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Magnus BenderView profile

Assistant Professor

• Artificial Intelligence
• Machine Learning
• Data Mining
• +7 more

Magnus Bender is an Assistant Professor at the Department of Programming, Logic and Intelligent Systems , part of the Department of People and Technology at Roskilde University (DK-4000 Roskilde, Denmark). He holds a Dr. rer. nat. (2024), M.Sc. (2021), and B.Sc. (2019) in Computer Science from Universität zu Lübeck. His research focuses on Artificial Intelligence in the Humanities and Law , including transformer models (BERT/GPT), text mining, legal text analysis, and ethics in AI. Recent work includes projects like DiRec: Safeguarding Diversity in News Recommendation (2022–2027) and organizing workshops such as Workshop on Humanities-Centred Artificial Intelligence (2025). He received the Best Paper Award (IEEE ICSC 2024) for work on human feedback in AI systems. Education: Dr. rer. nat. in Computer Science, Universität zu Lübeck (2024) M.Sc. in Computer Science, Universität zu Lübeck (2021) B.Sc. in Computer Science, Universität zu Lübeck (2019) External Positions: Research Associate (Postdoc) at University of Hamburg (2024–2025) Research Assistant at Universität zu Lübeck (2021–2024) His research integrates technical AI advancements with societal applications, emphasizing ethics and human-centered approaches. He actively contributes to interdisciplinary projects bridging computer science, law, and humanities.

• Logic Programming
• Computational Complexity
• Nonmonotonic Reasoning
• +4 more

Mantas Simkus is an Assistant Professor at TU Wien's Institute of Logic and Computation, affiliated with the Database and Artificial Intelligence Group. He previously held an Associate Professor position at Umeå University (Sweden) within the Wallenberg AI, Autonomous Systems and Software Program (WASP). He leads the FWF-funded project 'KtoAPP: Compiling Knowledge into Applications' and contributes to the Cluster of Excellence 'Bilateral Artificial Intelligence'. His research focuses on logic-based data management, knowledge representation, and nonmonotonic reasoning, with applications in semantic web technologies and ontology engineering. Education: Bachelor's in Computer Science from Vilnius University. Research interests include logic programming, computational complexity, description logics, and their integration with databases. He explores techniques for efficient query answering, schema validation (e.g., SHACL), and reasoning under incomplete information. His work bridges theoretical foundations (e.g., complexity analysis, formal semantics) with practical systems (e.g., ontology-mediated query processing). Key projects include 'KtoAPP' (2018–2025), investigating automated knowledge compilation, and contributions to the 'SemDat' and 'OMEGA' initiatives. He teaches courses on deductive databases and semi-structured data at TU Wien. He actively participates in academic service: co-chair of RuleML+RR 2024, editorial board member of the Artificial Intelligence journal, and former co-chair of DL 2019. His research group collaborates on topics like graph databases, answer set programming, and hybrid knowledge representation systems.

• Satisfiability Modulo Theories
• Automated Reasoning
• Formal Methods
• +3 more

Clemens Eisenhofer is a PreDoc Researcher at TU Wien's Institute of Logic and Computation within the Faculty of Informatics. His role combines doctoral research with active contributions to multiple funded projects, positioning him at the forefront of SMT solver development and formal methods research. His research centers on advancing Satisfiability Modulo Theories through innovations in bit-vector reasoning, non-classical logics, and custom theory integration. Key focus areas include enhancing Z3's capabilities for word-level operations, embedding proof calculi like connection calculus, and developing user-propagator frameworks. These efforts target practical applications in software verification, program analysis, and constraint solving, with direct implications for reliability-critical systems. Eisenhofer actively contributes to four major research initiatives: ARTIST (2021-2026) on automated reasoning foundations; SFB SPyCoDe (2023-2030) for cyber-physical systems verification; TAIGER (2023-2027) in theorem proving; and ForSmart (2023-2027) for smart contract analysis. These projects provide substantial computational resources and foster international collaborations, though he does not currently supervise students given his PreDoc status. His research operates within TU Wien's Institute of Logic and Computation—a leading European hub for formal methods—leveraging institutional expertise in computational logic and strong industry ties. The institute's collaborative environment supports his work on solver extensions while connecting theoretical advances to practical verification challenges across multiple domains.

• Software Engineering
• Cryptography
• Programming Languages
• +2 more

Christoph Hochrainer is a PreDoc Researcher at Technische Universität Wien, affiliated with the Software Engineering department. His academic role involves research in software systems and formal methods, supported by projects like ForSmart (2023–2027) and MirandaTesting (2023–2028). He completed his Diploma in automated reasoning at TU Wien in 2020. His research spans software engineering, cryptography, and programming languages, with specialized interests in fuzzing techniques, architecture description languages, and smart contract security. Recent work emphasizes zero-knowledge circuits, Solidity benchmarking, and macro systems for domain-specific tooling. Christoph's publications consistently explore automated testing and formal verification, with a trend toward practical applications in blockchain and secure software pipelines. He supervises student theses, including work on inconsistency detection in Solidity smart contracts. He contributes to collaborative projects focused on formal methods and software reliability, operating within TU Wien's research units. No scientific awards are documented.

• Graph Data Management
• RDF and Semantic Web
• Database Theory
• +3 more

Maxime Jakubowski is a PostDoc Researcher at TU Wien's Faculty of Informatics, affiliated with the Databases and Artificial Intelligence research group. Based in Room HA0320 at Favoritenstrasse 9, he can be contacted at maxime.jakubowski@tuwien.ac.at and maintains an ORCID profile (0000-0002-7420-1337). His research centers on graph data management within the Semantic Web ecosystem, specializing in RDF validation through shape constraint languages like SHACL and ShEx. He investigates formal foundations, expressiveness boundaries, and practical implementations including SQL compilation and neighborhood-based graph description. Current projects include FRESH (2021–2026), KtoAPP (2018–2025), and TARGET (2024–2028), focusing on graph data theory and implementation. Recent publications (2021–2025) demonstrate consistent contributions to RDF validation standards, with 14 articles addressing shape language formalization, compilation techniques, and provenance tracking. His work bridges theoretical database concepts with industrial applications in knowledge graph validation. Dr. Jakubowski supervises bachelor theses and teaches courses including Management of Graph Data (192.161) and Project in Computer Science. His research collaborations span international projects and the Dagstuhl Seminar 24102 on Shapes in Graph Data. He is an active member of the Databases and Artificial Intelligence research group, contributing to TU Wien's leadership in graph data management and Semantic Web technologies through both theoretical research and practical tool development.

• Programming Languages
• Category Theory
• Domain-Specific Languages
• +2 more

Nicolas Wu is a Reader (Associate Professor) of Computer Science at Imperial College London, leading the Functional Programming Research Group and serving as Senior PhD Tutor. Education: DPhil (Oxford), BS/BA (Oxford). Research applies category theory to programming language semantics, connecting domain-specific languages, algebraic effect handlers, and recursion schemes. Current work formalizes scoped effects and parameterized algebraic theories. Teaches functional programming and type theory. Supervises doctoral research on language design and formal verification.

David CarralView profile

Researcher

• Knowledge Representation
• Database Theory
• Artificial Intelligence
• +3 more

Dr. David Carral is a former Research Associate at the International Center for Computational Logic (ICCL) within the Faculty of Computer Science at TU Dresden. His work focuses on Knowledge Representation , Database Theory , and Computational Logic , particularly in the context of ontology-based data access, existential rules, and chase termination analysis. He contributed to projects like CFAED and collaborated on systems such as VLog and ROWL . David supervised theses including "Don’t Repeat Yourself: Termination of the Skolem Chase on Disjunctive Existential Rules" by Lukas Gerlach. His research bridges formal methods with practical applications in AI and database systems. Research interests include ontology design patterns , query rewritability , and efficient reasoning algorithms . He actively participated in conferences like KR and IJCAI, contributing to advancements in nonmonotonic reasoning and hyperproperties. His work integrates description logics, answer set programming, and semantic web technologies to address challenges in knowledge-based systems.

• Automata Theory
• Description Logics
• Formal Methods
• +3 more

Dr. Jan Hladik is a former Research Associate at the International Center for Computational Logic (ICCL) within the Faculty of Computer Science at TU Dresden. His research focused on automata theory, description logics, and formal methods with applications in access control and security systems. He contributed to the theoretical foundations of description logics, particularly in automata-based reasoning and complexity analysis. His work includes integrating OWL DL reasoning for RBAC systems and developing PSPACE automata for description logics. Hladik collaborated on tools like FaCT and RACER, advancing the implementation of formal logic systems. Education & Affiliations While specific educational details are not provided, his research contributions suggest advanced training in computer science and formal logic. He was affiliated with the Automata Theory research group at ICCL during his tenure. Research Contributions Hladik’s publications bridge theoretical computer science and practical applications in security, focusing on: Developing automata-based methods for PSPACE complexity in description logics Applying OWL DL reasoning to role-based access control (RBAC) Implementing formal systems like GF1- and optimizing tools for nominal reasoning Grants & Collaborations No specific grants are listed, but his work involved collaborations with institutions and participation in workshops like OWLED 2008 and DL 2003. Labs & Teams Active member of the Automata Theory group at ICCL, contributing to foundational research in computational logic.

• Artificial Intelligence
• Formal Verification
• Automated Reasoning
• +3 more

Jens Claßen is a former Visiting Scientist in the Automata Theory Research Group at the International Center for Computational Logic (ICCL), part of the Faculty of Computer Science at TU Dresden. His research focuses on formal verification of Golog programs, decidability in automated reasoning, and logic-based systems. Claßen contributed to advancing methods for verifying temporal properties (LTL) and knowledge-based actions in non-terminating programs. Research Interests: Formal Verification of Logic-Based Programs Decidability in Automated Reasoning Description Logic Applications Temporal Logic Analysis Publications highlight trends in program verification for Golog, emphasizing non-local effect actions and decidability boundaries. His work bridges theoretical logic and practical program analysis. No scientific awards are listed. Advising and grants sections remain unspecified. Claßens affiliation was with the ICCL and Automata Theory group during his tenure.

Rohit DuaView profile

Associate Professor

• Smart Embedded Sensing Systems
• Artificial Neural Networks
• Optoelectronic Sensors
• +3 more

Dr. Rohit Dua is an Associate Teaching Professor at Missouri University of Science and Technology (Missouri S&T), where he teaches in the Cooperative Engineering Program with Missouri State University. He holds a PhD and MS in Electrical Engineering from Missouri S&T and a BE in Electronics & Telecommunications from the University of Pune, India. Previously, he served as an Assistant Professor at New York Institute of Technology. His office is located at Missouri State University’s Springfield campus. Research Focus: Dr. Dua specializes in Smart Embedded Sensing Systems, Artificial Neural Networks, Optoelectronic Sensors, and their applications in biomedical/energy engineering. He actively integrates engineering education innovation into his research, developing experiential learning tools for K-12 and undergraduate students. Awards & Honors: 2023 ASEE Midwest Section Outstanding Service Award 2015 ASEE Zone III Conference: 1st Place Student Poster 2014 Missouri S&T Experiential Learning Award 2014 ASEE Midwest Section: 3rd Place Undergraduate Poster 2007 NYIT Faculty Scholars Award Educational Initiatives: He leads experiential projects including the Embedded Systems Club, FPGA-based synthesizers, K-12 logic laboratories, and microprocessor design tools. He received grants for student projects (e.g., OURE grants) and developed courses like Fun With Electronics . He frequently chairs ASEE Midwest Conference programs.

• Applied Algebraic Geometry
• Convex Geometry
• Combinatorics
• +3 more

Greg Blekherman is a Professor in the School of Mathematics at Georgia Tech. He is an associate director of the Algorithms, Combinatorics and Optimization (ACO) program and part of the NSF-Simons Southeast Center for Mathematical Biology. His research focuses on the interplay between convex and algebraic geometry, with applications to optimization and mathematical biology. Education: Ph.D., Mathematics, University of Michigan (2005) B.A., Mathematics, New York University (2000) Research Interests: Applied Algebraic Geometry and Convex Geometry Combinatorics (extremal, algebraic, probabilistic) Optimization (semidefinite programming, sums of squares) Mathematical Biology (robot locomotion, biomechanics) Recent Research Trends: His work bridges algebraic structures and geometric optimization, with recent focus on graph profiles, tropical geometry in extremal combinatorics, and convex hulls of algebraic varieties. Collaborations with robotics teams explore locomotion principles inspired by biological systems. Labs & Collaborations: Active in interdisciplinary projects with Dan Goldman's biology lab and robotics groups, applying geometric mechanics to optimize robot motion patterns.

Tobias JohnView profile

Researcher

• Knowledge Representation
• Automated Planning
• Formal Methods
• +7 more

Tobias John is a Doctoral Research Fellow in the Department of Informatics at the University of Oslo, affiliated with the Faculty of Mathematics and Natural Sciences. He is a member of the Reliable Systems and Data and Knowledge Management (DKM) research groups, and his work is supported by the EU REMARO project. His research focuses on enhancing the robustness of controllers that interact with evolving knowledge bases, particularly OWL ontologies, using formal logic and automated planning techniques. University: University of Oslo School: Faculty of Mathematics and Natural Sciences Department: Department of Informatics Research Groups: Reliable Systems, Data and Knowledge Management (DKM) Project: REMARO (EU-funded) His research interests center on knowledge representation, automated planning, formal methods, and logic in computer science. He investigates how ontologies can be integrated into planning systems to improve reasoning under uncertainty and ensure reliable behavior in dynamic environments. His work bridges theoretical computer science with practical applications in robotics and software reliability. The recent publications of Tobias John reflect a strong trend in combining ontology-based reasoning with robust planning and testing methodologies. His work spans from theoretical automata transformations to applied risk-aware planning for marine robots and mutation-based testing of knowledge graph applications. The dominant themes include ontology-mediated planning, logic-based validation, and reliability engineering in AI systems. He has not received any explicitly mentioned scientific awards. Tobias John is actively engaged in research but there is no indication of advising students or managing grants independently. His contributions are primarily through collaborative research within the REMARO project and his publications with senior researchers such as Einar Broch Johnsen, Eduard Kamburjan, and Patrick Koopmann. He is part of the Reliable Systems and Data and Knowledge Management (DKM) research groups at the University of Oslo, which focus on dependable computing, knowledge engineering, and formal verification of complex systems.

John R. SteelView profile

Professor

• Set Theory
• Mathematical Logic
• Inner Model Theory
• +3 more

John R. Steel is a Professor at the University of California, Berkeley, specializing in foundational areas of set theory, mathematical logic, and inner model theory. His research focuses on the interplay between large cardinals, determinacy axioms, and inner model constructions, contributing significantly to the understanding of core model theory, forcing axioms, and the continuum problem. He has delivered plenary lectures and tutorials at major international conferences including the European Set Theory Society meetings, the Association for Symbolic Logic annual meetings, and the Joint Mathematics Meetings. Key topics in his talks include mouse theory, hod analysis, comparison lemmas, and philosophical aspects of Gödel's program. Steel's work bridges technical set-theoretic constructions with foundational questions in mathematics, often addressing implications of determinacy axioms and large cardinal hypotheses in L(R) and beyond. His recent research explores multiverse perspectives, correctness results for extender models, and the consistency strength of AD-related principles.

• Static Analysis
• Abstract Interpretation
• Programming Languages
• +3 more

Julian Erhard is a researcher and lecturer at the Technical University of Munich (TUM), affiliated with the Chair of Languages and Description Structures in Computer Science under Prof. Helmut Seidl. His research focuses on static analysis techniques, particularly leveraging abstract interpretation to enhance precision and performance in compiler optimization and concurrency analysis. He contributes to the Goblint static analyzer and is a member of the ConVeY research training group. Erhard has organized preparatory mathematics courses and served as an exercise instructor for core computer science courses such as Functional Programming and Verification, Compiler Construction, and Static Analysis. His teaching spans multiple semesters from 2019 to 2025, emphasizing practical programming concepts and theoretical foundations. In research, he addresses challenges in context-sensitivity management, concurrency validation, and pointer analysis. His work includes developing frameworks like the digest framework for concurrency-sensitivity and tools like C-2PO for weakly relational pointer domains. Recent publications explore correctness witnesses for concurrent programs and optimizing context sensitivity dynamically. Erhard has co-organized ConVeY retreats and contributed to projects such as the Goblint validator and the Clustered relational thread-modular analysis framework. His expertise bridges theoretical advancements in abstract interpretation with practical compiler tool development.

• Modal Logic
• Coalgebra
• Automated Reasoning
• +3 more

Prof Dirk Pattinson is a Professor in the School of Computing at Australian National University (ANU). His research focuses on modal logic, coalgebraic systems, automated reasoning, and formal methods. He holds a PhD in Computer Science and has supervised numerous research students. Research interests include coalgebraic logic, non-classical modal logics, automated theorem proving, and applications in computational social choice. His work bridges theoretical foundations with practical tools like the COOL reasoner for modal fixpoint logics. Notable contributions span over 70 peer-reviewed publications since 2008, with recent work on non-iterative modal resolution calculi (2024), Hennessy-Milner properties via topological methods (2022), and formal verification of voting systems (2021). His research often integrates algebraic, categorical, and coalgebraic perspectives.