جستجوی استاد راهنمای دانشگاهی

Thomas Eiterمشاهده پروفایل

استاد

• Artificial Intelligence
• Knowledge Representation and Reasoning
• Computational Logic
• +۷ مورد دیگر

Thomas Eiter is a Full Professor at the Institute of Logic and Computation, Technical University of Vienna (TU Wien), where he serves as Head of Research Unit. He is a Full Member of the Division of Mathematics and Natural Sciences since 2022 and holds leadership roles within the university. His research focuses on knowledge representation and reasoning, computational logic, algorithms and complexity in AI, declarative problem solving, nonmonotonic logic programming and databases, and reasoning about actions and change. His work bridges theoretical foundations with practical applications in artificial intelligence, particularly in logic programming and knowledge-based systems. He has made significant contributions to Answer Set Programming (ASP), developing frameworks like DLV and HEX programs that enable sophisticated reasoning capabilities. His recent publications demonstrate a strong focus on stream reasoning (LARS framework), knowledge forgetting, modular reasoning systems, and the integration of logic programming with ontologies. His research shows consistent contributions to both theoretical foundations and practical implementations of AI systems over several decades. ACM Fellow (2020) Fellow of the European Association for AI (2006) Distinguished Paper Award of the 17th International Joint Conference on Artificial Intelligence (IJCAI, 2001) Prominent Paper Award of the Artificial Intelligence Journal (2013) Test of Time Award (10 years) of the International Conference on Logic Programming (2013) Eiter has led and participated in numerous research projects, both internationally funded (such as LogiCS@TUWien, Humane AI, AI4EU) and nationally funded (including projects like BILAI, TAIGER, and several FWF-funded initiatives). His research unit has received substantial support from European Commission programs (H2020) and Austrian funding agencies (FWF, FFG, WWTF). He is actively involved in the academic community as a member of the Austrian Academy of Sciences (ÖAW), Academia Europaea, and has served on the Executive Council of AAAI. His research unit maintains strong connections with international collaborators and has developed influential systems like the DLV answer set programming system.

Paul S. Rosenbloomمشاهده پروفایل

استاد

• Cognitive Architecture
• Artificial General Intelligence
• Hybrid Symbol Systems
• +۴ مورد دیگر

Paul S. Rosenbloom is a Professor in the Department of Computer Science at the University of Southern California , with affiliations at the Institute for Creative Technologies . His work focuses on cognitive architectures , particularly the development of the Sigma architecture and contributions to the Common Model of Cognition . He has pioneered the integration of symbolic, probabilistic, and neural systems in AI research. Research Interests: Dr. Rosenbloom's research spans hybrid symbol systems , neural-symbolic integration , and the evolution of computational models of cognition . His recent work rethinks the Physical Symbol Systems Hypothesis through hybrid systems that bridge symbolic AI and neural networks, addressing challenges in universality , compositional reasoning , and cognitive modeling . Scientific Awards: 2011 Kurzweil Award for Best AGI Idea 2012 Kurzweil Award for Best AGI Paper 2023 Springer Prize for Best Paper Publications and Contributions: He has authored over 150 publications and co-authored foundational works on the Common Model of Cognition with Laird, Lebiere, and Stocco. His research has been supported by grants from the U.S. Army RDECOM and USC's Institute for Creative Technologies. He has mentored numerous collaborators and co-authors, including researchers like V. Ustun , A. Demski , and H. Joshi , in projects spanning virtual humans , reinforcement learning , and distributed vector representations .

• Knowledge representation and reasoning
• Planning
• Nonmonotonic reasoning
• +۲ مورد دیگر

Yannis Dimopoulos is a Professor in the Department of Computer Science at the University of Cyprus. He has previously held research positions at the Max-Planck Institute for Computer Science in Saarbrücken and the University of Freiburg in Germany. He earned his B.Sc. and Ph.D. in Computer Science from the Athens University of Economics and Business. His primary research interests include: Knowledge representation and reasoning Planning Nonmonotonic reasoning Constraint satisfaction Machine learning His recent research, based on publications from 2017 to 2024, focuses on the theoretical and computational aspects of abstract argumentation, particularly control argumentation frameworks, probabilistic extensions, and the integration of argumentation with Boolean networks and negotiation under incomplete information. He has also contributed significantly to Answer Set Programming (ASP) for planning, developing the plasp 3 framework for effective ASP-based planning solutions. His scholarly work appears in top-tier venues such as AAAI, IJCAI, ECAI, KR, AAMAS, and journals like Artificial Intelligence and Autonomous Agents and Multi-Agent Systems. His most frequent collaborators include Pavlos Moraitis, Jean-Guy Mailly, Antonis C. Kakas, and Wolfgang Dvorák. No scientific awards or honors are mentioned in the provided text. Yannis Dimopoulos has advised or collaborated with several researchers, including Jean-Guy Mailly, Pavlos Moraitis, Nabila Hadidi, and Muhammad Adnan Hashmi, though formal student-advisor relationships are not explicitly detailed. His work often involves theoretical and computational modeling, and while specific grants or funding sources are not listed, his sustained publication record suggests active research support. He is actively involved in research teams and collaborations focused on argumentation, multi-agent systems, and automated reasoning, as evidenced by his extensive co-authorship network.

• Boolean Optimization
• Constraint Reasoning
• Satisfiability (SAT) Solving
• +۳ مورد دیگر

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.

Thomas Eiterمشاهده پروفایل

استاد

• Artificial Intelligence
• Knowledge Representation and Reasoning
• Computational Logic
• +۸ مورد دیگر

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

Patrick MARCELمشاهده پروفایل

استاد

• Databases
• Exploratory Data Analysis
• OLAP
• +۴ مورد دیگر

Patrick MARCEL is a Full Professor at the Department of Computer Science, University of Orléans, and a member of the LIFO laboratory. He holds a PhD from INSA Lyon (1998) and a Habilitation à Diriger les Recherches from Université de Tours (2012). His research focuses on databases, exploratory data analysis, OLAP, data mining, and recommendation systems. He serves as an associate editor for the DKE journal and leads the Steering Committee of the DOLAP workshop, co-chairing in 2017 and 2021. Education: PhD in Computer Science, INSA Lyon, 1998 Habilitation à Diriger les Recherches, Université de Tours, 2012 Research Interests: Exploratory Data Analysis & OLAP Data Mining and Machine Learning Personalization and Recommendation Systems Context-Aware Data Quality Management Emotional Data Interaction His work emphasizes intention-driven analytics, cube query optimization, and narrative generation in business intelligence. Publications: Over 80 articles spanning OLAP systems, data quality, and recommendation techniques, with recent emphasis on emotional intelligence in query design and matheuristics for optimization problems. His 2024 work explores intentional aspects in data narratives and context-aware methodologies. Awards: None explicitly listed. However, his editorial roles and workshop leadership highlight peer recognition. Advising & Grants: No student names listed, but active in mentoring through research projects. His work is supported by collaborations with industry and academic partners. Labs & Teams: Member of the LIFO lab (Laboratoire d’Informatique Fondamentale d’Orléans), team Pamda. Engaged in interdisciplinary research on data platforms and analytical processing.

Thomas W. Repsمشاهده پروفایل

استاد

• Programming languages
• Software engineering
• Static program analysis
• +۵ مورد دیگر

Thomas W. Reps is a Professor in the Department of Computer Science at the University of Wisconsin, holding the position since 1985. He has served as President and Co-founder of GrammaTech, Inc. since 1988, and held visiting roles including Guest Professor at the University of Paris 7 (2007-08), Visiting Researcher at CNR in Pisa, Italy (2000-01), and Guest Professor at the University of Copenhagen (1993-94). He previously served as Associate Chairman of the Computer Sciences Department at Wisconsin (1990-93) and held postdoctoral roles at Cornell University and INRIA. Reps' research spans programming languages, software engineering, and computer security, with a focus on static program analysis, machine-code analysis, and program slicing. His work in model checking, software maintenance, and analysis techniques for information security has significantly impacted the field of computer science. 2017 ACM SIGPLAN Programming Languages Achievement Award 2015 WARF Named Professorship 2005 ACM Fellow 2000 Guggenheim Fellowship 1986 NSF Presidential Young Investigator Award Reps' publications highlight advancements in interprocedural dataflow analysis, weighted pushdown systems, and symbolic computation. His work bridges theoretical foundations with practical applications in software verification and security, creating tools that have shaped modern program analysis techniques. He has collaborated extensively with researchers like Somesh Jha, Mooly Sagiv, and Gogul Balakrishnan across institutions in Europe and the U.S.

David G. Mitchellمشاهده پروفایل

دانشیار

• Propositional Satisfiability
• Constraint Satisfaction Problems (CSP)
• Formal Verification
• +۳ مورد دیگر

David G. Mitchell is an Associate Professor in the Department of Computing Science at Simon Fraser University (SFU). He is part of the School of Computing Science and affiliated with the Computational Logic Laboratory. His research focuses on propositional satisfiability (SAT) and finite domain constraint satisfaction (CSP), exploring their complexity and practical algorithm design for applications in formal verification and related tasks. Education : Ph.D., Computer Science, University of Toronto, 2002 M.Sc., Computing Science, Simon Fraser University, 1993 B.Sc., Cognitive Science and Artificial Intelligence, University of Toronto, 1989 Research Interests : Mitchell's work bridges mathematical logic and computer science, emphasizing SAT-based problem solving, constraint modeling languages, and automated reasoning. His contributions include advancements in clause learning, resolution complexity, and declarative programming frameworks for solving NP problems. He has developed tools like MXC and Enfragmo, which apply SAT techniques to real-world applications. Students : Mitchell has advised numerous graduate students, including current PhD candidates Mona Mehdizadeh and Sima Jamali, and past advisees such as Sahba Etezad, Heng Liu, and Faraz Hach. His students' work spans algorithm optimization, constraint satisfaction, and formal verification. Labs/Teams : He is a member of the Computational Logic Laboratory at SFU, contributing to research in logic-based problem-solving and algorithm development.

• Approximation Theory
• Semantics
• Constraint Satisfaction Problems
• +۴ مورد دیگر

Bart Bogaerts is a Professor at the Vrije Universiteit Brussel , affiliated with the Federated Labs AI and Robotics and the Department of Informatics and Applied Informatics . His research centers on Approximation Theory , Logic Programming , Knowledge Representation , and Constraint Satisfaction Problems , with a focus on formalizing reasoning methods and optimizing computational systems. His recent publications emphasize certified algorithms, semantic web traversal, and formal verification, reflecting collaborations with institutions like KU Leuven and Maastricht University. Key themes include: Algorithm Certification : Integrating Coq for verified logic programming and optimization techniques. Web Technologies : Distributed subweb specifications and query processing frameworks. Nonmonotonic Reasoning : Advancing approximation fixpoint theory in knowledge representation. Scientific recognitions include the AAAI 2022 Distinguished Paper Award and the IJCAI 2021 Distinguished Paper Award . Dr. Bogaerts supervises PhD students such as Samuele Pollaci, Robbe Van Den Eede, and Dirk Vandesande in joint programs with VUB and KU Leuven.

Karol Draszawkaمشاهده پروفایل

مدرس

• Artificial Intelligence
• Machine Learning
• Neural Networks
• +۵ مورد دیگر

Karol Draszawka serves as an Assistant lecturer at Gdańsk University of Technology, specifically within the Department of Computer Systems Architecture in the Faculty of Electronics, Telecommunications and Informatics. His academic work focuses on developing innovative approaches to artificial intelligence and machine learning problems. Dr. Draszawka's research interests span multiple domains of computer science, with particular emphasis on neural networks , reinforcement learning , and computer vision applications . His work demonstrates expertise in developing agents capable of solving complex logic tasks, improving multi-label classification systems, and implementing practical computer vision solutions for publishing sector applications. His research often bridges theoretical AI concepts with practical implementations, particularly in the areas of augmented reality and mobile applications. His publication record shows consistent contributions to the field from 2020 through 2024, with work appearing in journals like Applied Sciences-Basel and Communications in Computer and Information Science. His research demonstrates a progression from foundational AI concepts (like the Wumpus World environment) to increasingly sophisticated neural network applications and practical implementations in publishing technologies.

• Artificial Intelligence
• Cybersecurity
• Optimization Algorithms
• +۳ مورد دیگر

Alice Tarzariol is a Researcher at the Institut für Artificial Intelligence und Cybersecurity within the Faculty of Technical Sciences at Alpen-Adria-Universität Klagenfurt. She specializes in computational logic, optimization algorithms, and their applications in artificial intelligence. Her research focuses on advancing Answer Set Programming (ASP) techniques for complex problem-solving, including production scheduling, symmetry breaking, and constraint learning. She also explores interdisciplinary applications such as cancer data analysis through logic programming frameworks. Her work emphasizes improving algorithmic efficiency and developing tools for combinatorial optimization, formal verification, and bioinformatics. She contributes to projects like the institute’s efforts to strengthen regional knowledge transfer and serves on the Curricularkommission für das Erweiterungscurriculum Gender Studies. Her research spans both theoretical advancements in computational logic and practical implementations in industrial and medical domains. Key themes in her publications include symmetry detection and lifting, constraint satisfaction, and inductive logic programming. Recent work highlights declarative approaches to production scheduling and efficient symmetry-breaking methods. Her research has implications for automated decision-making, systems modeling, and data-driven healthcare solutions.

• Artificial Intelligence
• Knowledge Representation
• Automated Reasoning
• +۳ مورد دیگر

Yuliya Lierler is a full Professor of Computer Science at the University of Nebraska Omaha (UNO), affiliated with the College of Information Science & Technology (IS&T). She holds the Cheryl Prewett Diamond Professorship since 2020 and received the Mentor of the Year Award in 2025. Her research focuses on artificial intelligence, particularly knowledge representation, automated reasoning, declarative problem solving, and natural language understanding. She co-directs the NLPKR lab and has authored over 70 peer-reviewed articles in top AI venues. Her books include Discrete Mathematics in a Nutshell and Digital Minimalism for Teens . Education: Ph.D. in Computer Science from the University of Texas at Austin (2010). Professional development includes training in AI-driven teaching methodologies and online education. Research Interests: She explores formal methods in AI, including logic programming semantics (e.g., Answer Set Programming), automated reasoning techniques, and applications in natural language processing. Her work bridges theoretical foundations with practical tools, such as the text2ALM information extraction system. Service & Leadership: Co-Chair of the 38th International Conference on Logic Programming (2022), Executive Committee member of the Association for Logic Programming (since 2020), and former Graduate Program Committee Chair (2018–2020). She has organized multiple international conferences and contributed to AI education initiatives. Awards: Recipient of the 2025 Mentor of the Year Award (Nebraska Women in Tech), 2024 Outstanding Research Award (IS&T College), and 2016 Best Student Paper Award (with Amelia Harrison). Labs & Teams: Co-director of the NLPKR lab, focusing on natural language processing and knowledge representation. Collaborates on projects integrating declarative programming with semantic understanding.

Justin Pearsonمشاهده پروفایل

دانشیار

• Constraint Programming
• Combinatorial Optimisation
• Artificial Intelligence
• +۷ مورد دیگر

Justin Pearson is an Associate Professor at the Department of Information Technology; Division of Computing Science at Uppsala University . He is a member of the university's optimisation group and coordinates the IT department's mentor programme for new employees . Research Interests include Constraint Programming , Combinatorial Optimisation , Artificial Intelligence , Software Testing , and Complexity Theory . His work focuses on theoretical and practical aspects of constraint satisfaction, local search algorithms, and symmetry breaking in constraint programming. Teaching involves courses such as Algorithms and Data Structures II (1DL231) and Introduction to Machine Learning for Bachelor Students (1DL034), with a PhD-level course on Category Theory offered periodically based on demand. Scientific Contributions span publications in constraint programming for air traffic management, sensor networks, and industrial applications. Recent work includes parameterised treewidth in constraint models, time-series constraints, and symmetry breaking techniques. Students supervised include PhD candidates Frej Knutar Lewander (co-supervised with Pierre Flener), Yi Zhao (co-supervised with Di Yuan), and previously graduated students Gustav Björdal , María Andreína Francisco Rodríguez , and Joseph Scott .

• Artificial Intelligence
• Cybersecurity
• Computer Science
• +۳ مورد دیگر

Michael Morak is a Professor at the Department of Artificial Intelligence and Cybersecurity, Alpen-Adria-Universität Klagenfurt, affiliated with the Faculty of Technical Sciences. He holds the titles Privatdozent, Diplom-Ingenieur, and Doctor. His research focuses on artificial intelligence, cybersecurity, and computer science, with notable contributions in logic programming, answer set programming, and algorithmic methods. He has led and contributed to multiple research projects funded by entities like the Austrian Research Promotion Agency (FFG) and the Austrian Agency for International Cooperation in Education (OeAD), addressing topics such as multi-agent systems, radar simulation, and educational technology. His work spans theoretical advancements, including reversibility in planning and dynamic programming, as well as practical applications like interactive SQL learning tools (aDBenture). He collaborates with industry partners, including Infineon Technologies, and has published extensively in top-tier conferences and journals. Morak’s teaching emphasizes innovative methods in computer science education, leveraging game-based learning and interactive platforms to enhance student engagement. Key areas of research include formal methods in AI, algorithmic complexity, and the integration of logic programming with real-world systems. His projects often bridge academia and industry, aiming to solve complex challenges in cybersecurity, robotics, and educational innovation.

• Artificial Intelligence
• Knowledge Representation and Reasoning
• Logic Programming
• +۵ مورد دیگر

Tomi Janhunen is a Professor in Computing Sciences at Tampere University, part of the Faculty of Information Technology and Communication Sciences. His expertise spans Artificial Intelligence, Logic Programming, and Theoretical Computer Science. He actively contributes to academic leadership roles, serving on boards of the Finnish Association of Computer Science and Finnish Artificial Intelligence Society. His research focuses on Answer Set Programming (ASP), probabilistic reasoning systems, explainable AI, and optimization techniques applied to cybersecurity and maintenance scheduling. Key grants include the XAILOG and AI-ROT projects funded by the Research Council of Finland. Notable achievements include three prestigious awards: Best Paper Awards at the European Conference on Logics in AI (2021) and International Conference on Logic Programming (2023), and the Harold Boley award for system description (2022). Dr. Janhunen’s work emphasizes practical applications of declarative programming paradigms. Recent projects include Plingo—a probabilistic ASP system—and cybersecurity compliance frameworks in DevSecOps environments. His contributions bridge theoretical advancements with real-world challenges in AI security and industrial optimization.