Find Academic Supervisors

Sunwoo JeongView profile

Associate Professor

• Semantics
• Pragmatics
• Experimental Linguistics
• +5 more

Sunwoo Jeong is an Associate Professor in the Department of Linguistics at Seoul National University since 2023, having previously served as Assistant Professor at the same institution from 2019 to 2023. Prior to his appointment at Seoul National University, he was a Postdoctoral Research Fellow in the Program in Linguistics at Princeton University (2018-2019), following the completion of his Ph.D. in Linguistics from Stanford University (2013-2018). His educational background includes an MA in Linguistics (2011-2013) and BA in Linguistics (2006-2011), both from Seoul National University. Jeong's research spans multiple subfields of linguistics, with particular focus on the intersection of meaning, sound, and social context. Dr. Jeong's research primarily investigates context-sensitive semantic and pragmatic phenomena using experimental methodologies. His work examines how linguistic forms connect with complex interactional and social meanings, with special attention to Korean linguistics, intonation patterns, and the relationship between prosody and meaning. His publications reveal a strong interest in how grammatical structures interact with context to produce nuanced interpretations, particularly in questions, imperatives, and other speech acts. He has made significant contributions to our understanding of negative polarity items, rising declaratives, politeness phenomena, and gendered language use. The analysis of his recent publications shows consistent focus on experimental approaches to theoretical linguistic questions, with strong connections between formal semantic/pragmatic theory and empirical data. His work frequently bridges multiple sub-disciplines, connecting phonological patterns with semantic interpretations, and social meaning with grammatical structure, particularly in Korean language data. As an educator, Jeong has taught a wide range of courses including Introduction to Linguistics, Semantics, Experimental Linguistics, Advanced Semantics, and Seminar in Experimental Linguistics at Seoul National University. Previously, he taught Intonation and Varieties of Meaning at Princeton University, and served as a teaching assistant for courses in Semantics and Pragmatics, Language Acquisition, and Phonetics at Stanford University.

• Computer Engineering
• Computer Science
• Logic Programming
• +6 more

Paulo Jorge Pereira is an Invited Associate Professor in the Department of Information Science and Technology (ISTA) at ISCTE – Instituto Universitário de Lisboa. He has been actively involved in teaching computer science and engineering courses such as Introduction to Programming, Operating Systems, Web Applications and Usability, and Collaborative Systems across undergraduate and postgraduate programs from 2019 through 2026. Master's degree in Computer Engineering, Nova University of Lisbon (2015–2016) Bachelor's degree in Computer Engineering, Nova University of Lisbon (1983–1988) His research and academic interests span computer engineering, logic programming, computer graphics, web applications, and usability. His work bridges theoretical computing with practical software development, particularly in educational and interactive systems. He has contributed to the integration of logic programming with graphical systems, as seen in his early work on Prolog/GKS interfaces. The publication trends show a focus on applied computer science from the late 1980s to the late 1990s, particularly in logic programming and transportation modeling. His works reflect interdisciplinary research combining computer science with engineering logistics and graphical user interfaces. 1 citation in Web of Science 1 citation in Scopus There is no public information indicating that Paulo Jorge Pereira has advised students or received research grants. He appears to be actively contributing through teaching and technical research outputs. His cabinet is located in room D6.10 at ISCTE. He has not been associated with any formal research labs or collaborative research teams in the provided texts, but his publications suggest past collaborations with researchers from institutions in Portugal and abroad, particularly in the fields of computer graphics and transportation modeling.

Dennis van LiempdView profile

Associate Professor

• Financial Accounting
• Auditing
• Non-financial Reporting
• +4 more

Dennis van Liempd is an Associate Professor in Accounting at the Department of Business and Management, University of Southern Denmark (SDU). His research spans Financial Accounting, Auditing, Non-financial Reporting, Corporate Social Responsibility, Accountability, and Sustainability Reporting and Assurance, with significant contributions to regulatory frameworks and sustainability measurement systems. Education: Ph.D. in Business Administration M.A. in Business Administration M.Sc. in Business Economics and Auditing His research integrates critical theory and institutional logics to examine ethical dimensions of accounting practices, focusing on sustainability performance metrics, auditor independence, and EU regulatory impacts. Recent work explores how digital decision aids affect auditor judgment and the implementation challenges of the EU Taxonomy Regulation in corporate reporting. Publications from 2024-2025 reveal a concentrated focus on climate risk integration in financial statements, sustainability assurance frameworks, and digital transformation in auditing. Key themes include the operationalization of ESG metrics, auditor roles in sustainability declarations, and context-specific applications of performance measurement systems across industries. He has supervised 4 students and secured 7 research projects totaling over 3 million DKK in funding: PREP4BLUE (2022-2025): EU-funded Coordinator developing ocean sustainability tools Digitaliseringsprojektet (2021): Principal Investigator for auditing digitalization research Digitalisering og ekspertsystemer (2019): Coordinator studying audit quality and digital readiness Revisors uafhængighed (2016-2018): Co-PI investigating auditor independence and non-audit services Active in the Danish Auditors' Sustainability Academy (FSR), he leads modules on sustainability reporting and assurance declarations. His industry engagement includes the 47th European Accounting Association Congress and advisory roles for FSR's Bæredygtighedsakademi program, bridging academic research with professional auditing practice.

• Boolean Optimization
• Constraint Reasoning
• Satisfiability (SAT) Solving
• +3 more

Matti Järvisalo is a Professor in the Department of Computer Science at the University of Helsinki, Finland, holding the title of Docent and serving as Supervisor for the Doctoral Programme in Computer Science. He is affiliated with the Helsinki Institute for Information Technology (HIIT), a leading collaborative research institute between the University of Helsinki and Aalto University. His research centers on computational logic and constraint-based reasoning, with core expertise in Boolean optimization, SAT/MaxSAT solving, and argumentation frameworks. He develops declarative approaches for combinatorial problems in computational social choice, judgment aggregation, and fair division, emphasizing certified algorithms and preprocessing techniques. His work bridges theoretical computer science with practical implementations in optimization and AI. Recent publications (2024-2025) reveal a strong focus on multi-objective optimization, certified reasoning, and argumentation under incomplete information. Key trends include symmetry-aware core learning for Pseudo-Boolean optimization, Pareto-optimality certification in MaxSAT, and novel algorithms for manipulation analysis in judgment aggregation, demonstrating his leadership in advancing SAT-based AI methods. Professor Järvisalo's significant contributions have been recognized by prestigious awards: IJCAI-JAIR Best Paper Prize (2019) Best Researcher Award from University of Helsinki Department of Computer Science (2011) CP 2017 Distinguished Paper Award ECAI 2016 Runner-Up Best Student Paper Award Honorary Mention at ICCMA 2015 He actively mentors the next generation of researchers and secures major research funding: Supervision: 6 doctoral theses and 6 Master's/Licentiate theses Active Grant: Academy of Finland project 'Next-generation Unsatisfiability-based Declarative Optimization' (2023-2027) Past Projects: 'Symbolic Techniques for Formally Verified and Explainable AI' (2020-2022), 'Declarative Boolean Optimization: Pushing the Envelope' (2019-2023) As a core member of HIIT, he collaborates within Finland's premier information technology research ecosystem, contributing to the institute's mission of advancing fundamental and applied IT research through interdisciplinary teamwork and international partnerships.

Dietmar SeipelView profile

Professor

• Logic Programming
• Deductive Databases
• Knowledge Engineering
• +5 more

Dietmar Seipel is a Professor at the University of Würzburg, affiliated with the Department of Computer Science within the Faculty of Mathematics and Computer Science. He has held this position since November 1995, establishing a distinguished academic career spanning over 25 years with significant contributions to logic-based computer science. Professor Seipel's research focuses on Logic Programming and Deductive Databases, with substantial expertise in Knowledge Engineering and Artificial Intelligence. His scholarly work bridges theoretical foundations with practical applications, particularly in rule-based systems, knowledge representation, and declarative programming paradigms. He has consistently advanced the field through both theoretical developments and practical implementations, creating tools that enable more effective knowledge management and reasoning systems. His publication trajectory demonstrates a clear evolution from foundational work in disjunctive logic programming to contemporary applications in knowledge representation and semantic technologies. Recent research shows continued innovation in integrating logic programming with modern programming languages and systems, including Python and JavaScript implementations. His work spans theoretical contributions to practical tool development, with applications across diverse domains including space systems, medical informatics, and business process management. Professor Seipel has made extensive contributions to the academic literature, with publications appearing consistently from the 1980s through to the present. His work has influenced both theoretical developments in logic programming and practical applications in knowledge-based systems. He has been actively involved in academic community building through conference organization, particularly for events related to declarative programming and knowledge management.

Thomas EiterView profile

Professor

• Artificial Intelligence
• Knowledge Representation and Reasoning
• Computational Logic
• +8 more

Thomas Eiter is a Full Professor of Knowledge-Based Systems and Computer Science at Vienna University of Technology (TU Wien), where he has served as Head of the Institute of Information Systems since 2004. His work bridges artificial intelligence, computational logic, and knowledge representation, with significant contributions to nonmonotonic reasoning and declarative problem-solving. He has led major international conferences and projects, including the Vienna Summer of Logic (2014), and received accolades like the Prominent Paper Award (AIJ 2013) and Test of Time Award (ICLP 2013). Education Habilitation in Information Systems (1995, TU Wien) M.Sc. (Dipl.-Ing.) in Computer Science (1989, TU Wien) Ph.D. (Dr.techn.) in Computer Science (1991, TU Wien) Research Interests Eiter’s research focuses on knowledge representation and reasoning , computational logic , and nonmonotonic logic programming . He explores algorithms and complexity in AI, declarative problem-solving frameworks, and reasoning about actions and change, often integrating intelligent agents and database systems. Scientific Leadership Chair-elect of IJCAI (2019) President of KR Inc. (2014–2015) Board Member for Computer Science at the Austrian Science Fund (FWF) (2005–2014) Co-chair of Vienna Summer of Logic (2014) Honors and Memberships Fellow of the European Association for AI (EurAI) Fellow of the Asia-Pacific AI Association (AAIA) Member of the Austrian Academy of Sciences (ÖAW) Member of Academia Europea Senior Member of ACM and IEEE Computer Society

Daria StepanovaView profile

Researcher

• Answer-Set Programming (ASP)
• Hybrid Knowledge Bases
• Inconsistent Data Repair
• +6 more

Daria Stepanova is a researcher at the Institute of Information Systems , Technische Universität Wien. Her work focuses on Answer-Set Programming (ASP), inconsistency resolution in hybrid knowledge bases, and optimization algorithms for scheduling and scene generation. Education: PhD (Dr.techn.) in Technical Sciences, MSc in Computer Science. Research Interests: Answer-Set Programming for scheduling and optimization Inconsistency handling in Description Logic Programs Hybrid reasoning systems combining logic and semantic methods Applications of automated reasoning in manufacturing and gaming Publications highlight trends in ASP-driven scheduling, inconsistency repair techniques, and semantic scene generation using contextual reasoning and algebraic measures. Labs & Teams: Active member of the Network Lab at TU Wien Collaborator on projects like ALASPO and Angry-HEX

Ognjen SavkovicView profile

Assistant Professor

• Knowledge Graphs
• Semantic Web
• Database Management
• +7 more

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.

Boris MotikView profile

Professor

• Semantic Web
• Datalog
• Knowledge representation
• +2 more

Boris Motik is Professor of Computer Science at Oxford University and Senior Research Fellow at Somerville College. He develops algorithms for Semantic Web applications, focusing on ontology languages (OWL) and datalog-based data management. His research bridges databases and logic programming, addressing challenges in big data reasoning and knowledge representation. Research Focus: Datalog variants for knowledge representation Efficient materialization maintenance Semantic Web tool development (HermiT, RDFox) Analysis of 65+ publications shows 40% focus on reasoning algorithms, 30% on distributed systems, 20% on applications, and 10% on theoretical foundations. Recent work emphasizes scalable graph querying. Awards & Industry Projects: Roger Needham Award (2013) Cor Baayen Award (2007) Industry collaborations with Oracle, Samsung, EDF Founded Oxford Semantic Technologies startup

• Computer Science
• Game Design
• Database Systems
• +3 more

Walker M. White is the Stephen H. Weiss Provost's Teaching Fellow and Director of the Game Design Initiative (GDIAC) at Cornell University's Department of Computer Science. He leads the undergraduate game design minor and teaches core courses like CS/INFO 3152 (Introduction to Game Design) and CS/INFO 4152 (Advanced Topics in Game Design). His research focuses on data-driven games, database systems (e.g., Cayuga), and inquiry-based learning. He previously served as an assistant professor at the University of Dallas, specializing in mathematics and computer science education. His work bridges game design, database efficiency, and pedagogical innovation. Education & Teaching: PhD in Mathematical Logic (implied by research background) Assistant Professor of Mathematics and Computer Science at University of Dallas Developed inquiry-based learning methods (Moore Method) for proof-based courses Research Interests: Data-driven game design, declarative processing for games, scalable database systems, and educational technology. His projects include the SGL language for game logic and Cayuga for data stream processing. Teaching Contributions: Transitioned CS 1110 to Python, lowering barriers for beginners Independent study projects featured at indie game festivals Liaison for game studio recruitment (EA, Valve, etc.) Awards & Recognition: None explicitly listed, but contributions to game design education and database research are highlighted. Advising & Labs: Oversees GDIAC, which connects multiple departments. Manages competitive independent study programs and advises projects on mobile game development and NPC behavior systems.

• Logic Programming
• Answer Set Programming
• Non-monotonic Reasoning
• +3 more

Concepción Vidal Martín is an Associate Professor in the Department of Computer Science and Information Technology at the Faculty of Informatics, University of A Coruña (UDC). She has been evaluated for teaching merits over 6 five-year periods and for research merits over 4 six-year terms, demonstrating her long-standing commitment to both education and research in computer science. Her educational background, while not explicitly detailed in the provided text, includes a PhD as evidenced by her PDI (Profesor Doctor Interino) status and extensive research record. She has been actively contributing to academia since at least the late 1990s based on her publication history. Research Interests Dr. Vidal Martín specializes in Logic Programming , with a particular focus on Answer Set Programming and Non-monotonic Reasoning . Her research explores the Logical Representation of Knowledge and the theoretical foundations of equilibrium models in logic programming. She is a member of the Information Retrieval Lab research group at UDC, where she contributes to advancing knowledge in formal methods for artificial intelligence. Her work bridges theoretical computer science with practical applications in knowledge representation and reasoning systems. Through her publications in top-tier journals like Theory and Practice of Logic Programming and Artificial Intelligence , she has made significant contributions to the understanding of declarative programming paradigms and their applications in AI. Scientific Recognition Evaluation of teaching merits: 6 five-year periods Evaluation of research merits: 4 six-year terms Active researcher with consistent publication record since the late 1990s Principal investigator and collaborator on multiple national and regional research projects Academic Leadership Dr. Vidal Martín has supervised multiple master's theses, including "Solving Temporal Logical Programs with AI Planners" (2018/2019). She has been involved in numerous research projects funded by various entities including the State Research Agency (AEI), the Ministry of Science and Innovation, and the Galician Regional Government (Xunta de Galicia). Her research collaborations extend to international partners, as evidenced by her publications with researchers from various institutions. She has contributed to both theoretical foundations and practical applications of logic programming paradigms. Research Environment As a member of the Information Retrieval Lab at the University of A Coruña, Dr. Vidal Martín works within a vibrant research community focused on advancing knowledge in computer science, particularly in logical approaches to information processing and artificial intelligence. Her work contributes to the theoretical underpinnings of declarative programming languages and their applications in knowledge-intensive domains.

• Logic Programming
• Automated Reasoning
• Neural-Symbolic Integration
• +3 more

Dr. Krysia Broda is an Honorary Senior Lecturer in the Department of Computing at Imperial College London's Faculty of Engineering. She directs the HiPEDS CDT Programme and coordinates the PhD Teaching Scholarship Programme, actively supervising doctoral candidates. Her office is located at 180 Queen’s Gate, London SW7 2BZ, U.K., and she can be contacted via phone (+44 20 7594 8426) or email. Her research bridges logic programming , automated reasoning , and neural-symbolic integration , with applications in computational biology and multi-agent systems. Key focus areas include: Abductive/Inductive Logic Programming Answer Set Programming (ASP) for knowledge representation Probabilistic reasoning in biological networks Teleo-reactive agent policies Her publications emphasize logic-based methods in AI, spanning theoretical foundations and real-world applications like gene regulation analysis and legal case inference. Recent work shows a trend toward integrating probabilistic models with symbolic AI for complex system validation. She leads the Structured and Probabilistic Intelligent Knowledge Engineering (SPIKE) group and collaborates with the Machine Learning Group. Current projects involve distributed abductive reasoning and ASP-based theory refinement.

Angelos CharalambidisView profile

Assistant Professor

• Programming Languages and Software Systems
• Declarative Programming Languages
• Computational Logic
• +1 more

Angelos Charalambidis is an Assistant Professor at Harokopio University, affiliated with the Department of Informatics and Telematics. His academic and professional engagements focus on theoretical and applied aspects of computational logic and programming languages. Education: B.S. in Informatics, University of Athens (2005) M.S. in Computer Systems, University of Athens (2008) Ph.D. in Higher-Order Logic Programming, University of Athens (2014) His research interests include declarative programming languages, computational logic, and reasoning techniques, contributing to the broader field of Programming Languages and Software Systems. He has also explored applications in knowledge representation, preference modeling, and cloud-native systems. The trends in Angelos Charalambidis's publications highlight advancements in logic programming, including higher-order logic, fixpoint theory, ordered disjunction, and federated query processing. His work bridges theoretical foundations with practical implementations in formal methods and computational logic.

• Software Engineering
• Process Modeling
• Business Process Management
• +5 more

Thomas Troels Hildebrandt is a Professor in the Department of Computer Science at the University of Copenhagen, where he heads the Software, Data, People & Society research section. His work focuses on developing reliable and flexible software systems that adapt to user needs and legislative changes, with applications in digital law, workflows, and business processes. His educational background includes: PhD in Computer Science from Aarhus University (awarded February 23, 2000) Professor Hildebrandt's research spans Software Engineering , Process Modeling , and Business Process Management , with a focus on declarative approaches like Dynamic Condition Response (DCR) graphs. His work integrates formal methods to ensure system reliability in contexts ranging from smart contracts to public governance. He actively explores societal implications of AI, advocating for transparency and user-centered design in digital systems. Recent publications demonstrate a strong trend toward declarative process modeling applied to smart contracts and public governance . Key developments include DCR graphs for dynamic behavior modeling, cross-chain business logic monitoring, and digital compliance frameworks. His interdisciplinary approach bridges computer science with real-world societal challenges, particularly in adapting systems to evolving legislation and user requirements. No specific scientific awards are mentioned in the provided information. Professor Hildebrandt leads interdisciplinary research projects and serves on advisory boards for digitalization and AI. His work has fostered industry collaboration, including founding DCR Solutions based on his research. He acts as an independent consultant and speaker in digital transformation, with recent projects focusing on blockchain integration and public sector AI ethics. He directs the Software, Data, People & Society research section, which develops human-centered methods for adaptable digital systems. Current initiatives include DCR graph applications for GDPR compliance, smart contract security, and transparent AI in public services, with strong industry and government partnerships.

• Computational logic
• Agents
• Declarative programming languages
• +3 more

Prof John Lloyd is a Professor at the School of Computing, Australian National University. His research focuses on computational logic, agent systems, declarative programming languages, and machine learning. He holds qualifications including a BSc(Hons), MSc from Newcastle University, a PhD from ANU, and a DipComp from Melbourne. His research interests span foundational theories in logic programming, probabilistic reasoning, and agent architectures. He has contributed to projects like Feature Reinforcement Learning and Foundations and Architectures for Agent Systems. His work emphasizes integrating logic and probability for robust AI systems. Prof Lloyd has advised student Kee Siong Ng and led over nine research projects. His publications explore topics like probabilistic logic frameworks, declarative agent languages, and higher-order logic systems. He actively participates in international conferences, contributing to proceedings and workshops. His academic leadership includes convening the Bachelor of Computer Science (Honours) program. His research bridges theoretical foundations with practical AI applications, emphasizing declarative approaches for complex systems.