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Gabriel CiobanuView profile

Professor

• Membrane Computing
• Natural Computing
• Distributed Systems
• +6 more

Gabriel Ciobanu is a Professor at Alexandru Ioan Cuza University of Iasi, Romania, and a Senior Researcher at the Romanian Academy, Iasi. He has held various academic positions internationally including as a Visiting Professor at Newcastle University (UK) from 2010-2015 and as a Research Fellow/Professor at the National University of Singapore (2000-2004). His educational background includes PhD studies at A.I.Cuza University and Edinburgh University (1990-1994) under the mentorship of Robin Milner, and his undergraduate studies in the Faculty of Mathematics and Computer Science at A.I.Cuza University of Iasi (1977-1982). Professor Ciobanu's research focuses on Membrane Computing and Natural Computing , Distributed Systems Models including process calculi with emphasis on semantics, behavioral equivalences, logics, and verification. He has made significant contributions to bridging membrane computing and process calculi, and to the Foundations of Mathematics and Computer Science through his work on Finitely Supported Mathematics. His research has applications in theoretical computer science, formal methods, and computational biology. His publication record shows a consistent research trajectory focusing on theoretical computer science with applications to natural computing, membrane systems, process calculi, and finitely supported structures. Recent work (2023-2025) continues to explore these areas with increasing focus on multi-agent systems, continuation semantics, and applications to medical systems and reaction systems. Scientific Awards and Recognition 2013 Grigore Moisil Award, Romanian Academy (as co-author of "Mobility in Process Calculi and Natural Computing", Springer) 2010-2013 Member of the National Research Council (CNCS) in Romania 2008-2010 Royal Society of London Joint International Project (Newcastle University, School of Computing) 2004 Octav Mayer Award for Scientific Achievements, Romanian Academy of Sciences, Iasi branch 2000 Grigore Moisil Award of the Romanian Academy of Sciences for results in Theoretical Computer Science 1995-1996 Japan Society for the Promotion of Science Fellowship (Tohoku University and Kyoto University) 1994 DAAD Research Fellowship (Institute of Computer Science, University of Kiel) 1991-1992 Royal Society of London and Romanian Academy Fellowship (University of Edinburgh) Professor Ciobanu has supervised 8 PhD students and numerous master's students. He has served as Editor-in-Chief of the Scientific Annals of Computer Science since 2006 and has been a guest editor for special issues of several international journals. He has collaborated with researchers from numerous countries including UK, France, Netherlands, Spain, Italy, Russia, China, Singapore, and India. He has been involved in various research projects and has spent research periods at prestigious institutions worldwide including Edinburgh University, Universite de Paris XI, CWI and VU Amsterdam, Tohoku and Kyoto University, National University of Singapore, and Newcastle University.

Johannes Peter WallnerView profile

Associate Professor

• Knowledge Representation and Reasoning
• Artificial Intelligence
• Argumentation
• +7 more

Johannes Peter Wallner is an Associate Professor at Graz University of Technology (TU Graz), working in the Institute of Software Engineering and Artificial Intelligence within the Faculty of Computer Science and Biomedical Engineering. He leads the Knowledge Representation and Reasoning (KRR) research group and has previously been a researcher at TU Wien's DBAI group and the Constraint Reasoning and Optimization group at the University of Helsinki. Dr. Wallner's research focuses on knowledge representation and reasoning, artificial intelligence, argumentation, abduction, belief change, inconsistency handling and measurement, computational social choice, computational complexity, Boolean satisfiability, and answer set programming. His work bridges theoretical foundations with practical applications, particularly in developing computational models for argumentation systems. He has made significant contributions to structured argumentation frameworks, including assumption-based argumentation and ASPIC+. His recent publications demonstrate a strong trend toward advancing algorithmic approaches to probabilistic argumentation, abstraction techniques in argumentation systems, and applications of argumentation in domains like healthcare. He has been particularly active in exploring the computational complexity of various argumentation semantics and developing efficient algorithms for reasoning tasks. Dr. Wallner has received multiple prestigious awards including being selected for the IJCAI 2024 Early Career Track (only 12 researchers globally selected), being named a Top Scholar by ScholarGPS in 2024 (top 0.5% worldwide in AI), and receiving the AI 2000 Most Influential Scholar Honorable Mention in Knowledge Engineering in 2021 and 2022. As Principal Investigator, Dr. Wallner has secured significant research funding from the Austrian Science Fund (FWF), including two major projects: "A Novel Computational Workflow for Argumentation in AI" (grant P 35632, 358,848 €) and "Extending Belief Change to Advance Dynamics in Argumentation" (grant P30168-N31, 353,438 €). He is highly active in the academic community, serving on program committees for major AI conferences including AAAI, IJCAI, KR, and ECAI, and was a member of the Program Committee Board of IJCAI (2022-2024). He leads the Knowledge Representation and Reasoning (KRR) research group at TU Graz, which develops both theoretical foundations and practical implementations for computational argumentation systems. The group has contributed to several software systems including CEGARTIX (a SAT-based argumentation system), Vispartix (visualization of argumentation frameworks), ADFsys (an ASP-based argumentation system for abstract dialectical frameworks), and others that implement various argumentation frameworks.

Anne-Marie KermarrecView profile

Researcher

• Gossip-based networking
• P2P systems
• Social Networks
• +6 more

Anne-Marie Kermarrec is a Senior Researcher at INRIA (France), with prior roles at Microsoft Research (UK) and the University of Rennes 1 (France). Her work focuses on decentralized systems, including gossip protocols, peer-to-peer networks, social networks, and collaborative filtering. PhD in Computer Science (Rennes, 1996) Her research spans epidemic algorithms, content-based search in large-scale networks, and scalable group communication. She pioneered gossip-based peer sampling and multicast infrastructures like Scribe and SplitStream. Her publications highlight applications in decentralized news recommendation (AllYours), network coding, and privacy-preserving social platforms (Gossple). Key article trends include gossip protocols , P2P systems , social network analysis , decentralized storage , and collaborative filtering . She received the Michel Monpetit Award (2011), ERC Starting Grant (GOSSPLE, 2008-2013), and an ICDCS Best Paper Award (2010). Michel Monpetit Award (2011) ERC PoC AllYours (2013) ERC Starting Grant GOSSPLE (2008-2013) ICDCS Best Paper Award (2010) Kermarrec led program committees for major conferences (e.g., EuroSys, Middleware) and chaired the ACM Software System Award. Her software contributions include AllYours (news recommender), GossipLib (gossip library), and GossipPeer (P2P platform maintenance).

Silvia MikschView profile

Professor

• Visual Analytics
• Information Visualization
• Interaction Design
• +6 more

Silvia Miksch is a Full University Professor of Visual Analytics at TU Wien's Faculty of Informatics, leading the CVAST Center. She holds a PhD from the University of Vienna and has held roles including Head of the Department of Information and Knowledge Engineering at Danube University Krems. Her research focuses on Visual Analytics, Information Visualization, Temporal Data Analysis, and Medical Informatics. She has supervised numerous PhD and Master’s students, with notable advisees including Ignacio Baltazar Pérez Messina and Davide Ceneda. Her work bridges theory and practice, addressing challenges in Visual Analytics for healthcare, business intelligence, and digital humanities. Awards include the IEEE VGTC Technical Achievement Award (2023) and induction into the IEEE Visualization Academy (2020). She actively contributes to conferences like IEEE VIS and EuroVis as program chair and steering committee member. Her projects, such as 'VisuExplore' and 'DisCo', have received recognition for advancing visualization in medical and cultural domains. Key research areas include guidance-enriched systems, network visualization, and temporal reasoning. She explores applications in fraud detection, cultural heritage analysis, and pandemic data visualization. Her lab's tools, like 'Hermes' and 'COVIs', exemplify task-driven design for real-world data challenges.

• Formal Verification
• Probabilistic Systems
• Game Theory
• +5 more

Krishnendu Chatterjee is a Professor at the Institute of Science and Technology Austria (IST Austria) , Department of Computer Science. His research spans formal verification, probabilistic systems, game theory, and evolutionary dynamics, with over 300 peer-reviewed publications in top venues such as DISC, AAAI, LICS, PNAS, Nature , and Journal of the ACM . His research focuses on developing theoretical foundations and practical algorithms for analyzing complex systems, including Markov decision processes, stochastic games, probabilistic programs, and evolutionary models. He has made significant contributions to topics such as reachability analysis, termination of probabilistic programs, synthesis of controllers, and evolutionary game dynamics. Chatterjee's work is highly interdisciplinary, bridging computer science, mathematics, and biology. He has collaborated extensively with leading researchers worldwide and has been involved in editorial roles and program committees for major conferences in formal methods and theoretical computer science.

Miroslav StankovicView profile

Researcher

• Probabilistic Programming
• Invariant Synthesis
• Bayesian Networks
• +3 more

Miroslav Stankovic is a researcher at TU Wien's Research Area Cyber-Physical Systems , focusing on probabilistic programming, invariant synthesis, and moment-based analysis of probabilistic loops. His work bridges theoretical computer science and machine learning, particularly in analyzing Bayesian networks and distribution recovery.

John PallisterView profile

Adjunct Professor

• Volcanology
• Volcanic emergency
• Volcano monitoring
• +7 more

John Pallister is a Research Geologist at the USGS Cascades Volcano Observatory and leader of the Next-Generation Volcano Hazard Assessment project. He previously served as Chief of the USGS-USAID Volcano Disaster Assistance Program (VDAP) from 2004-2018 and has held adjunct professor positions at multiple universities worldwide including University of Colorado, University of Arizona, Portland State University, Nanyang Technical University, Université Blaise Pascal, University of Pittsburgh, and University of Hawaii Center for the Study of Active Volcanism. Ph.D., 1980, Geology - University of California, Santa Barbara, CA B.Sc., 1974, Geology - Emory University, Atlanta, GA Federal Executive Institute, U.S. Federal Executive Qualification, 1996 Dr. Pallister's research spans volcanology, volcanic emergency response, monitoring techniques, forecasting methodologies, and petrology. His work focuses on improving volcano hazard assessment and early warning systems through innovative monitoring approaches and international collaboration. He has been instrumental in developing best practices for volcano observatories worldwide and has contributed significantly to understanding volcanic processes during major eruptions including Mount St. Helens, Pinatubo, Merapi, and Chaitén. His expertise bridges scientific research with practical disaster risk reduction strategies. His publication record demonstrates consistent contributions to volcanic hazard assessment, eruption forecasting, and monitoring technologies. The articles show an evolution from fundamental petrologic studies of ophiolites and magma chambers to applied research on eruption forecasting, satellite monitoring techniques, and volcano observatory best practices. A clear trend emerges toward increasingly collaborative, interdisciplinary research focused on practical applications for volcanic risk reduction. U.S. Geological Survey: G.K. Gilbert fellowships for research on Precambrian Ophiolites (1984-1986) U.S. Geological Survey: G.K. Gilbert fellowships for petrologic studies of Mount Pinatubo (1994-1995) 1992 University of Arizona: Lowell Distinguished Field Geologist 1999 U.S. Vice Presidential Hammer Award for work on the National Atlas 2000 U.S. Geological Survey Customer Service Award University of California, Santa Barbara: Distinguished Alumnus Award 2006 U.S. Department of Interior (DOI) Distinguished Service Award 2016 Samuel J. Heyman Service to America Medal, Finalist Dr. Pallister has advised numerous graduate students across multiple institutions, serving on PhD committees for research on mantle xenoliths, caldera petrology, geomorphology, and remote sensing applications in volcanology. His policy contributions include serving on Science and Program Committees for USGS-INGV-IAVCEI Volcano Observatory Best Practices Workshops, providing external advisory services for the DOMERAPI project on Merapi Volcano, and delivering briefings to high-level officials including the Indonesian Vice President and Chilean President Michelle Bachelet during volcanic crises. He has testified before U.S. Congress on geologic hazards and mapping. As leader of the Next-Generation Volcano Hazard Assessment project and former Chief of VDAP, Dr. Pallister directs teams focused on improving volcanic crisis response capabilities worldwide. His work with the USGS Cascades Volcano Observatory involves monitoring active volcanoes in the Pacific Northwest, while his international collaborations through VDAP have strengthened volcano monitoring capabilities in numerous countries facing volcanic threats.

• Formal Methods
• Cyber-Physical Systems
• Probabilistic Programming
• +4 more

Ezio Bartocci is a Full Professor in Formal Methods for Cyber-Physical Systems Engineering at TU Wien's Faculty of Computer Science. He leads the Trustworthy Cyber-Physical Systems (TrustCPS) Group within the Cyber-Physical System Research Unit. His research focuses on formal verification, probabilistic systems, and runtime monitoring, with applications in autonomous systems, safety-critical software, and embedded systems. Roles & Affiliations: Full Professor, TU Wien (100% research focus) Principal Investigator in projects funded by EU, WWTF, FFG, and industry partners Chair of the Curriculum Commission for Computer Engineering Editor-in-Chief of the Formal Methods in Outer Space series Research Interests: Formal methods for CPS: verification, synthesis, and runtime monitoring Probabilistic programming and loop analysis Temporal logic specifications and mining Automated tools for safety-critical systems (e.g., Polar, MoonLight) Applications in healthcare, robotics, and autonomous vehicles Key Projects: ProbInG (2020–2025): Analyzing probabilistic loops ARTIST (2021–2026): AI and robotics safety EdgeAI (2022–2025): Optimizing embedded processing TAIGER (2023–2027): Trustworthy AI and CPS Grants & Funding: €10M+ secured from EU Horizon 2020, WWTF, FFG, and industry partners like TTTech Auto AG. Academic Leadership: Teaches courses on logical methods, CPS engineering, and scientific research at TU Wien. Supervises PhD students in formal methods and CPS domains. Tools Developed: Polar (probabilistic loop analyzer), MoonLight (spatio-temporal monitoring), and FIM (fault injection tool).

• Algorithms
• Graph Neural Networks
• Problem decomposition techniques
• +4 more

Matthias Paul Lanzinger is an Assistant Professor at the Technische Universität Wien's Faculty of Informatics, Department of Database and Artificial Intelligence. His research focuses on algorithms, graph neural networks, hypergraph decomposition techniques, parameterized complexity, and computational logic. He leads projects like 'DeConquer' (Vienna Science Fund) and 'HyperTrac', exploring efficient query processing and hypergraph-based algorithms. Research interests include theoretical computer science, database systems, and applying logical frameworks to solve complex computational problems. Recent work emphasizes hypertree decompositions, fuzzy Datalog, and graph motif analysis via the Weisfeiler-Leman test. He co-edited the 2024 Datalog-2.0 workshop proceedings and has supervised students on topics like column-store performance and graph query languages. His publications span venues like ACM Transactions on Database Systems, ICLR, and IJCAI, highlighting contributions to algorithmic efficiency, database theory, and logical reasoning systems. Active in academic service, he teaches courses on database systems, scientific research, and advanced topics in informatics.

• Software Engineering
• Machine Learning
• Static Code Analysis
• +3 more

Markus Böck is a PreDoc Researcher at the Software Engineering department of Technische Universität Wien (TU Wien), Austria. His academic work focuses on the intersection of software engineering and machine learning , particularly in performance prediction and probabilistic program analysis . He contributes to automated code analysis and intelligent software systems research. Role: PreDoc Researcher Department: Software Engineering, TU Wien Contact: markus.h.boeck@tuwien.ac.at His research explores: Language-agnostic static analysis of probabilistic programs Context-dependent performance prediction from source code Interactive machine learning systems for software engineering Distributional reinforcement learning applications Code-based performance modeling Program analysis for probabilistic systems Key publication trends include: Advancing probabilistic program analysis (2024-2025) Performance prediction techniques (2022-2023) Reinforcement learning innovations (2020-2022) Application of machine learning to software engineering challenges Game theory algorithm optimization (2025)

Javier EsparzaView profile

Professor

• Theoretical Computer Science
• Software Verification
• Model Checking
• +9 more

Javier Esparza is a Professor and Chair of Foundations of Software Reliability and Theoretical Computer Science at the Technical University of Munich (TUM), Germany. He has held academic positions at several prestigious institutions including the University of Stuttgart, University of Edinburgh, and Technische Universität München since 1990. His work focuses on theoretical computer science with applications in software verification and formal methods. His educational background includes: M.S. in (Theoretical) Physics from the University of Zaragoza (Spain, 1987) Ph.D. in Computer Science from the University of Zaragoza (Spain, 1990) Habilitation in Computer Science from the University of Hildesheim (Germany, 1994) Professor Esparza's research interests span multiple areas of theoretical computer science and formal methods. He has made significant contributions to the fields of software verification, model checking, and Petri nets. His work on algorithms for the design and verification of reactive and distributed systems has been particularly influential. He has developed theoretical foundations and practical tools for analyzing systems with infinitely many states, pushing the boundaries of what can be formally verified. His research on formal models for distributed systems, particularly Petri nets and process algebras, has provided new insights into concurrency theory. Additionally, his work on the analysis of probabilistic systems and applications of linear and constraint programming to verification problems has opened new avenues for research. His recent publications demonstrate a continued focus on fundamental problems in verification and theoretical computer science, with particular emphasis on population protocols, model checking techniques, and theoretical foundations of distributed computing. His work bridges the gap between theoretical insights and practical applications in software reliability. His scientific achievements have been recognized with several prestigious awards: Doctor honoris causa in Informatics, Masaryk University (2009) Dissertation prize, University of Zaragoza (1990) TeachInf Award for best Bachelor course at TU München (2009) TeachInf Award for best Master course at TU München (2010) Diploma for excellent Teaching, TU München (2011) Member of Academia Europaea (2011) Professor Esparza has successfully advised numerous PhD students who have gone on to make their own significant contributions to computer science. His research has been consistently supported by competitive grants from major funding bodies including the German Research Council (DFG), the British Engineering and Physical Sciences Research Council, and the European Union. His research projects have often involved international collaborations, reflecting the global recognition of his work. He leads a vibrant research group at TUM focused on theoretical computer science and verification. The group has developed several influential software tools including Rabinizer, Peregrine, Owl, and Strix, which are widely used in both academia and industry for verification tasks. His group maintains strong collaborations with research institutions worldwide, particularly in Europe.

• Bayesian Statistics
• Time Series Analysis
• Econometrics
• +3 more

Gregor Kastner is Professor and Deputy Head of the Institute of Statistics at the University of Klagenfurt. His research focuses on Bayesian statistics, time series analysis, econometrics, and computational methods, with applications in finance, economics, and environmental modeling. He develops statistical software including packages for stochastic volatility modeling in R. Kastner's methodological work centers on Bayesian inference for high-dimensional problems, developing efficient computational algorithms for complex models. His applied research examines volatility dynamics in financial markets, macroeconomic forecasting, and spatial analysis of economic indicators. Recent projects include Bayesian nonparametric clustering for evaluating agricultural subsidies in Europe, sparse vector autoregressions for high-dimensional forecasting, and stochastic volatility models for commodity markets. He maintains active collaborations across economics, finance, and environmental science disciplines.

Milo TovaView profile

Professor

• Database Management
• XML and Semi-Structured Information
• Data Integration
• +3 more

Tova Milo is a Full Professor and Head of the Department of Computer Science at Tel Aviv University, where she has held academic roles since 1995. She specializes in database systems, XML, data integration, and crowd-sourcing. Her research bridges theoretical foundations and practical applications in data management. Education: Ph.D. in Computer Science from Hebrew University (1992). She has led major initiatives such as the ERC Advanced Investigators grant (MoDaS project) and holds ACM Fellow status. She chairs key committees like the ACM SIGACT-SIGMOD PODS executive committee and has organized over 50 international conference programs. Research interests focus on database management, XML, data-centric business processes, and leveraging crowd-sourcing for data tasks. Her work has been recognized with the ACM PODS Test-of-Time Award (2010) and an IBM Faculty Award (2008). Grants and funding include over 20 awards from the European Union, US-Israel Binational Science Foundation, and industry partners like IBM and Microsoft. She contributes to editorial boards of ACM Transactions on Database Systems and The VLDB Journal.

• Statistical Modeling
• Machine Learning
• Data Clustering
• +3 more

Lukas Sablica, Ph.D., is a researcher affiliated with the Department of Statistics and Mathematics at WU Vienna University of Economics and Business. His work focuses on statistical methodology, computational statistics, and software development for statistical analysis. He is particularly known for contributions to probabilistic modeling, distribution sampling techniques, and the development of R packages such as circlus , mistr , and watson , which support advanced statistical analyses including circular/spherical clustering, mixture distributions, and Watson distribution modeling. Research interests include mathematical analysis of special functions, algorithmic approaches to distribution sampling, and applications of machine learning in environmental sensor data analysis. His interdisciplinary work bridges theoretical statistics with practical software solutions. Key contributions include methods for efficient sampling from complex distributions (e.g., PKBD, Watson), bounds analysis for Kummer’s functions, and machine learning models for estimating resource usage (e.g., EcoShower project). Collaborations involve experts in environmental science, computer science, and applied mathematics.

Gregory GutinView profile

Professor

• Combinatorial Optimization
• Algorithms
• Graph Theory
• +2 more

Gregory Gutin is a Professor of Computer Science at Royal Holloway, University of London, UK. He has held academic positions at Brunel University (Lecturer in Mathematics, 1996), Odense University (Visiting Lecturer in Computer Science, 1995; Postdoctoral Researcher, 1993), and was a PhD student at Tel Aviv University's School of Mathematics (1991). His career spans roles as a School Teacher in Gomel (Byelorussia, 1979), Researcher in Byelorussian institutions (1982-1987), and academic staff in the UK, Denmark, and Israel. He earned a PhD in Mathematics from Tel Aviv University, with prior research roles in Byelorussia (geology, oil, mathematics). His work bridges theoretical and applied computer science, focusing on combinatorial optimization, parameterized algorithms, and information security. Dr. Gutin's research centers on combinatorial optimization and parameterized algorithms , with applications in graph theory , constraint satisfaction , and access control in information security. His publications address arc routing problems, workflow satisfiability, and probabilistic methods for parameterized complexity, contributing both to foundational theory and practical implementations. His selected publications highlight a focus on fixed-parameter tractable algorithms for constraint satisfaction, arc routing in operations research, and access control mechanisms. These works solved open problems in algorithm design and influenced subsequent research in parameterized complexity and security systems. Best Paper Award at ACM SACMAT 2016 Best Paper Award at ACM SACMAT 2015 Royal Society Wolfson Research Merit Award 2014 Kirkman Medal 1996 Wolf Prize for PhD Students 1992 Dr. Gutin has collaborated extensively with researchers like Magnus Wahlstrom, Anders Yeo, and David Karapetyan. His work on workflow satisfiability introduced novel constraint classes used in access control systems, and he co-authored the influential textbook Digraphs: Theory, Algorithms and Applications (2009). The Royal Society award in 2014 recognized his sustained contributions to algorithmic research.