Stefania Monica is an Associate Professor at the Department of Engineering Sciences and Methods, University of Modena and Reggio Emilia. She specializes in Artificial Intelligence, Multi-Agent Systems, Robotics, and Programming Languages. Her research focuses on topics such as agent interaction protocols, indoor positioning algorithms, and agent-oriented programming (Jadescript). She teaches courses on Artificial Intelligence, Data Science, Web Technologies, and IoT. Recent work includes studies on stigmergic interactions in multi-agent systems and 3D indoor positioning using optimization algorithms. Her contributions span theoretical frameworks (e.g., kinetic models) and practical implementations (e.g., Jadescript language enhancements for robustness and interoperability). Research interests emphasize synergy between AI and robotics, with applications in localization, swarm intelligence, and neural-symbolic learning. Teaching responsibilities include managing engineering courses on data science, information systems, and IoT development. She actively contributes to academic conferences and journals, curating special issues on computational logic and agent-based systems.
Paolo Enrico Camurati is a Full Professor in the Department of Control and Computer Engineering (DAUIN) at the Polytechnic University of Turin, where he contributes to research and teaching in formal methods and hardware verification. He is a member of the Formal Methods (FM) research group and has been actively involved in PhD supervision in the Computer and Systems Engineering program. His research interests include formal verification, binary decision diagrams, SAT solvers, electronic CAD, and the formal verification of hardware design correctness. These areas align with theoretical computer science and cyber-physical systems, contributing to advancements in reliable computing systems. Recent publications (2022–2024) show a strong focus on model checking techniques, interpolation-based learning, and optimization of binary decision diagrams for machine learning applications, indicating active and impactful research in formal methods and EDA. He has taught core computer engineering courses such as Specification and Simulation of Digital Systems , Algorithms and Data Structures , and Programming Techniques at both bachelor's and master's levels, supporting quality education in computing disciplines. He has no listed scientific awards in the provided material. Prof. Camurati advises PhD students in the Computer and Systems Engineering program and has taught extensively across multiple academic years. While specific grants are not mentioned, his ongoing research output suggests active funding and project involvement. He is a key member of the FM - Formal Methods Group (DAUIN), which drives research in formal verification and automated reasoning. The FM - Formal Methods Group (DAUIN) serves as his primary research lab, focusing on theoretical and applied aspects of formal verification, model checking, and decision diagram technologies.
Stefano Quer is an Associate Professor at the Department of Control and Computer Science (DAUIN), Politecnico di Torino. He holds a PhD in Electronic Engineering from the same institution and has been affiliated with DAUIN since 1996. Researcher (1996-2000) Associate Professor (2000-present) Visiting Faculty at UC Berkeley (1994-1995) Research Interests His work spans Formal Verification BDD/SAT Techniques Embedded Systems Hardware/Software Co-Verification Parallel Computing with applications in VLSI CAD, industrial IoT, and energy-efficient systems. Recent articles focus on GPU-accelerated graph algorithms, wireless sensor calibration, and AI-driven test optimization. Scientific Awards Best Paper Award, IEEE EURO-DAC'94 Academic Contributions Supervised PhD students Lorenzo Cardone and Andrea Calabrese Member of DATE, ICSOFT Technical Program Committees Topical Advisor for Sensors MDPI 60+ publications in IEEE/ACM venues
Elena Umili is an Assistant Professor (RTD-A) at the Department of Computer, Control and Management Engineering (DIAG) of Sapienza University of Rome, specializing in Neurosymbolic AI research. Her work bridges deep learning with symbolic reasoning systems. She received her PhD in Engineering in Computer Science from Sapienza University of Rome in 2023 under the supervision of Prof. Giuseppe De Giacomo and Prof. Roberto Capobianco. Her doctoral thesis focused on 'Discovering Logical Knowledge in Non-Symbolic Domains'. Her research interests center on Neurosymbolic AI integration , particularly: Combining deep machine learning with symbolic reasoning Temporal logic specifications in neural systems Automata learning through neural relaxations Non-Markovian reinforcement learning tasks Visual grounding of logical specifications Analysis of her recent publications reveals a strong focus on neural-symbolic integration where she develops frameworks like DeepDFA and Neural Reward Machines. Her work consistently addresses the challenge of incorporating logical constraints into deep learning systems, with applications spanning robotics, sequence generation, and visual reasoning. The research demonstrates increasing sophistication in handling temporal logic specifications within neural architectures. She is an active member of research groups focused on Artificial Intelligence and Knowledge Representation, as well as Artificial Intelligence and Robotics at Sapienza University. While no formal advisees or major awards are currently documented in her public profile, her recent publications indicate significant contributions to the neurosymbolic AI field through top-tier conferences including ECAI, KR, and specialized workshops. Her work shows strong potential for future impact in bridging the gap between neural and symbolic AI paradigms.
Cristiano Pegoraro Chenet is a researcher affiliated with the Department of Control and Computer Engineering (DAUIN) at Politecnico di Torino. He holds the academic rank of Researcher and contributes to teaching as an external collaborator for the Algorithms and Programming course in the Electronic and Communications Engineering Bachelor’s program. Research Interests : Focused on resilient computer architectures, hardware-based malware detection, and design diversity techniques for fault tolerance. His work intersects machine learning, security, and embedded systems, particularly in cloud computing and RISC-V architectures. Publications : Active in IEEE conferences and journals, with a recent survey in IEEE ACCESS analyzing hardware malware detection methods. His research includes contributions to the Horizon Europe Vitamin-V project and experiments on radiation-hardened mixed-signal systems. Collaborations : Works with the SMILIES research group at DAUIN, engaging in international projects with institutions across Europe.
Luisa Mich is an Associate Professor in the Department of Industrial Engineering at the University of Trento, Italy, holding this position since 2002 after progressing from Research Fellow (1983-1987) to Researcher (1988-2001). She teaches Enterprise Information Systems, Tourism Information Systems, and Web Strategies across multiple departments including Economics, Humanities, and Mathematics, while pioneering ICT integration at the university since 1989. Education: PhD in Physics, University of Trento (1983), thesis: "Theory and experimentation on interaction in human systems" Scientific High School Diploma, Marcelline Institute, Bolzano (1976) Her research centers on Requirements Engineering innovations including the award-winning 7Loci meta-model for web presence strategy and enhanced creativity techniques surpassing traditional brainstorming. Current work integrates Natural Language Processing with legal document analysis and web reputation monitoring, demonstrating strong interdisciplinary connections between computer science, tourism management, and semantic technologies. Recent publications (2022-2025) reveal a decisive shift toward AI-driven business process development and tourism applications, with semantic technologies bridging legal compliance and requirements engineering. Key trends include agentic AI systems, optimized creativity techniques for requirements elicitation, and ontology-based personalization frameworks – all addressing practical challenges in destination management and customer experience. Scientific Recognition: While lacking major prizes, her expertise is validated through editorial board roles (Journal of Information Technology & Tourism, Journal of e-Learning) and leadership in professional societies including ACM, IEEE, and IFITT. Advising and Grants: Mich has supervised approximately 100 theses across scientific and humanities disciplines, including doctoral programs in Information Technology and Materials Science. Her grant leadership includes the European WEE-NET project (2005-2008) establishing Web Engineering networks and Papyrus (2008-2010) for cultural digital libraries, alongside consultancy for tourism boards like Suedtirol and Visit Trentino. Research Infrastructure: She co-founded Trento's Department of Information and Communication Technology and directed the Computer Science and Organisations program. Her ECDL certification initiative (1998-2010) became Italy's first university-adopted ICT certification, while her "ICT and tourism" research group drives destination management innovations through the Trentino Tourism System.
Ognjen Savkovic is an Assistant Professor (RTD-a) at the KRDB Research Center for Knowledge and Data, Faculty of Engineering, Free University of Bozen-Bolzano, Italy. He is based at the NOI Techpark in Bolzano and is actively involved in research on Knowledge Graphs, Semantic Web, and data quality. His work bridges formal logic and machine learning to enhance data management systems. His research interests include Knowledge Graphs, Semantic Web, Database Management, Data Quality, Artificial Intelligence, and Logic Reasoning. He focuses on schema validation (e.g., SHACL), property graph schemas (PG-Schema), and integrating machine learning with declarative languages like Datalog for industrial applications such as welding quality monitoring and cloud resource configuration. His recent publications show a strong trend in semantic technologies for industrial applications, particularly in collaboration with Bosch and Siemens. His work spans theoretical foundations of schema languages and practical implementations in smart manufacturing and cloud systems. He has published in top venues including WWW, ISWC, CIKM, and SIGMOD. Scientific Awards: No specific awards mentioned. Ognjen Savkovic advises students and collaborates on research projects, though specific students are not listed. His research involves significant grant-funded collaborations, particularly in EU-level industrial AI and semantic technology initiatives. He has contributed to projects involving Siemens and Bosch, focusing on semantic diagnostics and scalable data science solutions. He is a key member of the KRDB Research Center, contributing to a vibrant research team working on knowledge representation, reasoning, and industrial applications of semantic technologies.
Alessandro Chiado' is a Fixed-term Tenure-Track Assistant Professor at the Polytechnic University of Turin , affiliated with the Department of Applied Science and Technology (DISAT) and the PolitoBIOMed Lab - Biomedical Engineering Lab . Scientific disciplinary sector: BIOS-07/A - Biochemistry (Area 0005 - Biological Sciences) ERC skills: Genetic tools for medical diagnosis, Non-medical biotechnology, Medical technologies for disease monitoring, Spectroscopic techniques Research Interests focus on Antimicrobial Aptamers , Biosensors , MicroRNAs , and Protein Engineering . His work integrates nanotechnology with biochemical assays, particularly using SERS spectroscopy for food authenticity verification and biomedical diagnostics. Recent Work Trends include portable diagnostic platforms (e.g., DESPITE FRAUD project), glioma stem cell crosstalk inhibition strategies ( PRECISE project ), and advanced biosensor design. Articles emphasize FESEM image analysis , miRNA detection , and graphene-based microwave sensors . Scientific Awards :- CoV-Ab2 patent for SARS-CoV-2 seroprevalence testing- National patent for silver nanoparticle-porous silicon sensor Teaching Roles : Course collaborator in Materials and Characterizations for Micro and Nanotechnologies and Principles of Pharmaceutical Biotechnology across multiple engineering programs (Chemical, Aerospace, Automotive, Design). Supervised Research : PhD student Ettore Grimaldi's work on metal-dielectric nanostructures for SERS spectroscopy . Labs include the Vibrational Spectroscopy and Nano-optics Laboratory , Biochemistry Lab , and Nanoscience Labs (Organic Chemistry, Powder Chemistry, Vibrometric).
Juan David Guerrero Balaguera is a Research Fellow at Politecnico di Torino's Department of Automatic Control and Computer Science (DAUIN), affiliated with the CAD group. He holds a Ph.D. in Computer and Control Engineering from Politecnico di Torino (2024), advised by Prof. Matteo Sonza Reorda and Prof. Ernesto Sanchez. His research focuses on dependable hardware for safety-critical systems, including GPU reliability, fault tolerance, AI accelerators, and functional in-field testing. Prior to his Ph.D., he earned a Master's (2017) and Bachelor's (2013) in Electronics Engineering from Universidad Pedagógica y Tecnológica de Colombia, where he taught digital design, embedded systems, and FPGA-based image processing from 2014 to 2020. His research interests span advanced FPGA design, computational arithmetic for AI, fault effects analysis in GPUs, and reliability assessment of neural networks. Notable contributions include methods for generating self-test libraries (STLs) for GPUs, evaluating fault impacts on TCUs, and enhancing CNN robustness via dropout layer optimization. Education: Ph.D. in Computer and Control Engineering, Politecnico di Torino (2024) M.S. in Electronics Engineering, Universidad Pedagógica y Tecnológica de Colombia (2017) B.S. in Electronics Engineering, Universidad Pedagógica y Tecnológica de Colombia (2013) He has received the Ph.D. Quality Award (2023 and 2024) from Politecnico di Torino and Best Paper recognitions at DATE 2023 and DDECS 2021. His work bridges theoretical fault models with practical GPU testing methodologies, emphasizing real-world applications in AI and edge computing. Current teaching roles include collaborating on GPU programming (Master's level) and computer sciences courses (Automotive Engineering). Research collaborations involve exploring reliability trade-offs in split-computing DNNs and developing fault-aware design flows for AI accelerators.
Paola Iacumin is a Full Professor in Geochemistry and Volcanology (GEO/08) at the University of Parma's Department of Chemical Sciences, Life and Environmental Sustainability. She serves as Head of the Isotopic Geochemistry Laboratory and holds leadership roles in academic governance, including Delegate for Education and former Degree Course President. Education: PhD in Earth Sciences (1996, Université Pierre et Marie Curie, "Très honorable avec félicitations"); European Doctorate; Degree in Geological Sciences (1988, University of Trieste, 110/110 with honors) Her research focuses on isotopic techniques applied to Earth Sciences, paleoclimatology, and environmental monitoring. Key areas include hydrology , carbonate isotope analysis , paleodiet reconstruction , and food traceability . She has developed patented methods for isotopic analysis and founded LabGo s.r.l. for agri-food traceability solutions. Recent publications analyze chromium contamination in springs, squid fraud detection via lanthanide tracers, paleoenvironmental studies of Sudanese remains, and strontium isotope limitations in archaeology. Her work combines field studies (e.g., Mediterranean oceanographic expeditions) with laboratory innovations. Scientific Awards: Carlo Minguzzi Prize (1996) University of Trieste Degree Prize (1989) As principal investigator, she has led isotopic geochemistry projects while managing laboratory infrastructure and advising on curriculum development for environmental and geological degree programs.
Marilena Musci is an Associate Professor in Analytical Chemistry at the University of Parma, Italy. She has been active since 1999, transitioning from Assistant Professor to Associate Professor status while focusing on food chemistry research. 1993 - Chemistry Degree, University of Parma 1996 - Food Chemistry Specialization (cum laude), University of Parma Research Focus: Specializes in innovative extraction methods for trace compounds in complex food matrices, hyphenated analytical techniques for contaminant quantification, aromatic profile characterization of foods, and multivariate statistical analysis applications in food science. Teaching: Delivers courses on Analytical Chemistry, Chemiometric Techniques, Experimental Design, and Green Analytical Chemistry across first and second cycle degree programs in Food Science and Technology. Contact: Email: marilena.musci@unipr.it
Professor Andrea Arcuri is a leading academic in software engineering at Kristiania University College (formerly Westerdals), Oslo, where he has been a full-time Professor since October 2016 and leads the AISE (Automated Intelligent Software Engineering) lab. Additionally, he holds a part-time Adjunct Professor position at Oslo Metropolitan University (OsloMet) since 2020. His research interests revolve around Automated Software Testing and Search-based Software Engineering , with a focus on tools like EvoMaster (for system-level testing) and EvoSuite (for Java unit testing). His work integrates testing, security, and development practices for enterprise systems, particularly using SpringBoot , Kotlin , and Docker technologies. He has contributed to open-source educational materials on enterprise development, testing, and security, including courses PG5100 and PG6100 at Kristiania University College. His publications emphasize practical applications, such as cloud deployment, microservice architectures, and secure coding practices. Notable awards include: ACM SIGSOFT Impact Paper Award (2023) ICST 10-Year Most Influential Paper (2022) ICSE 10-Year Most Influential Paper (2021) Best Paper Awards at SSBSE (2017, 2015) IEEE Software Award (2017) ACM Distinguished Paper Awards (ASE 2015, ISSTA 2010) Best PhD Paper at SBST (2008) Professor Arcuri supervises PhD candidates and postdocs in automated testing and software quality, while actively serving on program committees for top journals and conferences. He advocates for hands-on learning through his open-source educational repository, which emphasizes Docker integration and practical examples for enterprise systems.
Yehia Moustafa Abd Alrahman is a PostDoc researcher at the SysMA research unit of IMT School for Advanced Studies Lucca, where he also participates in the FILIERASICURA project with Cisco. He is preparing to relocate to the University of Leicester to collaborate with Prof. Nir Piterman on the ERC Consolidator Project DSynMA (Distributed Synthesis from Single to Multiple Agents). His academic journey began with a scholarship-funded computer engineering degree at IMT Lucca, followed by a master's scholarship in computer science where he served as a teaching assistant. Abd Alrahman's research focuses on formal methods for developing correct-by-construction software systems with emphasis on predictability, adaptivity, efficiency, reusability, maintainability and modularity. His work particularly addresses challenges in contemporary information systems including embedded systems and service-oriented architectures. Currently, he is investigating formal analysis approaches for securing supply chains in cyber-physical systems. His research spans attribute-based communication, collective adaptive systems, multi-agent systems verification, and reconfigurable distributed systems. His publication record shows a consistent trajectory from foundational work on attribute-based communication (2014-2018) toward increasingly sophisticated verification frameworks for reconfigurable systems (2019-2025). Recent publications demonstrate a clear evolution toward distributed synthesis techniques, model checking for reconfigurable multi-agent systems, and formal frameworks for runtime reconfiguration. His work bridges theoretical computer science with practical applications in secure system design. Abd Alrahman completed his PhD with first honors rating 'excellent' in the Computer, Decisions, and Systems Science track at IMT School for Advanced Studies Lucca. While no formal awards are documented in the provided materials, his consistent publication record in top venues like FORTE, ISoLA, and AAMAS demonstrates recognition within the formal methods community. His collaborations with established researchers like Nir Piterman, Rocco De Nicola, and Michele Loreti indicate strong research networks. As a PostDoc researcher, Abd Alrahman works within the SysMA research unit at IMT Lucca, contributing to the Italian Project FILIERASICURA with Cisco. His upcoming move to Leicester represents a significant career advancement through the ERC Consolidator Project DSynMA, which will expand his research scope into distributed synthesis for multi-agent systems.
Laura Carnevali is an Associate Professor of Computer Science at the Department of Information Engineering, University of Florence, where she leads research in formal methods and performance evaluation as a member of the Software Technologies Lab. She teaches Software Engineering for Embedded Systems, Quantitative Evaluation of Stochastic Models, and Foundations of Computer Programming at the School of Engineering. Her research focuses on formal methods for real-time software development and performance evaluation of non-Markovian models, with significant contributions to the ORIS Tool for quantitative system analysis. Key areas include: Stochastic modeling of critical infrastructure Formal verification of real-time systems Reliability engineering methodologies Performance evaluation of cyber-physical systems Her publications show strong emphasis on applied formal methods, with recent work focusing on workflow analysis, infrastructure reliability, and transportation systems modeling. Research consistently integrates theoretical frameworks with practical applications in engineering domains. Awards include: Best Paper Award at ICPE 2021 She actively contributes to academic service as program committee member for leading conferences including FORMATS, QEST, and EPEW, and serves as reviewer for IEEE Transactions on Software Engineering, Reliability, and other prestigious journals.
Roberto Zunino is an Associate Professor in the Department of Mathematics at the University of Trento, specializing in blockchain technologies, formal methods, and distributed systems. His research bridges theoretical computer science with practical cryptographic applications, particularly in Bitcoin and smart contract ecosystems. His research interests focus on blockchain security , smart contract formalization , and probabilistic verification . Key areas include MEV (Maximal Extractable Value) theory, UTXO-based smart contracts, and computationally sound tokenization. His work combines rigorous mathematical modeling with real-world protocol analysis, emphasizing security guarantees through formal methods. Recent publications demonstrate a strong trend toward theoretical foundations of blockchain economics and security. His 15 most recent papers (2020-2025) analyze MEV formalization, Bitcoin contract liquidity, UTXO scalability, and smart contract language design, revealing deep integration of type theory, game theory, and cryptographic primitives. Zunino actively teaches courses including Informatics , Interactive Theorem Proving (using Lean 4), and Computer Tools for Mathematics . His educational focus emphasizes formal verification, imperative programming foundations, and mathematical logic applications in computer science.
