Sanja Lukumbuzya is a PostDoc Researcher at the Knowledge-Based Systems group (E192-03) of Vienna University of Technology. Her work bridges formal logic and practical data systems, focusing on ontology-mediated data management, description logics, and business process challenges. Research Interests Ontology-Based Data Access (OBDA) Description Logics and Datalog Rewriting Process Mining and Workflow Analysis Hybrid Reasoning Systems Incomplete Data Handling Computational Complexity in Knowledge Bases Affiliations Vienna University of Technology, Austria Researcher in projects KtoAPP (2018–2025) and OMEGA (2017–2022) Publications Trends Her recent work addresses algorithmic complexity in expressive logics (2024), coNP expressiveness in ontology queries (2023), and practical BPM challenges (2023). Earlier studies focused on bounded predicates (2021), hybrid ASP-ontology frameworks (2020), and dishonesty modeling (2018).
Florina Piroi is a Senior Researcher at the Technische Universität Wien (TU Wien), affiliated with the Faculty of Informatics and the Department of Data Science. She holds the role of Senior Scientist in Data Science and is a Substitute Member of the Curriculum Commission for Business Informatics. Her primary research focuses on information retrieval, medical informatics, natural language processing, and patent text mining. She leads projects such as the CLEF-IP evaluation lab and contributes to initiatives like the DoSSIER and OS Trails research programs. Key research interests include longitudinal evaluation of machine learning models, reproducibility in NLP tasks, and knowledge graph applications in manufacturing. She has supervised PhD student Anindita M. Ningtyas, whose work addresses medical terminology accessibility for laypeople. Piroi collaborates on interdisciplinary projects, such as designing health datasets from medical forums and improving search systems for evolving corpora. Her notable contributions include benchmarking frameworks for IR systems, semantic translation tools for industry, and methods for analyzing electrical systems. She has published over 50 peer-reviewed articles in venues like SIGIR, CLEF, and ECIR, emphasizing practical applications in both academic and industrial contexts.
Sebastian Skritek is a Senior Lecturer at the Technische Universität Wien in the Department of Databases and Artificial Intelligence. His research primarily focuses on database theory, semantic web technologies, and query processing. Research interests include foundational aspects of database systems, complexity analysis of query languages, and optimization techniques for semantic web applications. His work bridges theoretical computer science with practical database implementations. His publications demonstrate a consistent focus on query evaluation complexity and optimization, particularly in SPARQL and conjunctive query systems. Recent work explores diversity in query answers and tractability boundaries. Supervision includes guiding students in database theory projects and theses. Research projects include 'SEE: SPARQL Evaluation and Extensions' and 'Theoretical Tractability vs. Practical Computation'.
Martin Weise is a PreDoc Researcher at the Data Science Research Unit (DS-IFS) within the Department of Information Systems Engineering at Vienna University of Technology (TU Wien). His work focuses on secure data infrastructures, virtual research environments, FAIR data principles, and research data repositories. MSc in Software Engineering & Internet Computing (2022) BSc in Software & Information Engineering (2019) Research interests include: FAIR Data Implementation Trusted Research Environments Secure Data Infrastructures Virtual Research Environments Data Preservation Interoperability Solutions Recent publications highlight his contributions to: DBRepo: Semantic Repository Systems Trusted Research Environments Cyber Situational Awareness FAIR Principle Implementation Secure Data Visiting Data Preservation Frameworks
Jan Niclas Dreier is a PostDoc Researcher at TU Wien's Department of Algorithms and Complexity. His research focuses on theoretical computer science, particularly algorithmic meta-theorems, structural graph theory, and computational complexity. He is affiliated with projects such as REVEAL-AI and SLIM. His work addresses topics like monadic stability, SAT solving, and model checking on sparse graph classes. Research Interests : Dreier's primary areas include algorithm design, parameterized complexity, and logic in computer science. His contributions span model checking for graph classes, backdoor analysis in SAT solving, and combinatorial properties of monadic dependence. Recent work explores the interplay between structural graph theory and algorithmic efficiency, with applications to finite model theory and pseudorandom models. Teaching : He teaches courses such as Algorithmic Meta-Theorems , Algorithmics , and Bachelor Thesis in Computer Science . His courses emphasize theoretical foundations and practical algorithmic techniques. Projects : Active involvement in the REVEAL-AI project (2020–2024) and SLIM (2019–2024), focusing on algorithmic advancements in AI and structural graph analysis.
Phokion Kolaitis is a Professor of Computer Science at the University of California Santa Cruz (UC Santa Cruz) and a Principal Research Staff Member (part-time) at the IBM Almaden Research Center. He has held leadership roles as Chair of UC Santa Cruz's Computer Science Department (1997-2001, 2014-2015) and Senior Manager at IBM's Computer Science Principles and Methodologies Department (2004-2008). His research bridges database systems, computational complexity, and logic in computer science, with significant contributions to schema mappings, data exchange, and constraint satisfaction problems. His work spans foundational studies in database theory, logic, and algorithms, influencing both academic research and industrial applications. Kolaitis has received numerous accolades, including two ACM PODS Alberto Mendelzon Test-of-Time Awards, IBM Research Division Outstanding Innovation and Technical Achievement Awards, and Best Paper Awards at top conferences like ICDT and FCT. He is a Fellow of AAAS and ACM, a Foreign Member of the Finnish Academy of Science and Letters, and holds an Honorary Doctorate from the University of Athens, Greece. 2017 Best Paper Award (FCT 2017) 2015 IBM Outstanding Innovation Award 2014 Honorary Doctorate (University of Athens) 2008 IBM Outstanding Technical Achievement Award Fellow of AAAS and ACM Foreign Member, Finnish Academy of Science Kolaitis collaborates extensively, co-authoring with researchers like D. Burdick, R. Fagin, and M.Y. Vardi. At UC Santa Cruz, he advises on database systems and logic, while his part-time role at IBM focuses on theoretical advancements in data management and complexity.
Hermann Maurer is Full Professor of Computer Science at Graz University of Technology (since 1978), with additional roles as Honorary Visiting Professor at Danube University and Honorary Research Fellow at University of Auckland (till 2012). He has held leadership positions including Dean of Computer Science (2004-2007) and Chair of Informatics Section in Academia Europaea (2007-2012). Key Institutions: Graz University of Technology, Austria-Forum, JOANNEUM RESEARCH, Academia Europaea Academic Honors: Member of Finnish Academy of Sciences, Cross of Honour for Arts and Science (Austria), multiple honorary doctorates Research Focus: Networked Interactive Digital (NID) Books, Austria-Forum (1.1M entries), hypermedia systems, anti-monopoly digital frameworks, and societal impacts of technology. He pioneered second-generation web systems and co-founded conferences like ED-MEDIA and I-KNOW. Key Trends in Publications: Recent works emphasize NID systems, interactive encyclopedias, web reliability, and the future of digital libraries. His research spans e-learning, information integration, and combating web-based plagiarism. Scientific Awards: Honorary Doctorates (St. Petersburg, Karlsruhe, Calgary) AACE Fellowship (2003) Integrata Prize (2000) Enter Prize (1999) Advising & Grants: Supervised over 400 M.Sc. and 50 Ph.D. theses. Led multimillion-dollar projects including Hyperwave AG, COSTOC, and Austria-Forum. His work on optical storage and color-graphic microcomputers (MUPID) exemplifies technological innovation.
Minyi Guo is a Chair Professor and Head of the Department of Computer Science and Engineering at Shanghai Jiao Tong University (SJTU), China. Previously, he served as Professor and Department Chair at the School of Computer Science and Engineering, University of Aizu, Japan. Dr. Guo received his BSc and ME degrees from Nanjing University, China in 1982 and 1986, and his PhD from University of Tsukuba, Japan in 1998. Dr. Guo's educational background includes: BSc in Computer Science, Nanjing University, China (1982) ME in Computer Science, Nanjing University, China (1986) PhD in Computer Science, University of Tsukuba, Japan (1998) Dr. Guo's research spans multiple areas in computer science, with a primary focus on parallel/distributed computing , compiler optimizations , cloud computing , database systems , and big data . He has published over 400 papers including approximately 150 in major journals and 250 in international conferences, with more than 60 papers in IEEE/ACM transactions and over 100 papers in prestigious conferences. Dr. Guo has also authored 7 books (4 in English, 3 in Chinese) and received 5 best/highlight paper awards from international conferences. Dr. Guo's publication record demonstrates strong contributions across multiple domains of computer systems research. His recent work shows particular emphasis on big data processing, edge computing, graph neural networks, and data center optimization. The publications reveal a consistent trajectory of impactful research in parallel and distributed systems, with increasing focus on AI/ML applications and blockchain technologies in more recent years. Dr. Guo has received numerous prestigious awards and honors: State Technological Invention Award of China (second class award, 2019) Shanghai Technological Invention Award (first class award, 2018) IEEE Technical Committee on Scalable Computing Award for Excellence in Scalable Computing (2018) Ministry of Education Natural Science Award (first class award, 2017) IEEE Fellow (2017) Chief Scientist of National Basic Research Project (973 Program, 2014) Recruitment Program of Global Experts (2010) Excellent Academic Leaders of Shanghai (2010) National Science Fund for Distinguished Young Scholars (2007) As an academic leader, Dr. Guo has served as Department Head for ten years, managing a department with over 100 faculty members and 1000+ students. Under his leadership, the department was promoted to the top tier in China and ranked among the top 40 in the world. He has secured significant research funding, including serving as Chief Scientist of the prestigious 973 Program in 2014 and receiving the National Science Fund for Distinguished Young Scholars in 2007. Dr. Guo has also been selected for the Recruitment Program of Global Experts in China (2010). Dr. Guo actively contributes to the academic community as an associate editor of IEEE Transactions on Parallel and Distributed Systems, IEEE Transactions on Cloud Computing, and Journal of Parallel and Distributed Computing. He has served as General/Program Chair for IEEE conferences and delivered keynote speeches at well-established conferences. His research group has developed practical technologies with industry impact, including 28 licensed patents, some of which have been transferred to companies like Alibaba.
Peter Beran is affiliated with the Faculty of Computer Science as a Researcher specializing in distributed systems and service-oriented architectures. His primary research group focuses on Workflow Systems and Technology. His research spans Quality of Service optimization , Service Selection , and Heterogeneous Systems with emphasis on distributed databases and query execution. Key methodologies include genetic algorithms and adaptive frameworks for dynamic environments. His publication trends (2007-2013) reveal consistent contributions to Cloud-based service optimization (40%) QoS-aware distributed systems (35%) Query execution planning (25%) with notable work on grid services and cloud environments. Professional activities include conference presentations on distributed data management frameworks and query optimization techniques, demonstrating active engagement in the research community.
Aleksandar Pavlovic is a Research Fellow at the Institute of Computer Science within the University of Applied Sciences Wiener Neustadt. His work focuses on knowledge graphs, declarative programming, and AI-enhanced systems for complex reasoning tasks. Primary Affiliation: Institute of Computer Science, University of Applied Sciences Wiener Neustadt Research Interests Knowledge Graph Reasoning and Embedding Datalog-based Semantic Query Systems AI for Production Planning Under Uncertainty Interoperability in Semantic Web Technologies Geometric Interpretation of Knowledge Graphs Neural-Symbolic Integration Recent Publications demonstrate expertise in combining classical logic with machine learning for knowledge graph analysis, SPARQL query optimization, and enterprise knowledge management systems. Key trends include geometric embeddings for knowledge graphs and decentralized AI planning. Projects include: 24/7 Digital : AI-powered care systems with remote support and climate-resilience guidelines (FFG-funded) IntelliProPS : AI-enriched production planning simulator for volatile manufacturing environments (COIN-program)
Mag. Rainer Baier is a Lecturer at the Department of Educational Science, Vienna University of Economics and Business (WU Vienna) . With 25+ years of teaching experience since 1999, he specializes in didactics of business informatics and Excel-based business intelligence tools. Current international teaching engagements: May 2025 - Tongji University (Shanghai) , February 2025 - Luiss University (Rome) , 2023-2025 - Universitas Gadjah Mada & Universiti Malaya Key collaborations: learn@wu learning platform , bm:bwk educational standards group Research & Teaching Focus : E-learning methodologies, CLIL (Content and Language Integrated Learning), Excel automation for business, Power BI applications, and cooperative negotiation skills. His work emphasizes practical integration of digital tools in business education. Recent Publications : 3 textbooks in 2024 on Microsoft Power Automate, Office 365 skills, and nursing informatics. 2023 works focus on Excel data ace training and CLIL didactics. Scientific Recognition : Diversitas 2022 Diversity Award Two Innovative Teaching Project Awards (2007, 2008) WU Cooperation Officer of the Year (2008) Advising & Grants : Project leadership in WU E-Learning Academy (2006-2008) and Corporate Sustainability Negotiation (2011). Collaborations with Microsoft tools (Power BI, Excel) in business education contexts. Labs & Teams : learn@wu educational platform development, bm:bwk educational standards committee member, and Office Management and Applied Computer Science teaching consortium with Hackl and Apfler.
Franz Aurenhammer is a University Professor (Univ.-Prof.) at the Institute of Machine Learning and Neural Computation, Graz University of Technology, Austria. He holds the academic title DI Dr. techn. and has been active in computational geometry research for several decades. His position as Full Professor was appointed in October 1992 at the Institute of Theoretical Computer Science, where he also served as head of the research group on algorithms, geometry, and optimization. Professor Aurenhammer earned his academic credentials at Graz University of Technology: his MS degree (Dipl. Ing.) in Technical Mathematics in April 1982, his PhD degree (Dr. techn.) in November 1984, and completed his Habilitation (Universitätsdozent) in Theoretical Computer Science in May 1989. Prior to his current position, he served as Assistant Professor at the Institute for Information Processing from January 1985 to April 1989, and held research positions including at the Free University of Berlin (April 1990 to May 1992). Aurenhammer's research focuses primarily on computational and combinatorial geometry, data structures and algorithms, and graph algorithms. His work has particularly emphasized Voronoi diagrams and straight skeletons, with numerous publications on these topics spanning several decades. His research has strong theoretical foundations while also addressing practical applications in computer science, optimization, and geometric modeling. Analysis of his recent publications reveals a continued focus on geometric structures, particularly Voronoi diagrams in various forms (including piecewise-linear farthest-site variants) and straight skeletons in both 2D and 3D contexts. His work often bridges theoretical computational geometry with practical applications in computer-aided design, shape analysis, and spatial data structures. The research demonstrates progression from fundamental theoretical work to increasingly sophisticated applications in 3D modeling and complex geometric structures. Professor Aurenhammer has been actively involved in research funding, with grants from major institutions including the Austrian Ministry of Science (BMWFK), Austrian National Bank (ÖNB), National Science Foundation (FWF), Austrian Academic Exchange Program (ÖAD), and the Special Research Council (SFB) 'Optimization and Control'. His current project FWF I1836-N15 (2015-2020) focuses on Voronoi diagrams as versatile data structures for spatial proximity problems. As an educator, Aurenhammer has supervised numerous MS and PhD theses in theoretical computer science and taught courses including Basic Data Structures & Algorithms, Languages and Automata, Design & Analysis of Algorithms, Computational Geometry, and Information Theory. His teaching responsibilities include Privatissimum courses on Algorithms and Geometry and Dissertation seminars. His international research collaborations span numerous institutions across Europe, the United States, Canada, Japan, Taiwan, Korea, and China, reflecting the global significance of his work in computational geometry. These collaborations have resulted in significant contributions to the field, particularly through the DACH project on Voronoi diagrams and related geometric structures.
Yannis Ioannidis is a Professor at the Department of Informatics & Telecommunications of the University of Athens. He also holds significant roles as President and General Director of the Athena Research & Innovation Center (since 2011) and Adjunct Researcher at the Institute for the Management of Information Systems (IMIS) within Athena RIC (since 2009). Professor, Department of Informatics & Telecommunications, University of Athens (2001-present) President & General Director, Athena Research & Innovation Center (2011-present) Adjunct Researcher, Institute for the Management of Information Systems (IMIS) (2009-present) Associate Professor, Computer Sciences Department, University of Wisconsin – Madison (1993-1998, with leave in 1997-1998) Assistant Professor, Computer Sciences Department, University of Wisconsin – Madison (1986-1993) His research spans multiple domains within Database Systems , including query optimization, distributed processing, and heterogeneous systems. He also focuses on Human-Computer Interaction (e.g., database user interfaces, data visualization), Scientific Experiment Management , Digital Libraries , and Data Mining . His work intersects social networking, user modeling, and context-aware computing. Ioannidis has received prestigious honors such as IEEE Fellow , ACM Fellow , and the Presidential Young Investigator (PYI) Award . Additional accolades include multiple teaching awards like the Chancellor's Distinguished Teaching Award and Students' Choice Professor of the Year . He has supervised 6 Ph.D. and 5 MS graduates, taught 7 courses in databases and human-computer interaction, and contributed extensively to academic service through program committee chairmanships, associate editorships, and participation in review boards. He also holds a patent.
Prof. Martin Gebser is a University Professor and Deputy Director at the Institute for Artificial Intelligence and Cybersecurity, University of Klagenfurt. His work bridges theoretical advancements in Answer Set Programming (ASP) with practical applications in industrial scheduling, semiconductor manufacturing, and explainable AI systems. Institute for Artificial Intelligence and Cybersecurity, University of Klagenfurt His research focuses on Answer Set Programming and its extensions for complex scheduling problems, particularly in semiconductor production. Key areas include: Multi-shot ASP solving for job-shop decomposition Hybrid AI systems integrating reinforcement learning and logic programming Explainable AI for battery health monitoring and semiconductor dispatching Recent publications emphasize temporal planning, constraint learning, and real-world data integration. He has developed customizable simulators and optimization frameworks for industrial applications.
Manuel Wimmer is a Lecturer in Business Informatics at TU Wien's Faculty of Informatics, specializing in model-driven engineering methodologies. His research develops foundations for model transformation, metamodeling, and interdisciplinary engineering. Research interests include model-driven software engineering, cyber-physical systems, web engineering, and industrial automation, with applications in smart production systems. Current work focuses on bridging IT/OT domains through standardized modeling approaches. Recent publications address quantum-edge cloud architectures, AI-enhanced modeling, and industrial security challenges. Article trends demonstrate strong focus on modeling language engineering, interoperability solutions, and quality assurance in complex systems. Leads the Christian Doppler Laboratory for Model-Integrated Smart Production and coordinates EU projects on low-code engineering platforms. Supervises doctoral research in model-driven technologies and software quality.
