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Balder ten CateView profile

Associate Professor

• Logic in computer science
• Data management
• Knowledge representation
• +5 more

Balder ten Cate is an Associate Professor at the University of Amsterdam, where he leads the Theoretical Computer Science research unit within the Institute for Logic, Language and Computation (ILLC). His academic journey includes previous positions at INRIA, UC Santa Cruz, Stanford, LogicBlox, and Google. He maintains active collaborations across institutions including the University of Bergen (co-advising PhD students) and Tsinghua University. Primary Affiliation: Theoretical Computer Science (TCS) Secondary Affiliation: Mathematical & Computational Logic (MCL) Office: Room L6.38, LAB42, Science Park 900, Amsterdam Dr. ten Cate's research spans diverse applications of logic in computer science and AI, with particular emphasis on data management, knowledge representation, and machine learning. His work bridges theoretical foundations with practical applications, focusing on how logical frameworks can enhance data systems and AI capabilities. He has developed significant contributions in finite model theory, database theory, and computational learning theory, with recent work exploring connections between universal algebra and learning theory. His publication record shows a strong trajectory in theoretical computer science, with recent papers focusing on query algorithms, interpolation in logical fragments, and the learnability of database queries. The research demonstrates consistent contributions at top venues including PODS, ICDT, IJCAI, and ACM Transactions journals. His work on 'Extremal Fitting Problems for Conjunctive Queries' received the ACM PODS 2023 Best Paper Award, while 'SAT-Based PAC Learning of Description Logic Concepts' earned an IJCAI 2023 Distinguished Paper Award. 2024 ETAPS Best Paper Nomination 2023 ACM SIGMOD Research Highlights Award 2023 Alberto Mendelzon Test-of-Time Award ICDT 2012 Best Paper Award 2006 EACSL Ackermann Prize for best dissertation Dr. ten Cate actively supervises PhD and MSc students, with recent theses covering topics like modal formula characterization, conjunctive queries, and temporal logic. He serves on numerous program committees including PODS 2025 and ICALP 2024, and has organized workshops on learning and logic. His current MSCA European Re-Integration Fellowship 'LLAMA: Logic and Learning: an Algebra and Finite Model Theory Approach' (2021-2025) demonstrates ongoing research leadership. He also contributes to academic service through committee memberships including the ASL Committee on Education and the editorial board of the Journal of Logic, Language and Information.

• Enterprise Modeling
• Cybersecurity
• Multi-Level Modeling
• +5 more

Manfred Jeusfeld is a Professor of Information Technology at the University of Skövde's School of Informatics, Department of Information Technology. He specializes in enterprise modeling, cybersecurity, multi-level modeling, and critical infrastructure protection. His research integrates formal methodologies with practical applications in domains like product lifecycle management and data warehouse architecture. Research Interests: Multi-Level Modeling (formal semantics, tool implementation) Cybersecurity in Critical Infrastructures (model-based analysis, vulnerability assessment) Conceptual Modeling Methodologies (enterprise architecture, ontological frameworks) Product Lifecycle Management (virtual factories, extended PLM systems) Key Projects: Leading the Virtual Factories of the Future (VF-KDO) research profile (2018–2026) ELVIRA project (EU ISF-funded cybersecurity analysis for smart grids) OMI project (teaching enterprise modeling tools for European education) Publications: Recent work emphasizes systematic literature reviews in cybersecurity modeling, formal verification of multi-level systems, and tool contributions like DeepTelos for ConceptBase. His work bridges theoretical model development with real-world applications in critical infrastructure protection.

• Natural Products
• Metabolomics
• Biodiversity Conservation
• +4 more

David Bruno is a Professor at the University of Burgundy, affiliated with the SAMBA research team. His work focuses on natural products discovery, metabolomics, and biodiversity conservation, with significant contributions to structural novelty identification in plant extracts and chemotaxonomic digitization. He leads initiatives like the INVENTA workflow and plantMASST community-driven projects. His research integrates computational frameworks with experimental data to address global challenges such as deep-sea mining policy, antimicrobial resistance, and pandemic emergence. Bruno has authored over 50 publications, emphasizing open science and collaborative research. He serves as a key figure in the SAMBA group, driving advancements in biogeosciences and marine biology. Research interests include chemical ecology of marine organisms, metabolomic profiling of plant biodiversity, and policy frameworks for genetic resource access (ABS). His work spans drug discovery (e.g., antiparasitics, anti-mycobacterial agents) and environmental policy, with a focus on Antarctic marine biodiversity and climate change impacts. Bruno’s interdisciplinary approach bridges chemistry, ecology, and computational biology to advance sustainable solutions. Notable contributions include the development of analytical tools for metabolite annotation, species distribution modeling in sub-Antarctic ecosystems, and leadership in international collaborations like the vERSO project. His lab’s infrastructure supports large-scale metabolomic studies and open-access data repositories.

• Bioinformatics
• Text Mining
• Machine Learning Applications in Biomedical Research
• +4 more

Patrick Ruch is a Professor at the Geneva School of Economics and Management (HES-SO), specializing in bioinformatics, text mining, and computational methods for health sciences. He leads research in areas such as machine learning applications in biomedical research, research data management, and natural language processing for scientific literature triage. His work emphasizes improving reproducibility, equity in publishing, and the integration of AI in healthcare. Key affiliations include the SIB Swiss Institute of Bioinformatics and the ArODES initiative. Research interests focus on leveraging AI to enhance data-driven decision-making in medicine, addressing systemic biases in academic publishing, and developing tools for genomic variant curation. He has collaborated extensively on international projects like BiCIKL and DOME, advancing FAIR data principles and open science practices.

Dmitriy TraytelView profile

Associate Professor

• Interactive Theorem Proving
• Runtime Verification
• Logic
• +11 more

Dmitriy Traytel is an Associate Professor at the Department of Computer Science (DIKU), Faculty of Science, University of Copenhagen, where he leads the Software, Data, People & Society (SDPS) section. He earned his PhD from TU München under the supervision of Tobias Nipkow in 2015 and previously held a senior researcher position at ETH Zürich's Information Security Group. His primary research interests include interactive theorem proving, runtime verification, logic, automata, decision procedures, and coinduction. He works extensively with the Isabelle/HOL proof assistant, developing foundational theories and verified tools. His work bridges theoretical logic and practical system verification, focusing on correctness, expressiveness, and scalability. The recent publications highlight a strong focus on verified runtime monitoring, formalization of logical systems, and efficient query evaluation. Key themes include the development of formally verified monitoring tools (e.g., TimelyMon, WhyMon, VeriMon), foundational work on corecursion and datatypes in Isabelle, and translations of logical formalisms into executable and verifiable code. Several publications have received distinguished paper awards, indicating high impact in the programming languages and verification communities. Distinguished Paper Award, POPL 2025: 'Barendregt Convenes with Knaster and Tarski: Strong Rule Induction for Syntax with Bindings' Distinguished Paper Award, POPL 2023: 'Admissible Types-to-PERs Relativization in Higher-Order Logic' Distinguished Paper Award, ATVA 2018: 'Optimal Proofs for Linear Temporal Logic on Lasso Words' Best Student Paper Award, FSCD 2016: 'Formal Languages, Formally and Coinductively' Traytel has (co)supervised numerous PhD, MSc, and BSc students, many of whose projects contribute directly to his research agenda in verified systems and formal methods. He is actively involved in the academic community, serving on program committees for POPL, ITP, RV, and CPP, and has chaired conferences such as CPP 2023 and 2024. His tools, including TimelyMon, VeriMon, and WhyMon, are practical outcomes of his research, enabling scalable, explainable, and trustworthy runtime verification. He leads a research group focused on trustworthy stream processing, distributed streaming computations, and explainable monitoring. His work often involves collaboration with researchers at ETH Zürich and other institutions, particularly in the areas of security and monitoring.

Karolina RatajView profile

Assistant Professor

• Psycholinguistics
• Neurolinguistics
• Semantic Processing
• +9 more

Karolina Rataj is an Assistant Professor at the Faculty of English, Adam Mickiewicz University in Poznań, where she also serves as Head of the Neuroscience of Language Laboratory and Coordinator of the M.A. Programme in Applied Cognitive Linguistics. She has been involved in significant research projects funded by the National Science Center and the National Centre for Research and Development, and previously held a postdoctoral researcher position at the University of Twente, Netherlands. Her research focuses on psycholinguistics, neurolinguistics, and cognitive neuroscience, particularly in the areas of figurative language comprehension (metaphor, irony, similes), semantic processing in monolingual and bilingual contexts, and electrophysiological methods such as ERPs and EEG. She investigates language processing in both healthy individuals and clinical populations, including those with schizophrenia and aphasia. Her recent publications reveal a strong trend in experimental neurocognitive research, employing ERP components like N400, P200, and LPC to decode semantic integration, metaphor comprehension, and creative cognition. Her work frequently compares native and non-native language processing, shedding light on the cognitive effort involved in bilingualism. AMU Rector's Award for organisational achievements (2013) AMU Rector's Award for organisational achievements (2017) AMU Rector’s Scientific Award for publications (2019) She has advised and collaborated on multiple research projects and grants, including the OPUS 13 project on semantic inhibition and an NCN-funded study on novel metaphoric comprehension in bilinguals. She is actively involved in academic service, serving as Deputy Chair of the Human Research Ethics Committee at AMU and as a peer reviewer for journals such as Frontiers in Psychology , Bilingualism: Language and Cognition , and Biological Psychology . Karolina Rataj leads the Neuroscience of Language Laboratory at AMU, which specializes in EEG studies of language and cognition, and she has conducted training in neuroimaging, TMS, and ERP analysis at institutions in Poland, Germany, and the Netherlands.

Patrick McInerneyView profile

Lecturer

• Photogrammetry
• 3D Modelling
• Lighting/Rendering
• +9 more

Patrick McInerney is a Lecturer at South East Technological University (SETU) , Waterford, Ireland, affiliated with the Department of Computing and Mathematics and the Centre for Information Systems and Techno-culture. His research focuses on photogrammetry, 3D modeling, computational photography, and semantic technologies for digital cultural heritage and human-machine symbiosis. Education: BSc (Hons) in Industrial Computing; Postgraduate Diploma in Sociology (The Open University) Research Interests: Metrology-based documentation of cultural heritage, semantic web applications for street art archiving, and human-centered machine learning in digital humanities. His work bridges computer science, visual arts, and social sciences. Key Collaborations: Leads the MementoArtem Digital Street Art Archive project, collaborating with SETU Library, INSYTE-Cooley research group, and external partners. His research aligns with the UN Sustainable Development Goal of Quality Education through digital preservation. Professional Affiliations: Member of CIPA Heritage Documentation, ICOMOS, and IFAC. Active in the Technology, Culture and International Stability (TECIS) committee.

Susanne FeistelView profile

Researcher

• Research Data Management
• Marine Data Science
• Data Curation
• +3 more

Dr. Susanne Feistel is a Researcher at the Leibniz Institute for Baltic Sea Research (IOW) in Warnemünde, Germany, affiliated with the IT & Data Management department under the Directorate. She holds a Dr. rer. nat. from Ludwig Maximilian University of Munich (2012) and a Dipl. Biol. from the University of Rostock (2004). Her research focuses on marine data management systems, with specialization in research data curation, metadata frameworks (notably IOWMETA), and oceanographic database development (IOWDB/ODIN2). Key domains include: Research data lifecycle management for marine science Baltic Sea hydrographic and hydrochemical data analysis Data provenance and reproducibility frameworks Development of FAIR data standards for ocean research Her publications demonstrate consistent focus on marine data systems, with recent work emphasizing standardized data management practices for large-scale research collaborations, geospatial analysis of Baltic Sea conditions, and reproducible data workflows. Publications show strong thematic clustering around metadata systems, hydrographic assessment methodologies, and research data governance. As Data Steward, she contributes to institutional and national research data management strategies, including DAM (German Marine Research Alliance) initiatives. No awards or student supervision information was found in the source materials.

Maria-Esther VidalView profile

Professor

• Data Science
• Semantic Web
• Knowledge Graphs
• +7 more

Prof. Dr. Maria-Esther Vidal is the head of the Scientific Data Management Research Group at Technische Informationsbibliothek (TIB) , a member of the L3S Research Centre at Leibniz Universität Hannover, and a full professor (on-leave) at Universidad Simón Bolívar, Venezuela. She lectures Master courses at the Faculty of Electrical Engineering and Computer Science, Leibniz Universität Hannover.

• Program Verification
• Programming Language Design
• Logic
• +6 more

Neelakantan R. Krishnaswami is a Professor of Computer Science at the University of Cambridge, affiliated with the Computer Laboratory and a Fellow of Trinity College . His research focuses on program verification, programming language design, and the intersection of logic, semantics, and type theory. PhD in Computer Science from Carnegie Mellon University (2011) His work addresses foundational challenges in programming languages, including refinement type systems with explicit proofs, deterministic parsing with fused lexing, and verification of systems code using separation logic. He has also contributed to bidirectional typechecking, higher-order reactive programming, and logical models for concurrency. Recent publications highlight trends in refinement types with explicit proof terms, parser combinator optimization, and formal verification of C and WebAssembly code. These works span type theory, denotational semantics, and practical compiler design. Distinguished Paper Award, POPL 2020 Distinguished Paper Award, PLDI 2019 He has collaborated extensively on projects involving functional reactive programming, logical relations, and substructural type systems. His contributions include the design of the flap parser library and the Datafun language, which extends Datalog with higher-order features.

• Filesystems
• High Performance Computing
• Distributed Storage
• +4 more

Ramnatthan Alagappan is an Assistant Professor at the Siebel School of Computing and Data Science, University of Illinois. His research focuses on distributed systems, storage systems, and fault tolerance in modern datacenter environments. He leads projects investigating high-performance storage abstractions, replication strategies, and reliability engineering for distributed infrastructure. Key research areas include filesystem design, crash consistency mechanisms, and optimizing storage hierarchies for hybrid NVM environments. His work emphasizes practical implementations of theoretical models, such as the LazyLog shared log abstraction and IONIA replication framework for disk-based key-value stores. Alagappan has received the NSF CAREER Award (2024) for his research on datacenter-aware storage systems. His recent publications address challenges in disaggregated datacenters, fault tolerance for modern workloads, and automated reliability testing for cluster management systems. He collaborates extensively on projects involving distributed storage protocols, log-based systems, and performance optimization for large-scale infrastructures. His research spans theoretical contributions (e.g., consistency models) to applied systems work (e.g., implementing fault-tolerant storage stacks), with a focus on bridging gaps between hardware capabilities and software system design.

Roberto YusView profile

Assistant Professor

• Data Management
• Knowledge Representation
• Privacy
• +7 more

Roberto Yus is an Assistant Professor in the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County (UMBC). He leads the DAta Management & Semantics (DAMS) Research Group and previously served as a Postdoctoral Researcher at the University of California, Irvine (UCI). Education: Ph.D. in Computer Science (University of Zaragoza, 2016), M.S. (2011), and B.S. (2010) in Computer Science from the same institution. Research Interests: Focuses on semantic data management in IoT environments, privacy-preserving systems, smart buildings, and water systems. His work includes developing frameworks like PRIVACYLENS, SMARTSPEC, and SEMIOTIC to bridge IoT device interactions with user requirements and privacy preferences. Publications & Projects: Over 30 peer-reviewed articles in top conferences/journals (e.g., VLDB, PerCom). Projects include TIPPERS (privacy-preserving middleware), Co-zyBench (thermal comfort benchmarking), and GenAIPABench (AI privacy assistants). Awards: Mark Weiser Best Paper Award (2022), 2nd place INCS-CoE Sandpit Challenge (2022), FPI Fellowship (2011-2015). Advising: Mentors Ph.D., MS, and undergraduate students in IoT, privacy, and data management. Grants: $40K INCS-CoE Seed Funding (2022), NSF S&CC grants, and Spanish Ministry grants totaling $31K in mobility support. Labs & Teams: Leads the DAMS Group at UMBC and collaborates with researchers at UCI, Telecom SudParis, and international institutions. Active in IEEE and ACM conferences, editorial roles for Sensors and Frontiers in Big Data .

Farshad FotouhiView profile

Professor

• Biomedical Informatics
• Semantic Web
• Multimedia Databases
• +2 more

Farshad Fotouhi serves as Professor and Interim Chair of Computer Science at Wayne State University's College of Engineering. With a PhD from Michigan State University (1988), he leads research in biomedical informatics, semantic web technologies, and multimedia systems. His work develops AI-driven solutions for medical diagnosis, recommendation systems, and robotic navigation. Recent innovations include COVID-19 detection from X-rays using ensemble learning, cold-start solutions for recommender systems, and SLAM algorithms for dynamic environments. Fotouhi has graduated over 30 PhD students and has received research funding from NSF, NIH, and Ford Motor Company. His teaching includes theoretical computer science and automata theory courses.

Rob MaloufView profile

Professor

• Computational Linguistics
• Morphological Theory
• Statistical NLP
• +3 more

Professor and Chair of Linguistics at San Diego State University with adjunct appointment in Big Data Analytics. Research specializes in computational morphology, statistical NLP, and machine learning applications in linguistics. Developed models for paradigm-based morphology using information theory and neural networks. Education: Ph.D. from Stanford University (1998). Recipient of multiple teaching and research awards including SDSU Faculty of the Year (2014). Supervised over 20 graduate students in linguistics and computational methods. Research Areas: Computational morphology, statistical language processing, machine learning, corpus linguistics Teaching: Computational linguistics, statistical methods, machine learning seminars Tools: Developed Toolkit for Advanced Discriminative Modeling, Rescorla-Wagner learning models

Bhavani ThuraisinghamView profile

Professor

• Cyber Security
• Data Security
• Privacy
• +5 more

Bhavani Thuraisingham is the Louis A. Beecherl Jr. Distinguished Professor of Computer Science and Executive Director of the Cyber Security Research and Education Institute at The University of Texas at Dallas. She holds a Doctor of Engineering (D.Eng.) from the University of Bristol (2011), a Ph.D. in Mathematics (Theory of Computation) from Swansea University (1979), and earlier degrees in Mathematics and Physics from the University of Ceylon (1975). Her research focuses on cyber security, data security, privacy, and the integration of AI with security. Specific interests include assured information sharing, secure geospatial data management, surveillance/biometrics, and data mining for counter-terrorism. She pioneered work on secure database systems, the inference problem in databases, and cloud data management security. Notable achievements include over 130 journal articles, 300+ conference papers, 7 patents, and prestigious awards from IEEE, AAAS, ACM, and others. She founded UT Dallas’ Cyber Security Institute, which has secured $65M+ in research funding. Her leadership roles include NSF program director (2001–2004) and MITRE Corporation researcher. Awards include IEEE Fellow (2003), AAAS Fellow (2003), and recognition as a top innovator by Silicon India (2002). Current initiatives emphasize trustworthy AI, blockchain security, and policy frameworks for emerging technologies.