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 .
Paul Major is a Full Professor in the Department of Mechanical and Aerospace Engineering at the Polytechnic University of Turin, where he has established himself as a leading researcher in aerospace systems. He serves as a member of the PhotoNext Interdepartmental Center for Applied Photonics and the University Internship Commission, demonstrating his commitment to interdisciplinary research and student development across multiple domains of engineering. Professor Major's research focuses on digital twin technology, prognostics and diagnostics of aerospace systems, and embedded sensor systems. His work bridges theoretical modeling with practical applications, particularly in the areas of augmented reality for aircraft monitoring, optical fiber sensors for structural health monitoring, and machine learning applications for predictive maintenance of electromechanical systems. His research has significant implications for improving aircraft safety, efficiency, and sustainability, with applications extending to lunar exploration technologies and space habitat design. His recent publications reveal a strong trend toward integrating advanced computational methods with physical systems, particularly in the domains of lunar exploration technology, additive manufacturing for aerospace applications, and sustainable aviation solutions. The interdisciplinary nature of his work spans aerospace engineering, computer science, materials science, and control systems, reflecting the increasingly interconnected nature of modern engineering research. His team has made significant contributions to optical sensor integration, AR visualization for maintenance, and prognostic frameworks for electromechanical systems. Professor Major actively mentors doctoral students, with current advisees including Matteo Bertone, Pierluigi Vergari, Armando Vittorio Atzori, and several others working on cutting-edge aerospace projects including lunar drones, aircraft anti-icing systems, and electromechanical actuator diagnostics. He has secured numerous research grants from both competitive funding bodies and commercial contracts, including projects like ASTRA (Advanced Space Tethers for Remote-sensing Applications), SmartCore, and FreME (Freno Multidisco Ad Attuazione Elettromeccanica Smart). He leads the ASTRA research group focused on Additive manufacturing for Systems and sTRuctures in Aerospace and is actively involved with the student team ICARUS. His work has practical applications in both terrestrial and space environments, with recent projects addressing lunar exploration technologies, sustainable aviation solutions, and advanced monitoring systems for aerospace applications.
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.
Dr. Danilo Giordano is an Associate Professor at the Department of Control and Computer Science (DAUIN) within Polytechnic University of Turin. He actively contributes to the SmartData@PoliTO Center, focusing on big data and data science applications. Research Interests: Big data, machine learning, cybersecurity, predictive maintenance, smart cities Scientific Awards: Best Student Paper Award ITC (2015), IETF Applied Research Prize coauthor (2017) His academic work spans machine learning for network security , big data analytics in industrial contexts , and smart city infrastructure optimization . Notably, his recent publications examine satellite network performance, darknet visibility enhancement, and language model applications in cybersecurity. As an editorial board member of COMPUTER NETWORKS (since 2024), he has also organized multiple conferences including the Data Challenge sessions at PHME conferences and served as publication chair for ACM CoNEXT workshops.
Luca Barbierato is a Fixed-term Assistant Professor at the Department of Control and Computer Engineering (DAUIN), Politecnico di Torino, specializing in applied artificial intelligence, cybersecurity, and co-simulation infrastructures for integrated energy systems. He actively contributes to research in edge computing, IoT, and sustainable energy technologies. Research Focus: AI applications in energy systems, secure IoT infrastructures, and co-simulation frameworks Teaching Roles: Invited PhD teaching component (2025/26), teaching assistant across multiple programs His recent publications address critical areas including OpenTitan-based security controllers, urban building energy modeling, and distributed power system co-simulation. Barbierato's work aligns with SDG Goals 7 (Affordable Energy), 9 (Innovation Infrastructure), and 11 (Sustainable Cities). Notable scientific recognition includes the Learning to Teach (L2T) badge from Politecnico di Torino.
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.
Gaia Maselli is an Associate Professor at the Department of Computer Science, Sapienza University of Rome. She holds a Ph.D. in Computer Science from the University of Pisa and serves as an Associate Editor for Elsevier Computer Communications. Her professional roles include membership in the TPC of multiple international conferences and leadership as Program Co-Chair for WONS 2025. Her research focuses on cybersecurity, network security, and applications of machine learning in data analysis and artificial intelligence. She contributes to interdisciplinary projects such as the NATO-funded "SeaSec: DroNets for Maritime Border and Port Security" (2021-2023), which aligns with her expertise in secure networked systems. She is actively involved in academic leadership and collaborative research initiatives within the field of computer science.
Angelo Spognardi is an Associate Professor in the Department of Computer Science at Sapienza University of Rome, leading the Network Security Lab group since March 2020. He teaches courses including Practical Network Defense and Programming Unit 2 for Computer Science and Cybersecurity programs. His research spans information security , with emphasis on fake phenomena in social media , fake content analysis in review systems, adversarial machine learning , and network security for resource-constrained devices . His work integrates bio-inspired models for bot detection and focuses on resilient metrics against disinformation campaigns. Recent publications explore LLM-powered bot detection and IPv6 security. He leads the Prebunking research project predicting coordinated inauthentic behaviors in social media. His lab promotes initiatives like CyberX Mind4Future , offering cybersecurity training with virtualized labs and hackathons. Master's students in Cybersecurity under his guidance achieve 100% placement with top salaries in Italy. Spognardi maintains active collaborations with the Sysma group at IMT Lucca and previously worked with DTU IoT Center and CNR's Institute of Informatics and Telematics. His industry impact includes frameworks like SafeDroid for Android malware detection and analyses of IoT broker vulnerabilities.
Gabriele Tolomei is an Associate Professor of Computer Science at Sapienza University of Rome. He leads the HERCOLE Lab (Human-Explainable, Robust, and Collaborative Learning) and focuses on advancing AI systems that are interpretable, robust, and decentralized. His research spans machine learning, computer security, and adversarial learning. PhD in Computer Science, Ca' Foscari University of Venice (2011) MSc in Computer Science, University of Pisa (2005) BSc in Computer Science, University of Pisa (2002) His research interests are centered on Explainable AI , Robust Machine Learning , and Collaborative Learning . He has contributed to areas such as counterfactual explanations for graph neural networks, community membership privacy, and fairness in graph algorithms. His work intersects Web Search and Mining with Computational Advertising , emphasizing user engagement and post-click satisfaction. He teaches courses like Operating Systems for BSc Computer Science and Big Data Computing for MSc Computer Science. Current PhD students under his supervision include Edoardo Gabrielli, Fabiano Veglianti, Flavio Giorgi, Matteo Silvestri, and Vittoria Vineis. The HERCOLE Lab, established in 2021, promotes interdisciplinary research on human-centered AI, adversarial resilience, and edge computing. Collaborators include Fabrizio Silvestri (Full Professor), Federico Siciliano (Postdoctoral Researcher), and Ziheng Chen (Research Scientist at Walmart Labs).
Chiara Brombin serves as Associate Professor of Statistics (SECS-S/01) at Vita-Salute San Raffaele University's Faculty of Psychology and contributes to the University Center for Statistics for Biomedical Sciences (CUSSB). Her academic career at the institution spans from Research Fellow (2010-2013) through fixed-term researcher positions (2013-2021) to her current role, demonstrating sustained institutional engagement and scholarly progression. Education: PhD in Statistical Sciences (2009), University of Padua Bachelor's Degree in Statistical and Economic Sciences (2005), University of Padua Research Focus: Dr. Brombin specializes in shape analysis, permutation testing, and advanced multivariate modeling with biomedical applications. Her work develops computational frameworks integrating facial expressions/biosignals (FIRB 2012 project) and applies joint latent class models to clinical subgroups. Recent publications emphasize statistical innovation in gene therapy efficacy, cancer treatment optimization, and pandemic response analytics through rigorous longitudinal/survival modeling. Publication Trends: Her 2024-2025 output in Nature, Science Translational Medicine, and specialized biostatistics journals reveals three converging themes: (1) network-based approaches for psychophysiological healthcare data, (2) joint modeling of longitudinal biomarkers with survival outcomes in immunology/oncology, and (3) shape analysis applications in genomic editing safety assessment. These works consistently integrate Bayesian networks with permutation-based validation. Scientific Recognition: Futuro in Ricerca 2012 award (MIUR) for emotion interpretation research Academic Leadership: Dr. Brombin has coordinated doctoral committees for Cognitive and Behavioral Sciences (2022-2024 cycles) and secured FIRB project funding as national coordinator. Her teaching portfolio spans undergraduate statistics methodology to graduate advanced modeling, with current responsibility for five courses including Multidimensional Data Analysis and Advanced Modeling in Psychology. She maintains active collaboration with CUSSB research teams on gene therapy and cancer imaging projects. Research Infrastructure: As core faculty in CUSSB, she leads statistical development for interdisciplinary teams in hematopoietic stem cell research and prostate cancer radiotherapy trials, applying shape analysis to [11C]-choline PET/CT imaging data and developing open-source tools for joint model implementation.
Ilaria Lucrezia Amerise is an Associate Professor in the Department of Economics, Statistics and Finance 'Giovanni Anania' (DESF) at the University of Calabria (UNICAL). Her research focuses on multivariate analysis, time series, nonparametric statistics, and statistical methods for complex/high-dimensional data including functional and spatial data. Editor-in-Chief of JP Journal of Biostatistics (ANVUR Area 13) Editorial Board Member of International Journal of Statistics and Systems (ANVUR Area 13) Recent research involves: Statistical preprocessing of crowdsourced data for Nigerian food prices Quantile regression with heteroskedasticity and non-crossing constraints Electricity demand forecasting via Reg-SARMA models Exchange rate prediction using simultaneous prediction intervals Time series outlier detection and smoothing techniques She contributes to academic governance through the Laboratorio Statistico Informatico (Statistical Informatics Lab) within DESF. Teaching includes undergraduate and graduate courses in Statistics, with materials available in both Italian and English.
Professor Luca Fanucci is a Full Professor of Electronics at the Department of Information Engineering , University of Pisa. He serves as Rector's Delegate for Inclusion of Students with Disabilities and leads research in integrated circuits, embedded systems, and assistive technologies . Institutional roles include membership in the National University Conference of Delegates for Disability (CNUDD) and leadership in the PhD program in Information Engineering. Born: Montecatini Terme (1965) Education: Laurea in Electronic Engineering (1992), PhD in Information Engineering (1996), University of Pisa Professional Journey: ESA research (1992-1996), CNR researcher (1996-2004), University of Pisa faculty (2004-present) His research focuses on: System-level design of integrated circuits and embedded systems Hardware-software co-design for low power consumption Spacecraft and satellite communication systems Medical devices and telemonitoring platforms Assistive technologies for disabilities Recent publications highlight AI in space applications and telemedicine systems . Key projects include the Ingeniars spin-off for satellite communications and the AsTech National Laboratory for assistive technologies. Scientific Recognition : IEEE Fellow (2019) 40+ patents H-index 34 (5000+ citations) He coordinates international conferences (DATE, HiPEAC, Spacewire) and serves as Associate Editor for Technology and Disability and Microprocessors and Microsystems journals.
Aris Anagnostopoulos is a Professor at the Department of Computer, Control, and Management Engineering (Dipartimento di Ingegneria Informatica, Automatica, e Gestionale) at Sapienza University of Rome since April 2012. His academic journey includes a Marie-Curie fellowship at Sapienza University and a postdoctoral position at Yahoo! Research in Santa Clara, CA. His educational background includes: Ph.D. in Computer Science, Brown University, Providence, RI Sc.M. in Applied Mathematics, Brown University, Providence, RI Sc.M. in Computer Science, Brown University, Providence, RI Diploma in Computer Engineering and Informatics, University of Patras, Patras, Greece Professor Anagnostopoulos's research focuses on the design and analysis of algorithms with applications in data mining and data science. His work spans stochastic analysis of dynamic processes, social network modeling and mining, WWW algorithms, randomized and approximation algorithms, information retrieval, and information security. His research has evolved to address contemporary challenges in federated learning, knowledge graphs, and ethical AI considerations in recommendation systems. His recent publications demonstrate a strong trend toward addressing real-world applications of data science and machine learning, particularly in healthcare, social media analysis, and privacy-preserving techniques. His work shows increasing interdisciplinary collaboration, especially with medical researchers, while maintaining strong theoretical foundations in algorithm design. Among his notable scientific awards are: Google Focused Research Award (1 of 6 PIs), 1M USD Junior Fellow, School for Advanced Studies, Sapienza University of Rome Personal research grant, Swedish Research Foundation, 200K euro, 2011 (declined) Best Poster Award, 4th International Conference on Web Search and Data Mining (WSDM 2011) Marie Curie International Incoming Fellowship, 160K euro, 2010 Paris Kanellakis Fellowship, Brown University Runner Up, Best Paper Award, 14th International World Wide Web Conference 2005 (WWW 2005) Professor Anagnostopoulos serves as the academic responsible for mobility (RAM) for the Data Science master's program and has developed comprehensive teaching materials for data science education. He teaches courses including Social Networks and Online Markets, Algorithmic Methods of Data Mining, Data Mining, and Algorithm Design. His teaching approach emphasizes both theoretical foundations and practical applications, with extensive use of AWS and Python-based tools to prepare students for industry certification.
Giuseppe Antonio Di Luna is an Associate Professor at the Dipartimento di Ingegneria Informatica, Automatica e Gestionale (DIAG), Sapienza University of Rome . His research spans critical areas of Distributed Computing, Distributed Systems , and Computer Security , with a focus on Dynamic Networks, Mobile Agents, Anonymous Communication , and NLP techniques applied to binary analysis . Current research themes include anonymity in distributed environments Security challenges in confidential computing Algorithm design for mobile robots and dynamic networks Applying NLP to enhance binary analysis security His recent publications across top venues like DSN, EuroS&P, and JPDC reflect these interdisciplinary interests, with notable work on: Black hole detection in dynamic rings Robustness of binary similarity systems Confidential virtual machine evaluation tools Self-stabilizing computation in anonymous networks He has received prestigious awards including the Axa Fellowship (2020-2022) , ASPLOS 2019 Distinguished Paper Award , and DIMVA 2019 Best Paper Runner-Up . His collaborative efforts include organizing the EuroSys 2023 conference in Rome.
