جست‌وجوی استاد و پژوهشگر

Emilio Jesús Gallego Ariasمشاهده پروفایل

پژوهشگر ارشد

• Theorem Proving
• Functional Programming
• Computer Music
• +۷ مورد دیگر

Emilio Jesús Gallego Arias is a non-tenured Research Fellow at the French National Center for Scientific Research (CNRS), hosted at the Institute of Fundamental Computer Research (IRIF) of CNRS and University of Paris Cité. He is also a member of the PiCube Inria team. Previously, he held postdoctoral positions at the University of Pennsylvania (2012–2014) and MINES ParisTech (2014–2019). His research spans mechanically-verified functional and logic programming , with a focus on the Coq proof assistant and the Mathematical Components Library . He develops tools like coq-lsp (language-server for Coq IDEs) and jsCoq (web interface), replacing earlier projects like SerAPI . His work bridges programming language theory , digital signal processing , and formal verification , particularly in the ANR FEEVER project for verifying Faust programs. His 15 most recent works (2014–2024) address type systems , differential privacy , and formal verification in domains like audio processing and mechanism design . Publications span journals (e.g., Journal of Privacy and Confidentiality), conferences (ICML, POPL, FARM), and workshops (CoqPL, UITP). He contributes to open-source projects (GitHub), including DFuzz (linear dependent types), DualQuery (privacy algorithms), and RAM (relational machine). He uses formal methods in collaborative development platforms (Gitter, GitLab) and advocates for free software and accessible audio technology .

Reynald Affeldtمشاهده پروفایل

استاد مهمان

• Formal Verification
• Coq Proof Assistant
• Monadic Equational Reasoning
• +۷ مورد دیگر

Reynald Affeldt is a Chief Senior Research Scientist at AIST (National Institute of Advanced Industrial Science and Technology, Japan) and a Visiting Professor at NAIST (Nara Institute of Science and Technology). His work focuses on formal verification of software using logic and the Coq proof-assistant, with notable contributions to monadic equational reasoning, probabilistic programming, and robotics applications. His research spans multiple domains, including Monadic effects and equational reasoning Probabilistic and nondeterministic programming Information theory and error-correcting codes 3D geometry for robotics Recent publications highlight his efforts in extending monadic reasoning with transformers and formalizing probabilistic semantics in Coq. He has contributed to various conferences, notably as a committee member for CPP and TyDe tracks, and as a program chair for APLAS-related events. His work includes applications to OCaml, imperative language semantics, and algorithm verification (e.g., n-queens, quicksort).

• GPU computing
• Parallel computing
• Domain-specific languages
• +۹ مورد دیگر

Prof. Dr.-Ing. Richard Membarth is a faculty member at Technische Hochschule Ingolstadt , where he holds the professorship for System-on-a-Chip and AI for Edge Computing. He is also affiliated with the German Research Center for Artificial Intelligence (DFKI) as a Senior Researcher and Team Leader for Compiler Technologies and High-Performance Computing, and with the Saarland University Computer Graphics Lab . His research spans GPU computing, domain-specific languages, and compilers. PhD from Friedrich-Alexander University Erlangen-Nürnberg (2013) Postgraduate diploma from Auckland University of Technology His research focuses on: Parallel computer architectures and programming models Automatic code generation for embedded to HPC systems Image processing, computer graphics, and deep learning applications Domain-specific languages for performance-portable code Recent publications highlight compiler design, GPU acceleration, and parallel algorithms. Scientific awards include the HiPEAC Paper Award (2018) and GPCE Best Paper Award (2015) . Professional roles include organizing High-Performance Graphics conferences as Treasurer (2024-2025) and Papers Chair (2020).

Earl T. Barrمشاهده پروفایل

استاد

• Software Engineering
• Program Analysis
• Automated Program Repair
• +۵ مورد دیگر

Earl T. Barr is a Professor of Software Engineering at University College London (UCL), where he heads the System Software Engineering Group and is a member of the Centre for Research on Evolution, Search and Testing (CREST). He received his Ph.D. in Computer Science from the University of California, Davis in 2009. His educational background includes: Ph.D. in Computer Science, 2009, University of California, Davis Barr's research focuses on software engineering, particularly program analysis, automated program repair, and the application of machine learning to code (AI4Code). He is renowned for his work on dual channel analysis, which examines how code combines natural language elements (in identifiers, comments, and stylistic choices) with formal programming language. His research also explores game theory applications to software development processes and how dual channel constraints can improve type inference and code understanding. His recent publications demonstrate a strong trend toward leveraging large language models for code understanding and modification, with particular emphasis on dual channel constraints and natural type inference. His work bridges traditional software engineering techniques with modern AI approaches, showing how machine learning can enhance program analysis and repair while maintaining rigorous theoretical foundations. Notable awards include: ACM SIGSOFT Distinguished Paper Award for Automated Software Transplantation (2015) ACM SIGSOFT Distinguished Paper Award for Learning Natural Coding Conventions (2014) ACM SIGSOFT Distinguished Paper Award for Collecting a Heap of Shapes (2013) Best Paper Award for TrustDavis: A Non-Exploitable Online Reputation System (2005) Barr actively supervises numerous PhD students and postdocs, with current research focusing on AI for code, software security, and program analysis. He collaborates extensively with Santanu Dash of Royal Holloway on dual channel program analysis, and they jointly supervise PhD students through the EPSRC Centre for Doctoral Training in Cyber Security for the Everyday. His work often combines theoretical rigor with practical tool development, resulting in several publicly available research tools that influence both academic research and industry practice. He leads the System Software Engineering Group at UCL, which focuses on developing novel approaches to software engineering challenges at the intersection of human and machine aspects of programming. Current research directions include dual channel analysis for vulnerability detection, game-theoretic approaches to development processes, and AI-assisted software development.

Nelly Bencomoمشاهده پروفایل

دانشیار

• Software Engineering
• Requirements Engineering
• Decision-making under Uncertainty
• +۷ مورد دیگر

Nelly Bencomo is an Associate Professor in the Department of Computer Science at Durham University in the UK, where she joined in September 2021. Previously, she was a Senior Lecturer at Aston University and has held research positions at Lancaster University and INRIA Paris. She is a leading researcher in software engineering for autonomous and self-adaptive systems, with a focus on uncertainty quantification and decision-making under uncertainty. Her research interests span Decision-making under Uncertainty, Software Engineering for Autonomous and Self-adaptive Systems, Bayesian Inference and Machine Learning, Requirements Engineering, Model-Driven Engineering, and runtime models. She has pioneered concepts like models@run.time and requirements@run.time, exploring how systems can maintain awareness of their requirements and models during operation. Her work increasingly addresses AI ethics, human values in software, and responsible AI. Her recent publications (2021-2025) reveal a strong focus on uncertainty representation and management in adaptive systems, with growing attention to explainability, digital twins, and LLM applications in software engineering. Her work bridges theoretical foundations with practical applications in healthcare, education, and sustainable systems. Best Paper Award at International Conference on Engineering Digital Twins 2024 (EDTconf'24) Best Software Artefact at Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS'24) Listed in Women for Innovation in Health Science in the North of England 10-year Most Influential Paper Awards 2019 for seminal work in self-adaptive systems Best Paper Award REFSQ 2013 Nelly has successfully supervised multiple PhD students to completion and currently mentors several postgraduate researchers. She leads the EPSRC-funded Twenty20Insight project and the Leverhulme Fellowship QuantUn, focusing on uncertainty quantification using Bayesian surprises. Her research portfolio includes significant contributions to European projects and UK research councils in the area of self-adaptive and autonomous systems. She is also involved in the Leverhulme Centre for Algorithmic Life as Project Lead in the Department of Computer Science and leads the Durham Strategic Research Fund project JusTN0W.

Marsha Chechikمشاهده پروفایل

استاد

• Software Engineering
• Formal Methods
• Software Specification and Verification
• +۷ مورد دیگر

Marsha Chechik is a Professor in the Department of Computer Science at the University of Toronto within the Faculty of Arts and Science. She previously served as Chair of the Department of Computer Science (2019-2022) and as Acting Dean in the Faculty of Information (July-December 2022). Professor Chechik received her Ph.D. from the University of Maryland in 1996 and has established herself as a leading researcher in software engineering with a focus on formal methods. Her research interests include software safety and security, automated verification, software product lines, and model management. Professor Chechik has authored numerous papers in formal methods, software specification and verification, computer safety and security, and requirements engineering. Her work has evolved to incorporate newer areas such as machine vision reliability analysis, normative requirements with large language models, and machine learning development lifecycle analysis. Her research consistently bridges theoretical foundations with practical applications in software engineering. Professor Chechik has served in numerous leadership roles including Program Committee Co-Chair for major conferences such as ICSE 2018, TACAS 2016, VSTTE 2016, ASE 2014, CONCUR 2008, CASCON 2008, and FASE 2009. She is currently the Area Chair for ASE 2025 in Security and Other Non-Functional Properties. She has also served as Associate Editor in Chief of Journal on Software and Systems Modeling and as associate editor of IEEE Transactions on Software Engineering (2003-2007, 2010-2013). Best paper award at RE'12 (2012) SIGSOFT Distinguished Paper at ICSE'12 (2012) Winner of Best Student Paper Award at CASCON'07 (2007) Winner of Distinguished Paper Award at ICSE'07 (2007) Professor Chechik regularly mentors PhD students, with notable advisees including Michalis Famelis, Shiva Nejati, Jocelyn Simmonds, Ou Wei, and Aws Albarghouthi. Her advising philosophy emphasizes rigorous formal methods while addressing practical software engineering challenges. She has been involved in numerous research grants focusing on software verification, safety-critical systems, and requirements engineering. Currently, her work explores the intersection of formal methods with emerging technologies like large language models and machine vision systems. Professor Chechik maintains an active research lab focused on model-based software engineering, with projects spanning software product lines, model management, and verification techniques. Her team collaborates with industry partners to address real-world software engineering challenges while advancing theoretical foundations. Current work includes developing techniques for normative requirements operationalization, machine vision reliability analysis, and automated code reconciliation using AI techniques.

• Social Media
• Public Relations
• Corporate Communication
• +۱۵ مورد دیگر

Christian Möller serves as Senior Lecturer at Kiel University of Applied Sciences since 2010 and Professor of Corporate Communication at Berlin School of Media, Communication and Business (HMKW) since 2019. He heads the Institute for Applied Journalism (ifap), co-founded cultural initiative kultursphäre.sh, and holds regulatory roles as auditor at Freiwillige Selbstkontrolle Fernsehen (FSF) and member of Germany's Commission for Public Broadcasters' Financial Requirements (KEF) since 2018. His academic foundation includes a doctorate in media studies from Christian-Albrechts-University of Kiel, complemented by studies in modern German literature, German studies, and public law. Prior professional experience spans diplomatic service as US Consulate Press Spokesman in Hamburg (2008-2010) and OSCE media freedom advocacy in Vienna (2002-2008). Möller's research critically examines digital transformation's impact on communication ecosystems, with core expertise in social media governance, corporate communication ethics, and journalism's evolving role. His work consistently addresses tensions between regulatory frameworks and creative freedom, particularly regarding internet governance and media economics in European contexts. Current investigations focus on mobile journalism innovations and cultural marketing's societal implications. Publication analysis reveals a 15-year trajectory centered on OSCE-regional media freedom, internet policy development, and journalism system transformation. Key thematic clusters include multistakeholder governance models (2004-2013), European digital policy challenges (2018), and UN-level internet freedom frameworks (2019). His scholarship uniquely bridges diplomatic practice with academic rigor, emphasizing practical implementation of regulatory standards. Through ifap, Möller directs applied research on contemporary journalism practices while leveraging kultursphäre.sh to explore cultural communication intersections. His regulatory engagements at KEF/FSF provide real-world testing grounds for theoretical frameworks developed in corporate communication and media ethics scholarship.

Carl Coreaمشاهده پروفایل

پژوهشگر

• Business Informatics
• Theoretical Informatics
• Artificial Intelligence
• +۳ مورد دیگر

Dr. Carl Corea is a postdoctoral researcher at the University of Koblenz-Landau, Germany, affiliated with the Process Science Group within the Department of Computer Science. He holds a PhD in Computer Science (with distinction, 2020) and has served in roles such as Acting Professor of Business Information Systems (2023/24) at Justus Liebig University Giessen and Visiting Researcher at SAP Signavio. His research bridges business informatics and theoretical computer science, focusing on process mining, declarative process specifications, and decision modeling (DMN). He actively contributes to academic leadership roles, including memberships on doctoral committees, examination boards, and interdisciplinary research centers at the University of Koblenz. Corea's research interests include business process management, artificial intelligence applications in processes, and inconsistency measurement in business rules and process models. He has delivered courses on AI in Accounting, Project Management, and Business Process Management at multiple institutions. His work has been recognized with awards such as the Best Paper Award at WI 2019 and the Debeka Innovationspreis for research projects like 'Predictive Process Monitoring'. He serves on the program committees of major conferences in AI and business process management, including KR, AAAI, BPM, and ECAI. His publications span topics like declarative process modeling, DMN verification, and carbon-aware process execution. Corea also chairs Minitracks at events like HICSS and oversees conference organization for tracks such as Business Process Technology. Education: PhD in Computer Science (2020, with distinction) Awards: Multiple research and teaching awards, including nominations for early-career recognition Administration: Member of doctoral committees, academic boards, and interdisciplinary research centers Grants: DAAD Fellowship for international conference participation (2020)

Benjamin Kaminskiمشاهده پروفایل

استاد

• Formal Verification
• Probabilistic Programs
• Quantitative Verification
• +۱۲ مورد دیگر

Benjamin Kaminski is a Professor at Saarland University and a Lecturer at University College London, where he contributes to the field of computer science with a strong emphasis on formal verification and logic. He is currently the Head of the Examination Board for the B.Sc. in Computer Science (English) program at Saarland University and actively supervises PhD, Master’s, and Bachelor’s students in research projects related to logic and verification. His research centers on the quantitative aspects of formal program verification , particularly in probabilistic and quantum programs. Key interests include weakest-precondition reasoning, expected runtimes, incorrectness logic, and the integration of machine learning with formal methods. He advocates for explainable verification and explores non-classical models such as weighted programming. His recent publications reflect a consistent focus on probabilistic semantics , runtime analysis , and deductive verification of programs, utilizing formal logic and mathematical structures to ensure correctness and efficiency. These works span high-impact venues such as POPL, LICS, and JACM. Ackermann Award for outstanding dissertations 2020 Distinguished Paper at POPL 2021 Best Paper Award at LOPSTR 2020 EATCS Best Paper Award at ESOP 2016 Borchers Badge for doctoral distinction 2019 Best scientific production award at Université Paris-Saclay 2022 Benjamin Kaminski has advised numerous students at various levels, including current PhD candidates Tobias Gürtler, Lena Verscht, Anran Wang, and Linpeng Zhang. He has served on program committees for top conferences such as POPL, CAV, LICS, and ICALP, and has reviewed for prestigious journals including Journal of the ACM and TOPLAS . He has also evaluated research proposals for the Israel Science Foundation and Czech Science Foundation, highlighting his role in shaping global research agendas. His editorial work includes contributions to Foundations of Programming and Software Systems (2019). He is actively involved in the formal methods research community, contributing to workshops and symposia on static analysis, dependable software engineering, and quantitative evaluation of systems. His leadership in organizing and reviewing for major conferences underscores his influence in theoretical computer science.

Eric Grosseمشاهده پروفایل

استادیار

• Operations Management
• Digital Transformation
• Human Factors in Logistics
• +۱۲ مورد دیگر

Eric Grosse is a Junior Professor for Business Administration, especially Digital Transformation in Operations Management, at Saarland University, Faculty of Humanities and Social Sciences. His research focuses on integrating human factors—such as ergonomics, fatigue, learning, and behavior—into decision models for logistics and production systems. He leads several interdisciplinary research projects including Human-Centric Production and Logistics, Models for an Active Aging Workforce, and Behavioral Order Picking. University: Saarland University School: Faculty of Humanities and Social Sciences Department: Junior Professorship for Business Administration, especially Digital Transformation in Operations Management Academic Rank: Assistant Professor Email: eric.grosse@uni-saarland.de His research interests include Operations Management, Digital Transformation, Human Factors in Logistics, Ergonomics in Warehousing, Behavioral Operations, and Sustainable Logistics. His work emphasizes human-centered design in warehousing and production, aiming to balance economic efficiency with worker well-being. He develops optimization models that simultaneously minimize costs and physical strain, and explores how learning, incentives, and fatigue affect order picking performance. The analysis of his recent publications reveals a consistent focus on integrating ergonomic and economic objectives in manual materials handling and order picking. Key themes include storage assignment optimization, workforce scheduling with ergonomic constraints, human-robot collaboration, and the impact of worker behavior and fatigue on system performance. His methodologies often combine mathematical modeling, simulation, and empirical validation through case studies and experiments. Eric Grosse actively collaborates with researchers from institutions such as TU Darmstadt and has published in top-tier journals like the International Journal of Production Research, Computers & Industrial Engineering, and International Journal of Operations & Production Management. His work supports warehouse managers in improving working conditions while maintaining operational efficiency. Human-Centric Production and Logistics System Design Models and Methods for an Active Aging Workforce Behavioral Order Picking Green Warehousing Supply Chain Resilience Warehousing 4.0/5.0 Digital Transformation Coaching He advises and co-supervises research with a team of collaborators and has contributed to the development of assessment tools like the Warehouse Error Prevention (WEP) tool. His research is funded by the German Federal Ministry for Economic Affairs and Energy, indicating active grant involvement. Though no formal students are listed, his co-authored papers suggest mentorship of junior researchers. He has no listed scientific awards in the provided text.

• Formal Methods
• Software Engineering
• Programming Languages
• +۱۳ مورد دیگر

Michael Leuschel is a Professor in the Institute of Computer Science at Heinrich-Heine-Universität Düsseldorf, Faculty of Mathematics and Natural Sciences. He leads research in formal methods, programming languages, and software engineering, with a focus on the development and application of the ProB model checker and constraint solver. He is co-founder of Formal Mind and scientific advisor to Nobreach, and actively contributes to the formal methods community through editorial and organizational roles. His research interests include formal verification, model checking, logic programming, partial evaluation, and the B and Event-B methods. He has pioneered techniques for animating and validating formal models, with applications in safety-critical systems such as railway operations. His work bridges theoretical foundations with industrial practice, enabling rigorous software construction. The recent publications highlight a strong trend in applying formal methods to AI safety, particularly in railway systems (e.g., KI-LOK project), integrating reinforcement learning with safety shields, and validating AI-based components. Other themes include interactive simulation, domain-specific validation documents, and the use of ProB for TLA+ and railML. The work combines theoretical advances in model checking with practical tool development. Michael Leuschel has supervised numerous students and collaborators, including Jens Bendisposto, Sebastian Krings, Philipp Körner, and Joshua Schmidt. He has been involved in significant research grants and projects, such as KI-LOK and the development of ProB, often in collaboration with industry and other academic institutions. His work has led to the creation of widely used tools and methodologies in formal methods. He is a key member of the Software Engineering and Programming Languages research group. His team develops and maintains ProB, works on integrating formal models into applications, and explores new frontiers in AI validation using formal techniques. The group is active in both theoretical research and practical tool building.

• Answer Set Programming
• Logic Programming
• Knowledge Representation
• +۷ مورد دیگر

Mario Alviano is a Professor at the University of Calabria's Department of Computer Engineering, Modeling, Electronics and Systems (DIMES) in Rende, Italy. With a prolific publication record spanning from 2008 to 2025, he has established himself as a leading researcher in Answer Set Programming (ASP), logic programming, and knowledge representation. His work bridges theoretical foundations with practical applications across diverse domains including cybersecurity, environmental monitoring, and explainable AI. Alviano's research focuses on advancing the theoretical understanding and practical applications of Answer Set Programming. His key contributions include developing ASP Chef, a visualization and development framework for ASP; advancing theoretical foundations of conditional reasoning and typicality in weighted knowledge bases; and creating bridges between neural networks and symbolic AI through preferential interpretations. His recent work explores temporal extensions to conditional logics, applications of ASP to digital twin visualization, and tools for improving explainability in AI systems. Alviano's publications consistently appear in top-tier venues including ICLP, LPNMR, JELIA, and Theory and Practice of Logic Programming. His research demonstrates strong trends toward practical applications of theoretical advances, with increasing focus on explainability, visualization, and real-world problem solving. The recent surge in publications (26 in 2024 alone) indicates significant ongoing research activity and leadership in the field. His work increasingly integrates ASP with other AI paradigms, particularly neural networks, to create more interpretable and robust AI systems. Alviano has made substantial contributions to the development of tools and frameworks that lower barriers to entry for ASP, most notably ASP Chef which provides visualization capabilities for complex logic programs. His work on Hashcash Tree demonstrates applications to security problems, while his research on marketplace logistics shows practical business applications of declarative programming. His collaborative network is extensive, with frequent co-authorship with researchers including Wolfgang Faber, Nicola Leone, Francesco Ricca, Carmine Dodaro, Laura Giordano, and Daniele Theseider Dupré, reflecting strong connections across European AI research institutions. Alviano has also organized workshops including multiple editions of Datalog 2.0, demonstrating leadership in the logic programming community.

• Artificial Intelligence
• Knowledge Representation
• Constraint Answer Set Programming
• +۴ مورد دیگر

Dr. Yuliya Lierler is a Professor in the Department of Computer Science at the University of Nebraska Omaha's College of Information Science & Technology. She has been a faculty member since 2012, reaching the rank of full professor, and was appointed to the Cheryl Prewett Diamond Professorship in 2020. Her work focuses on artificial intelligence, particularly in knowledge representation, automated reasoning, and declarative problem solving. PhD in Computer Science (University of Texas at Austin, 2010) Dr. Lierler's research bridges logic programming with practical AI applications, including natural language understanding, constraint satisfaction, and SMT-based solvers. She is a co-director of the NLPKR lab and has authored over 70 peer-reviewed publications in venues like Artificial Intelligence Journal and AAAI. Her contributions include open-access textbooks and tools like text2alm for semantic information extraction. Her recent publications explore advancements in answer set programming (ASP) semantics, automated reasoning frameworks, and hybrid knowledge representation systems. She has served as program co-chair for major conferences like ICLP (2022) and PADL (2017), and received awards such as the IS&T Outstanding Research Award (2024). Dr. Lierler also mentors students and leads initiatives in teaching innovation through online education and professional development programs. Mentor of the Year Award, Aksarben Foundation (2025) IS&T Outstanding Research and Creativity Award (2024) Best Student Paper Award (with Amelia Harrison, 2016) Dr. Lierler contributes to academic service through leadership roles in international conferences and program committees. Her lab, NLPKR, focuses on integrating natural language processing with formal logic, while her teaching emphasizes formal methods and AI foundations.

• Data Management Systems
• Database Systems
• Operating Systems
• +۴ مورد دیگر

Prof. Jana Giceva Makreshanska is a Professor of Database Systems at the Technical University of Munich (TUM), affiliated with the TUM School of Computation, Information and Technology and the Department of Computer Science. Her research focuses on systems support for data management, leveraging modern hardware architectures including operating systems, compilers, and computer architecture. She holds a PhD from ETH Zurich (2017) and previously served as faculty at Imperial College London. Notable awards include the ERC Starting Grant (2024), VMware Early Career Faculty Award (2019), and ETH Medal (2018). Education: PhD in Computer Science, ETH Zurich (2017) Research roles at Microsoft Research and Oracle Labs Research Interests: Her work addresses holistic system design challenges in data management, including optimizing query processing for modern hardware, compiler integration, and emerging architectures like chiplets. She explores efficient data processing techniques for big data and transactional systems. Recent Contributions: Her recent work includes innovations in disaggregated systems (HotOS 2023), chiplet-aware scheduling (2025), and universal graph data structures (VLDB 2022). Her publications span topics like NVMe array optimization, FPGA-based partitioning, and hybrid OLTP/OLAP systems. Awards: ERC Starting Grant (2024) Best Paper Runner-Up at VLDB 2022 ACM SIGMOD Highlights Award (2023) Teaching & Service: Current courses include 'Cloud-Based Data Processing' and 'Data Processing on Modern Hardware'. She chairs diversity initiatives at SoCC 2023, serves on program committees for OSDI, VLDB, and SIGMOD, and leads gender equality efforts at TUM. Labs/Teams: Maintains the Lehrstuhl III (I3) database systems group at TUM, collaborating on projects like LakeVilla and ARCAS.

Fabio Papacchiniمشاهده پروفایل

مدرس ارشد

• Non-classical Logics
• Automated Theorem Proving
• Knowledge Representation and Reasoning
• +۱۲ مورد دیگر

Dr. Fabio Papacchini is a Senior Lecturer in Computer Science at Lancaster University Leipzig, affiliated with the School of Computing and Communications and research groups Security Lancaster (Systems and Software Security). He holds a PhD from the University of Manchester, where he was awarded a Doctoral Prize Fellowship, and previously conducted research at the University of Liverpool on projects involving robotics, artificial intelligence, and software systems for nuclear and offshore energy applications. His research centers on non-classical logics in computer science, with key interests in model theory, automated theorem proving, knowledge representation and reasoning, ontological reasoning, and formal verification. He has made significant contributions to modal logic, spatial logics, and ontology-mediated querying, particularly through reduction techniques and finite model analysis. The recent publications highlight a strong trend in logical foundations for AI and formal methods, focusing on efficient translations in modal logic, runtime verification of multi-agent systems, and integration of formal techniques with robotics and autonomous systems. His work bridges theoretical logic with practical applications in safety-critical domains. Doctoral Prize Fellowship, University of Manchester Dr. Papacchini has collaborated extensively with researchers such as Ullrich Hustadt, Clare Dixon, Cláudia Nalon, Michael Fisher, and Alessandro Ferrando. While no direct mention of student advising or grants is found, his active publication record and leadership in research projects suggest significant involvement in mentoring and collaborative research. He is associated with formal verification of autonomous systems and has explored applications in robot inspection and battery health management. He has contributed to the development of declarative languages for agent platforms and has participated in the Multi-Agent Programming Contest, showcasing applied work in automated planning and agent coordination.