learning systems XR for Cultural Heritage Publication Trends : Recent works focus on AI applications , XR training systems , and computer vision techniques applied to medical diagnostics and cultural preservation . Leadership Roles : Scientific Director for MEI - Interactive Egyptian Museum Coordinator of PNRR Mission 4 projects Principal Investigator for Holo-BLSD and ALPTECH initiatives Labs and Collaborations : Active in Visionary LAB and VR@POLITO Collaborates with Balletto Teatro di Torino for cultural XR applications Partners with Fondazione Museo Egizio and Robin Studio
Santa Di Cataldo is an Associate Professor at the Department of Control and Computer Engineering (DAUIN) of Politecnico di Torino. His research focuses on computer vision, pattern recognition, digital image processing, and medical image processing, with applications in industrial systems and AI for manufacturing. Scientific Branch: IINF-05/A - Information Processing Systems ERC Sectors: PE6_8 - Computer graphics, computer vision, multi media, computer games ERC Sectors: PE6_11 - Machine learning, statistical data processing His work includes developing AI-driven anomaly detection frameworks, physics-informed neural networks for additive manufacturing optimization, and neuro-symbolic approaches for Industry 4.0 applications. He supervises PhD students in Artificial Intelligence and Computer Engineering programs, collaborating on projects like BIG (Blue Is Green) and PNRR-Complementary Plan. Premio Donna Innovazione (2010) He leads courses such as Machine Learning in Applications and Applied AI and Machine Learning , while contributing to bioinformatics and robotics-related teaching. His research is supported by IAM@PoliTo and EDA groups, utilizing LADISPE laboratory facilities.
Alessandro Rizzo is an Associate Professor in Automation Engineering at the Politecnico di Torino , affiliated with the Department of Electronics and Telecommunications (DET) and the PIC4SeR Interdepartmental Centre for Service Robotics . He holds a PhD from the University of Catania and has held academic roles at Polytechnic University of Bari (2002–2015) and NYU Tandon School of Engineering (visiting roles). His work spans complex networks , robotics , epidemic modeling , and distributed control systems . Education : Laurea summa cum laude in Computer Engineering (University of Catania, 1996), PhD in Electronic and Control Engineering (University of Catania, 2000). Research Interests include data-driven control of autonomous vehicles, network dynamics , cooperative robotics , and epidemic modeling for public health. His recent articles focus on Koopman-based predictive control , adaptive bio-inspired architectures , and distributed localization algorithms . Scientific Awards include the IFAC Best Application Paper Award (2002) , IEEE Distinguished Lecturer (2007) , IEEE Senior Member (2008) , and APS Highlight in Physics (2014) . PhD Supervision : Mentoring research on AI for robotics, epidemic control, and autonomous systems, with students like Lorenzo Calogero and Zhipeng Ding . Editorial Roles : Associate Editor for journals such as IEEE Transactions on Control of Network Systems and IEEE Robotics and Automation Letters .
Renato Ferrero is an Associate Professor at the Department of Control and Computer Science (DAUIN), Politecnico di Torino (Polito) , with key roles as contact person for training activities and member of the PIC4SeR Interdepartmental Center for Service Robotics . His research spans Wireless Sensor Networks (WSN) , Internet of Things (IoT) , and Environmental Monitoring , supported by competitive grants like AGRITech Spoke 6 (2022-2025) and MIUR funding (2017). He has published extensively on topics including air pollution monitoring , quantum-inspired security , and agricultural technology , with recent work focusing on deep learning for mask/respirator detection and biofertilizer analysis . As an IEEE Access Associate Editor and program committee member for conferences like COMPSAC and RFID-TA, he contributes to academic governance. His teaching includes Computer Architecture (2019-2025) and Ubiquitous Computing (2019-2021) at Polito. He advises PhD students Chiara Panico and Nicola Dilillo , with projects in Data Science , Computer Vision , and AI Life Sciences .
Mario Baldi is an Associate Professor (on leave) of Information Processing Systems at the Department of Control and Computer Engineering , Politecnico di Torino , and concurrently a Fellow in the Office of the CTO, Adaptive and Embedded Computing Group, at AMD, San Jose, CA. His career blends deep academic research with extensive industry R&D leadership. Education M.Sc. (Summa Cum Laude) in Electrical Engineering, Politecnico di Torino, 1993 Ph.D. in Computer and System Engineering, Politecnico di Torino, 1998 Research Focus Baldi’s research spans programmable data planes, software-defined networking, big-data analytics for network management, network security, high-performance switching architectures, optical networking, QoS mechanisms, and multimedia/voice-over-IP systems . He is especially known for pioneering work on P4 -based programmable networks and SmartNIC architectures. Publication & Patent Impact Across 150+ refereed papers and 35+ US patents (plus European filings), his recent output concentrates on machine-learning-driven network data-plane functions , disaggregated stateful network services , and cloud-grade DPUs . The 2021–2024 articles emphasize real-time inference directly in the network data plane and modular SDN programming. Awards & Honors Best Paper Award, IEEE ICC 2007 Best Paper Award, IEEE ISCC 2008 Best Paper Award, IEEE GreenComm 2009 Best Paper Award, ACM/IEEE WI/IAT 2014 Grants & Projects Baldi has served as Principal Investigator or Scientific Coordinator on numerous EU Framework and Italian national projects (PRIN, FAR), leading consortia on energy-efficient packet networks, trusted software execution, wireless mesh architectures, and streaming media delivery. Teaching & Mentoring He has taught graduate courses on Enterprise Network Technologies, Computer Network Technologies and Services, Networks/Cloud/Application Security at Politecnico di Torino since 2003. He has also supervised PhD collegi for the Computer and Systems Engineering doctoral program (cycles 19–23) and held visiting/adjunct positions across four continents. Labs & Teams Previously headed the NetGroup (Computer Networks Group) at Politecnico di Torino (2001–2007) and co-chairs the p4.org Architecture Workgroup , driving open standards for programmable networking.
Leonardo Badia is an Associate Professor at the University of Padova . He holds a PhD in Information Engineering from the University of Ferrara and has held academic positions at IMT Lucca Institute and the University of Padova since 2016. Research Interests : His work focuses on mathematical optimization for communication networks, including Markov models for protocol analysis, cross-layer optimization of routing/scheduling/resource allocation, Age-of-Information (AoI) , energy harvesting , and game theory applications. He has published over 200 papers in top-tier journals and conferences. Recent Articles highlight his contributions to AoI optimization, adversarial modeling in CPS, strategic cooperation in IoT/metaverse, and energy-efficient network protocols. His work spans telecommunications , game theory , and networking , with subfields like hybrid ARQ , multi-radio resource management , and QoS-aware scheduling . Awards : Best Paper Awards at IEEE MobiWac 2005, IEEE CAMAD 2006, and IEEE Globecom 2007.
Alessandro Checco is an Assistant Professor in the Computer Science Department at University of Rome La Sapienza. His research focuses on crowdsourcing, distributed systems, and privacy-preserving technologies, bridging theoretical computer science with practical applications that consider human factors in technological systems. He has established himself as a significant contributor to the field of human computation and privacy-aware systems. His educational background includes: 2020: Fellowship of Higher Education from The University of Sheffield, Higher Education Academy 2015: Ph.D. in Mathematics from Hamilton Institute (Design of decentralised algorithms applied to channel/code selection and convex optimisation for throughput fairness of 802.11 networks) 2010: M.Sc. in Mathematical Engineering from University of Roma "Tor Vergata" (110/110 with great distinction) 2009: Erasmus Scholarship at Universiteit Gent, Department of Telecommunications 2007: B.Sc. in Mathematical Engineering from University of Roma "Tor Vergata" (110/110 with great distinction) Checco's research spans multiple areas at the intersection of computer science and social implications of technology. He is particularly interested in Crowdsourcing for Human Computation, Distributed Private Recommender Systems, Information Retrieval, Data Privacy, Distributed Systems, User Data Obfuscation in Web Systems, Societal and Economic Analysis of Online Work, Crowd Workers Unionisation, and Algorithmic Bias. His work often examines how technological systems can be designed to respect user privacy while maintaining functionality, and how crowd work can be structured to be more equitable for workers. His recent publications demonstrate a clear evolution in research focus, beginning with foundational work in wireless networks and distributed algorithms, then shifting toward human computation and privacy-preserving systems. His most recent work increasingly addresses the societal implications of crowd work, including investigations into crowd worker unionization and cooperative models. Several publications examine gender bias in algorithmic systems, reflecting growing attention to fairness and ethical considerations in his field. Among his notable achievements: All That Glitters is Gold-An Attack Scheme on Gold Questions in Crowdsourcing (Best Paper Award) Checco has secured significant research funding and led important projects including the H2020-funded FashionBrain project as Research Director and the EPSRC-funded BetterCrowd project as Research Associate. His work on the FashionBrain project demonstrates his ability to lead large-scale, interdisciplinary research initiatives. He has also received the Technology Innovation Development Award (TIDA) from Science Foundation Ireland. His research has practical applications across multiple domains including recommendation systems (BLC: Private Matrix Factorization Recommenders), peer review assistance using AI, smart farming technologies, and cooperative models for crowd workers (CrowdCO-OP). He has developed frameworks for understanding worker behavior in crowdsourcing platforms and created methods for improving quality control in human computation systems.
Giorgio Casari is a Full Professor of Medical Genetics at the Faculty of Medicine, Vita-Salute San Raffaele University in Milan, where he also serves as Director of the Center for Genomics, Bioinformatics, and Biostatistics at the San Raffaele Scientific Institute. With over 35 years of experience, his career includes leadership roles as Head of the Human Molecular Genetics Unit (2000-2009) and Research Coordinator at TIGEM (1994-2000). He teaches undergraduate and graduate courses in genetics and biotechnology across three degree programs. His research centers on mitochondrial origin neurodegenerative genetic diseases, integrating molecular genetics, genomics, and bioinformatics to investigate pathogenic mechanisms. Key focus areas include Wolfram syndrome, spinocerebellar ataxias, and the role of inborn errors of immunity in severe viral infections. His work has revealed critical insights into autoantibodies against type I interferons in life-threatening SARS-CoV-2 and West Nile Virus infections, with implications for rare disease diagnostics and personalized therapeutics. Analysis of his 221 publications shows a dominant 2023-2025 trend in immunogenetics of infectious disease susceptibility, particularly inborn errors affecting interferon pathways (NF-κB, MyD88, IRAK-4, OAS-RNase L). Concurrently, he maintains strong output in mitochondrial neurodegeneration and rare metabolic disorders, with high-impact publications in Nature, Science, and Journal of Experimental Medicine reflecting translational significance. Scientific Awards: No specific awards documented in provided materials Advising and Grants: Doctoral Committees: Continuous service on International PhD Program in Molecular Medicine committees (Cycles 31-40, 2015-2024) Research Leadership: Principal contributor to IRDiRC initiative on newborn screening for inherited metabolic disorders Labs and Teams: As Director of the Center for Genomics, Bioinformatics, and Biostatistics, Casari leads a multidisciplinary team providing genomic data analysis, bioinformatics pipeline development, and biostatistical modeling for San Raffaele Scientific Institute researchers. The center specializes in rare disease genomics, neurodegenerative disorder mechanisms, and infectious disease susceptibility profiling, supporting over 20 research groups through high-throughput sequencing and computational infrastructure.
Marco Antonio Bruno Esposito is an Associate Professor in the Department of Oral Diseases and Dentistry at the School of Medicine, Vita-Salute San Raffaele University. He teaches courses in the Master's Degree in Medicine and Surgery (including internships in Surgery/Surgical Specializations) and the Degree Course in Dental Hygiene (Epidemiology). His academic responsibilities extend until 2026, confirming active faculty status. Research Focus Professor Esposito's research centers on evidence-based dental implantology and oral rehabilitation. Key interests include: Surgical Innovations : Flapless techniques, computer-guided placement, and sinus lift procedures. Prosthetic Outcomes : Immediate loading protocols, abutment design, and splinting strategies. Biomaterials : Bone substitutes and soft tissue management in alveolar ridge preservation. Publication Trends His 75 publications emphasize multicenter randomized controlled trials (RCTs) with long-term follow-ups (5-13 years). Recent work (2023-2025) predominantly evaluates clinical outcomes of dental implants, comparing surgical techniques, prosthetic designs, and biomaterials. Over 85% of extracted articles are RCTs, reflecting a rigorous focus on evidence-based oral rehabilitation. Teaching & Academic Service He coordinates professional internships in surgical specializations and lectures on Head/Neck Diseases and Epidemiology. No awards, students, or grants were identified in available data.
Andrea Fronzetti Colladon is a Professor of Business Leadership and Intelligence at Roma Tre University, where he leads the Business and Collective Intelligence Lab. His academic career bridges rigorous research with practical business applications, focusing on how connections drive value and innovation in complex organizational environments. His research interests span Network Science, Natural Language Processing, Machine Learning, Social Network Analysis, Text Mining, Brand Analytics, Change Management, and Executive Coaching . He combines methods from network science and computational linguistics with theoretical frameworks from social sciences to advance understanding of management and human behavior. His work has practical applications in brand analytics, change management, and organizational transformation. Developed the Semantic Brand Score methodology for brand performance analysis Created the OCEAN Change Management Model for organizational transformations Authored influential books including Leading Meaningful Change and Social Network Analysis and Text Mining for Big Data Collaborates with leading institutions including MIT Center for Collective Intelligence, Northeastern University, and Université du Québec à Montréal His recent publications reveal a strong trend toward integrating text mining and network analysis to solve business problems, particularly in brand management, venture capital funding, and organizational change. His work consistently demonstrates how linguistic patterns and network structures can predict business outcomes and inform strategic decisions. Among his notable recognitions is the 2020-2021 Best Paper award from the International Journal of Forecasting . His research has been published in high-impact journals and books with publishers including Edward Elgar, Springer, and Routledge. As an educator and consultant, Fronzetti Colladon develops specialized courses on Social Network Analysis, Text Mining, Change Management, Problem Solving, and Business Analytics. He has worked with major organizations including TIM, Genpact, Enel, SACE, Renault Italia, Saatchi & Saatchi, Sky Italia, and GalaxyAdvisors, translating academic insights into practical business solutions. The Business and Collective Intelligence Lab he leads serves as a hub for interdisciplinary research, bringing together computer scientists, linguists, social scientists, and business experts to decode complexity and empower decision-making through innovative methodologies.
Carla Limongelli is an Associate Professor at Roma Tre University's Department of Civil, Computer and Aeronautical Engineering within the School of Engineering. Her academic work bridges computer science with educational applications, focusing on intelligent systems for learning environments. Her research interests center on artificial intelligence applications in education, with particular expertise in concept mapping systems, learning management platforms, and technology-enhanced museum experiences. Dr. Limongelli has developed innovative approaches to adaptive learning, social robotics in educational contexts, and multimodal learning analytics that track both physiological responses and behavioral patterns. Her recent publication trends reveal a strong focus on leveraging large language models for educational purposes, with increasing attention to multimodal applications combining visual, textual, and physiological data streams. This work spans from automated question generation to social robot interactions in museum settings. Dr. Limongelli has contributed significantly to the development of systems that support teachers in course building, concept map creation, and personalized learning path configuration, with applications extending from traditional educational settings to cultural heritage environments.
