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Xu DongView profile

Professor

• Artificial Intelligence
• Computer Vision
• Multimedia
• +3 more

Professor Dong Xu is a Tenured Professor in the Department of Computer Science at the University of Hong Kong (HKU), part of the School of Computing and Data Science. He holds a B.Eng. and Ph.D. from the University of Science and Technology of China (USTC). His career includes tenured roles at Nanyang Technological University and the University of Sydney, alongside postdoctoral research at Columbia University. His research focuses on Artificial Intelligence, Computer Vision, Multimedia, and Machine Learning , with applications in autonomous driving, AR/VR, medical image analysis, and video surveillance. Xu has authored over 150 papers in top journals and conferences, including CVPR, ICCV, and IEEE Transactions. He actively contributes to the academic community as an editorial board member for journals like ACM Computing Surveys and IEEE Transactions, and through leadership roles in conferences such as ACM Multimedia and ICME. Notable awards include Fellowships from IEEE and IAPR, and the IEEE Signal Processing Society Distinguished Lecturer title (2021–2022). Education: B.Eng. (USTC, 2001), Ph.D. (USTC, 2005) Professional Service: Program Coordinator of ACM Multimedia 2024, Guest Editor of over ten special issues.

Mihyun KangView profile

Professor

• Combinatorics
• Discrete Probability
• Algorithms
• +3 more

Mihyun Kang is a Professor in the Institute of Discrete Mathematics at Graz University of Technology (TU Graz), leading the Combinatorics Group. She holds significant academic positions and has been recognized with a Heisenberg Fellowship (German Research Foundation) and a Friedrich Wilhelm Bessel Research Award (Alexander von Humboldt Foundation). Her research focuses on combinatorics, discrete probability, and algorithms, with a specialization in random graph theory. She contributes to editorial boards, including Random Structures & Algorithms . Her research interests emphasize high-dimensional graphs, percolation processes, and structural properties of random graphs. She explores topics such as phase transitions, graph enumeration, and algorithmic applications in combinatorial problems. Her work bridges theoretical foundations with practical applications in algorithm design and probabilistic modeling. Dr. Kang’s scientific achievements include pioneering studies on hypergraphs, bootstrap percolation, and the evolution of random graph processes. Her recent publications highlight advancements in understanding graph components, connectivity thresholds, and universality phenomena in random structures. She collaborates widely, contributing to conferences and international initiatives like the SFB “Discrete random structures: enumeration and scaling limits.” Her professional activities include advising doctoral students and supervising research projects at TU Graz. She leads the Combinatorics Group, which hosts the Graz Combinatorics Seminar and actively engages in academic outreach. Her contributions extend to textbook authorship, including Diskrete Mathematik für die Informatik , and she maintains an active presence in discrete mathematics education and research.

• Data Mining
• Machine Learning
• Clustering Algorithms
• +3 more

Anna Beer is a researcher in the Faculty of Computer Science, specializing in data mining and machine learning with a focus on density-based clustering, spectral clustering, and interactive clustering frameworks. She holds a BSc and MSc in computer science and maintains an ORCID profile (https://orcid.org/0000-0002-6890-997X) for her research contributions. Research Themes: Development of clustering algorithms (e.g., DISCO, Scar, LUCKe), fairness in density-based clustering (FairDen), and applications to molecular dynamics and climate research (DROPP). Collaborations: Works with colleagues like Ira Assent, Christian Plant, and Lars Krieger, with recent contributions to conferences like ICLR 2025. Activities: Presented research on density-connectivity distance at a 2023 oral contribution. Publications: 9 publications since 2019, including 3 in 2025 and 6 in 2024, covering topics from cluster evaluation to deep active learning strategies.

• Databases
• Artificial Intelligence
• Query Optimization
• +1 more

Alexander Selzer is a PreDoc Researcher in Databases and Artificial Intelligence at Vienna University of Technology. His research focuses on query optimization, database systems, and AI-driven data processing. His work bridges theoretical computer science and practical database engineering, emphasizing efficient algorithms for modern data challenges. Recent projects explore machine learning applications in query performance and distributed computing frameworks. He mentors students in database optimization research, including projects on structure-guided query techniques and SQL-based system enhancements.

• Neurosymbolic AI
• Answer Set Programming
• Visual Question Answering
• +3 more

Nelson Nicolas Higuera Ruiz is a PreDoc Researcher at the Vienna University of Technology, affiliated with the Faculty of Informatics' Knowledge-Based Systems research group. His work bridges logic programming and deep learning for explainable AI. Research Focus: Neurosymbolic AI, Visual Question Answering (VQA), Answer Set Programming (ASP), and hybrid reasoning systems Projects: Leads optimization research in the LCS (2017–2025) project, developing neurosymbolic approaches for intelligent systems Key Contributions: Pioneering adaptive large-neighbourhood search algorithms for ASP optimization, modular neurosymbolic architectures, and contrastive explainability frameworks for VQA Collaborations: Active in international workshops and conferences including IJCAI, AAAI, and CLeaR, frequently collaborating with researchers like Thomas Eiter and Johannes Oetsch Publications: Focus on neurosymbolic integration, optimization algorithms, and explainability across AI, logic programming, and computer vision domains

Rafail OstrovskyView profile

Professor

• Algorithms
• Cryptography and Computer Security
• Theoretical Computer Science
• +3 more

Rafail Ostrovsky is a Professor of Computer Science and Mathematics at UCLA , affiliated with the Center for Information and Computation Security at the Henry Samueli School of Engineering and Applied Science. He earned his Ph.D. in Computer Science from MIT in 1992 under Silvio Micali. Research Focus: His work spans cryptography, algorithms, and theoretical computer science, emphasizing secure multi-party computation, zero-knowledge proofs, oblivious RAM, and high-dimensional data analysis. Applications include privacy-preserving data mining, systems security, and quantum cryptography. Article Trends: Recent publications address concurrent security protocols, robust secret sharing via expander graphs, and efficient multi-party computation. Topics intersect computational complexity, cryptographic reductions, and practical security implementations. Awards: Recipient of the 2018 RSA Conference Excellence in Mathematics Award , 2017 IEEE Fellow , and multiple IEEE/ACM honors. Holds 14 U.S. patents and over 290 refereed papers. Advising: Supervised 27 Ph.D. students, many now professors at top institutions. Served on 40+ program committees, including FOCS 2011 Chair. Labs: Leads the CICS research center, fostering interdisciplinary work in information security and cryptographic systems.

Zhang Yi-ChengView profile

Professor

• Econophysics
• Information economics
• Statistical physics
• +2 more

Zhang Yi-Cheng is a Full Professor of Theoretical Physics at the University of Fribourg, Switzerland, since 1992. His academic career includes visiting professorships at Nordita (Denmark) and INFN (Italy), and postdoctoral research at Brookhaven National Lab (USA). He specializes in interdisciplinary fields such as Econophysics , Statistical physics , and Complex network sciences , focusing on applications in financial markets, social systems, and global trade networks. His research explores topics like market dynamics, network structures, and algorithmic ranking systems. Notable awards include the 2011 Honorary Director of the Complexity Sciences Research Center and recognition as a 2011 Chinese '1000 Talents' awardee . His work bridges physics-based methodologies with socio-economic systems, addressing challenges in information-driven economies and networked societies. Zhang has contributed to influential studies on ranking algorithms, percolation theory in networks, and the interplay between economic complexity and trade. His interdisciplinary approach has led to advancements in understanding systemic risks, market inefficiencies, and the role of information in shaping global economic interactions.

Kurt MehlhornView profile

Professor

• Data Structures
• Graph Algorithms
• Computational Geometry
• +4 more

Kurt Mehlhorn is a distinguished academic in computer science, affiliated with the Universität des Saarlandes and the Max-Planck-Institut für Informatik . He has served as Professor of Computer Science since 1975 and as Director of the Max Planck Institute since 1990. His work bridges theoretical and applied computer science, with a focus on algorithmic design and implementation. Born : 29 August 1949, Ingolstadt, Germany Education : TU München (1968–1971), Cornell University (1971–1974), PhD in Computer Science (1974) Mehlhorn’s research spans foundational and applied domains, including Data Structures , Graph Algorithms , Computational Geometry , and Software Libraries . His contributions to algorithm engineering and EU-funded projects like ALCOM and GALIA have advanced the field. He co-founded Algorithmic Solutions GmbH in 1995 to commercialize algorithmic tools. Notable scientific awards : Leibniz-Award (1986) Humboldt-Award (1989) ACM Paris Kanellakis Theory and Practice Award (2011) Academia Europaea Erasmus Medal (2014) His editorial leadership includes roles at Algorithmica , SIAM Journal of Computing , and ACM Transactions on Algorithms . He has held advisory positions at institutions like IST Austria , ETH Zürich , and Simons Foundation , while directing research clusters such as the Cluster of Excellence in Multimodal Computing and the Indo Max Planck Center .

• Scientific Workflow Management
• Distributed Computing
• Numerical Linear Algebra
• +3 more

Wilfried Gansterer is a Professor at the Faculty of Computer Science, University of Vienna, leading the Theory and Applications of Algorithms research group. His work focuses on numerical algorithms, distributed computing, and machine learning, with notable contributions to graph neural networks and fault-tolerant systems. Active in projects such as Algorithmic Data Science for Computational Drug Discovery (2020–2028) and REPEAL (Resilience vs. Performance in Numerical Linear Algebra, 2016–2020). Research Interests: Dr. Gansterer’s expertise spans graph neural networks, matrix compression, adversarial defense mechanisms, and high-performance computing. His work addresses challenges in efficient computation, resilience against node failures, and optimizing distributed systems. Projects : Algorithmic Data Science for Computational Drug Discovery (2020–2028) REPEAL: Resilience vs. Performance in Numerical Linear Algebra (2016–2020) Verteiltes Rechnen (Distributed Computing, 2007–2014) Awards : 2023 Best Paper Award for work on Crossfire: An Elastic Defense Framework for Graph Neural Networks. Labs/Teams : Directs the Theory and Applications of Algorithms group, focusing on algorithmic innovation in distributed and high-performance computing environments.

Axel PolleresView profile

Professor

• Semantic Web
• Knowledge Graphs
• Ontology Reasoning
• +7 more

Axel Polleres is a full professor at the Institute for Data, Process and Knowledge Management in Vienna University of Economics and Business (WU Wien). He leads the department of Information Systems and Operations Management while maintaining active research in knowledge graphs, semantic web technologies, and ontology engineering. PhD and Habilitation from Vienna University of Technology Former positions at University of Innsbruck, Universidad Rey Juan Carlos, DERI Ireland, and Siemens AG Co-chair of W3C SPARQL working group Editorial board member for Semantic Web Journal and IJSWIS His research focuses on: Querying and reasoning over ontologies Graph schema languages (SHACL, SPARQL) Wikidata constraint formalization Ontology reuse in collaborative platforms Crisis management knowledge graphs FAIR data principles implementation Recent publications analyze knowledge graph evolution, constraint validation methodologies, and semantic web standardization efforts. Key topics include: OWL/RDF interoperability solutions Unit conversion systems for Wikidata Partition-based query processing frameworks Network resilience analysis for urban planning Open data platform discovery tools Temporal analysis of collaborative knowledge graphs He has co-organized major conferences like ISWC2023 and ESWC workshops while maintaining active roles in European research projects. Current work involves spatiotemporal knowledge graphs for city resilience and semantic web infrastructure development.

Martin BridsonView profile

Professor

• Geometric Group Theory
• Topology
• Spaces of Non-Positive Curvature
• +3 more

Martin Bridson serves as President of the Clay Mathematics Institute since 2018 and holds the Whitehead Professorship of Pure Mathematics at the University of Oxford's Mathematical Institute, where he has been a Fellow of Magdalen College since 2007. Previously, he was Head of Oxford's Mathematical Institute (2015-2018), Professor of Pure Mathematics at Imperial College London (2002-2007), and Professor of Topology at Oxford (1999-2002). His academic journey began with undergraduate studies at Hertford College, Oxford, followed by PhD work at Cornell University. Bridson's research centers on Geometric Group Theory, Topology, and Spaces of Non-Positive Curvature. His work explores the deep connections between algebraic structures and geometric properties, particularly focusing on metric geometry, profinite completions, and the topology of non-positively curved spaces. His influential monograph "Metric Spaces of Non-Positive Curvature" (co-authored with André Haefliger) has become a foundational text in the field. His recent publications (2024-2025) demonstrate continued leadership in geometric group theory, with significant contributions to profinite rigidity, CAT(0) geometry, and automorphism groups. These works reveal evolving research directions toward computational aspects of group theory and deeper connections with low-dimensional topology. Steele Prize for Mathematical Exposition (2020, with Haefliger) Fellow of the Royal Society (2016) Fellow of the American Mathematical Society (2015) Royal Society Wolfson Research Merit Award (2012) London Mathematical Society Whitehead Prize (1999) Bridson has secured major research funding including EPSRC Senior Fellowships (2007-2012, 1997-2002), EPSRC Platform Grants (2010-2015), and multiple NSF grants. His leadership extends to directing the Mathematical Institute at Oxford and presiding over the Clay Mathematics Institute, where he influences global mathematical research directions. His collaborative work spans institutions including Princeton, Geneva, and Lausanne, reflecting his international research network.

Torsten HoeflerView profile

Professor

• Deep learning Systems
• Parallel programming models
• High performance and datacenter networking
• +8 more

Torsten Hoefler is a Full Professor of Computer Science at ETH Zurich, Switzerland, with an adjunct appointment in Electrical Engineering. He previously held roles at the National Center for Supercomputing Applications (University of Illinois at Urbana-Champaign) and Indiana University. Full Professor of Computer Science, ETH Zurich (2020–present) Adjunct Professor of Electrical Engineering, ETH Zurich (2020–present) Member at Large, ACM SIGHPC Executive Committee (2013–present) Leadership roles in the MPI Forum and Blue Waters project His research focuses on performance-centric system design , with emphasis on scalable networking, parallel programming models, and performance modeling. Key contributions include the Slim Fly network topology, Data-Centric Python framework, and innovations in parallel graph computations and RDMA-based systems. Recent publications span topics like LLM training networks , quantization geometry , chiplet interconnects , and AI-driven climate modeling , reflecting his interdisciplinary approach combining HPC, AI, and hardware-software co-design. ACM Gordon Bell Prize (2019) ERC Consolidator Grant (2020) IEEE TCSC Award for Excellence (2019) SIAM SIAG/SC Junior Scientist Prize (2012) Latsis Prize of ETH Zurich (2015) He has received multiple best paper awards at top conferences (SC10, SC13, SC14, SC19, IPDPS'15, HPDC'15, OOPSLA'16) and contributed to MPI-3 standardization.

Werner ZornView profile

Professor

• Computer Networks
• Performance Analysis
• Networked Computer Systems
• +3 more

Prof. Dr. Werner Zorn is a renowned computer scientist and Professor of Communication Systems at the Hasso Plattner Institute (HPI) in Potsdam, Germany. With a foundational role in establishing Germany's early internet infrastructure and connecting China to the global internet, his work has been pivotal in shaping international network connectivity. His academic career spans from the University of Karlsruhe, where he was appointed Professor of Computer Science in 1979, to his current position at HPI since 2001. Education: He studied electrical engineering with a focus on communications at TH Karlsruhe (1962–1967) and earned his Dr.-Ing. with distinction in 1971. Research Focus: His research encompasses performance analysis of computing systems, computer networks, and the development of quantitative modeling methodologies such as FMC-QE (Fundamental Modeling Concepts for Quantitative Evaluation). His work bridges theoretical modeling with practical applications in network design and optimization. Publications & Articles: His publications reflect a deep engagement with internet history, network performance, and system modeling. Notable works include detailed accounts of China's first email connection and the evolution of the Chinese Academic Network (CANET), as well as innovative approaches to system performance modeling. Awards & Recognition: He has received numerous accolades, including the Order of Merit of the Federal Republic of Germany, induction into the Internet Hall of Fame, and the Chinese Government Friendship Award, underscoring his global impact. Current Projects: He leads projects like FMC-QE for hierarchical system modeling and the IT Services Atlas for implementing EU directives, alongside mentoring doctoral students in advanced network and system research.

• Diophantine Approximation
• Geometry of Numbers
• Parametric Approximation
• +4 more

Leonhard Summerer is an Associate Professor at the Faculty of Mathematics, Department of Mathematics . His research primarily focuses on Diophantine Approximation , Geometry of Numbers , and Parametric Approximation . His work explores the Approximation Property in parametric settings, Lattice Theory , and Linear Dependence in number theory. Recent publications include studies on Jarník’s identity, simultaneous approximation to multiple reals, and geometric interpretations of number-theoretic problems. He has authored numerous peer-reviewed articles and contributed chapters to educational books such as 77-mal Mathematik für Zwischendurch , emphasizing mathematical outreach and pedagogical innovation . Active in academic discourse, he has delivered talks on topics like Packings and Tilings in Z and Simultane Approximation m reeller Zahlen since 2006.

• Edge Computing
• Fog Computing
• Cloud Computing
• +4 more

Dragi Kimovski is a Habilitated Assistant Professor in Distributed Systems at Klagenfurt University, Austria, focusing on Edge Computing and AI. He previously held roles at the University of Innsbruck and the University of Information Science and Technology in Macedonia. His research spans Edge/Fog/Cloud computing, multi-objective optimization, and high-performance computing. He has coordinated major projects like 6GContinuum and KärtnerFog, and led initiatives such as DataCloud and ASPIDE. His teaching includes courses on Distributed Computing, Cloud Computing, and IoT. He is the co-creator of the Carinthian Computing Continuum and maintains a blog on Edge AI World. His work emphasizes sustainable and efficient computing solutions for emerging technologies. Education: Not explicitly listed in the provided text. Research Interests: Edge Computing, Fog Computing, Cloud Computing, Multi-objective Optimization, High-Performance Computing, AI in Distributed Systems. His work addresses challenges in resource management, latency reduction, and scalability across heterogeneous environments, with applications in healthcare, IoT, and 6G networks. Projects: 6GContinuum (Coordinator): Focuses on AI services over 6G networks. KärtnerFog (Scientific Coordinator): Develops adaptive Fog infrastructures over 5G. DataCloud (WP5 Leader): Manages Big Data pipelines on the Computing Continuum. ASPIDE (Scientific Coordinator): Advances exascale programming models for data processing. Teaching: Klagenfurt University: Courses include Distributed Computing, IoT, Cloud Computing, and Advanced Programming. University of Innsbruck: Taught Advanced Parallel and Distributed Systems. University of Information Science and Technology: Courses in High-Performance Computing and Network Architectures. Labs/Teams: Co-created the Carinthian Computing Continuum, an automated SDN testbed for Edge computing research. Active in interdisciplinary teams addressing extreme data processing and sustainable computing.