جست‌وجوی استاد و پژوهشگر

Yang Laurence Tianruoمشاهده پروفایل

استاد

• Cyber-physical-social systems
• Big data computing and analytics
• Ubiquitous/pervasive computing
• +۳ مورد دیگر

Laurence Tianruo Yang is a distinguished academic holding dual roles as National Distinguished Professor at Huazhong University of Science and Technology (China) and W.F. James Research Chair at St. Francis Xavier University (Canada). He has been a Tenured Professor since 2009 and has held progressively senior positions since 1999. His expertise spans cyber-physical-social systems, big data analytics, and cloud computing. Education: B.E. in Computer Science (Tsinghua University), B.Sc. in Applied Physics (Tsinghua University), Ph.D. in Computer Science (University of Victoria). Research focuses on parallel/distributed computing, embedded systems, and IoT. He has published over 400 journal papers with 26,463 citations and an H-index of 80. Notable recognitions include IEEE Fellowships, the John B. Stirling Medal, and multiple best paper awards. He actively leads IEEE technical committees and has secured CAD$5M+ in research funding from NSERC, CFI, and Chinese national programs. Editorial roles include IEEE Transactions on Computers, IEEE Systems Journal, and Elsevier journals. He has organized over 10 international conferences and authored/co-authored 25+ books.

Marcus Hilbrichمشاهده پروفایل

استاد

• Distributed Systems
• Software Engineering
• Cloud Computing
• +۵ مورد دیگر

Marcus Hilbrich is a Professor in Computer Science with extensive academic experience across multiple institutions. His primary affiliation is Chemnitz University of Technology, where he held roles including Assistant Professor, Acting Professor of Software Engineering, and Research Assistant. He also served as Scientific Coordinator at Humboldt University of Berlin (SFB 1404 FONDA) from 2022–2024. Education: He earned a Doctor of Engineering (Dr.-Ing.) from Dresden University of Technology in 2015, focusing on job/user-centric monitoring in distributed environments. His diploma thesis (2008) explored performance analysis of parallel simulations using the SUN Niagara II architecture. Research Interests: Hilbrich specializes in distributed systems, software engineering, cloud computing, and workflow management. He investigates microservices architecture, resilience engineering, and scalable monitoring techniques. His work bridges theoretical foundations (e.g., formal methods for workflows) with practical applications in HPC and data analysis. Publications: He has authored/co-authored over 15 peer-reviewed articles, including key contributions on ßMACH software management guidance, validity constraints in data workflows, and microservices design patterns. His research often addresses interdisciplinary challenges in computational systems and software lifecycle management. Projects: Active involvement in third-party funded projects like SFC (Cloud Computing for Secure Financial Transactions), ECOUSS (parallel simulations), and WisNetGrid (knowledge networks in grids). His work often integrates performance analysis and system scalability. Labs/Teams: Central to his work is the SFB 1404 FONDA collaborative research center, focusing on foundational aspects of distributed heterogeneous environments.

Michael Kerberمشاهده پروفایل

استاد

• Computational Topology
• Algebraic Topology
• Computational Geometry
• +۴ مورد دیگر

Michael Kerber is a Professor at Graz University of Technology, Institute of Geometry, specializing in computational topology and geometry. His research bridges mathematical theory with applications in data analysis, focusing on persistent homology and geometric algorithms. PhD from Max Planck Institute for Informatics (2009) Postdoc positions: Max Planck Institute, Stanford University, IST Austria His work centers on designing efficient algorithms for topological data analysis, particularly: Persistent Homology 2-Parameter Persistence Geometric Filtrations Algebraic Curve Analysis High-Dimensional Sphere Packing Recent publications emphasize: Improved Delaunay bifiltration methods NP-hardness of interleaving distance computation Sparse Čech filtrations for big data Integration with graph neural networks He has co-developed key software tools: PHAT DIPHA HERA SOPHIA

• Translation Studies
• Translation Technologies
• Terminology Management
• +۲ مورد دیگر

Mag. Dr. Vesna Lusicky is a faculty member at the Department for Translation Studies , University of Vienna, where she currently serves as Vice-Director of Studies in the Translation Studies Directorate of Studies. She maintains regular office hours on Tuesdays 14:00–15:00 and can be reached by e-mail for appointments. Her teaching portfolio spans a broad spectrum of translation-oriented subjects. Core courses include Translation Management , Translation Technologies and the Language Industry , Terminology Work and Language Resource Management , and Technical Communication and Terminology . These offerings are delivered at both undergraduate and graduate levels, with multiple parallel groups scheduled each semester. Research & teaching interests are centred on the intersection of language, technology and professional practice, covering: Computer-assisted translation (CAT) tools and localization workflows Terminology management and multilingual knowledge resources Project management in the language services industry Technical writing and domain-specific communication No specific scientific awards or publications are listed in the provided source. At present, no advisees, collaborative laboratories, or funded projects have been disclosed in the available material.

Ranjan Rajivمشاهده پروفایل

استاد

• Internet of Things
• Edge computing
• Big data analytics
• +۷ مورد دیگر

Ranjan Rajiv is a Professor and Chair of the Internet of Things (IoT) at the School of Computing, Newcastle University, UK, serving as Academic Director (School’s Chair) from 2020–2024. He leads the Networked and Ubiquitous Systems Engineering (NUSE) Group and directs the Newcastle Urban Observatory. Previously, he held roles at CSIRO Australia, ANU, and UNSW. His research focuses on distributed systems, including IoT, edge computing, and sustainable computing. Education: Integrated MPhil/PhD from the University of Melbourne (2003–2008), BEng (Computer Engineering) from North Gujarat University. Early education in India included top academic distinctions. Research interests span IoT, cloud computing, big data analytics, and edge computing. He has secured over $68M in grants and published 300+ peer-reviewed articles. Awards include the IEEE TCSVC Rising Star Award (2019), TCCPS Early Career Award (2018), and multiple best paper recognitions. Leadership roles include editorial boards of IEEE Transactions on Cloud Computing, ACM Computing Surveys, and others. He is a Fellow of IEEE, Academia Europaea, and the Asia-Pacific Artificial Intelligence Association.

Maximilian Brunnerمشاهده پروفایل

پژوهشگر

• Numerics of PDEs
• Finite Element Methods (FEM)
• Contractive Iterative Solvers
• +۳ مورد دیگر

Maximilian Brunner is a Postdoc at TU Wien's Institute of Analysis and Scientific Computing (E 101), specializing in Numerics of Partial Differential Equations (PDEs). He holds a Dipl.-Ing. (MSc) and Dr.techn. (PhD) from TU Wien, with his doctoral thesis on On optimal adaptivity for semilinear PDEs earning the 2025 Study Prize from the Austrian Mathematical Society (ÖMG). His research focuses on adaptive finite element methods (FEM), iterative solvers for nonlinear PDEs, and cost-optimality analysis. He collaborates with Prof. Dirk Praetorius and contributes to projects funded by the Austrian Science Fund (FWF). Previously, he was a PhD student (2020–2024) and taught courses in numerical mathematics and scientific programming. His work bridges theoretical advancements in adaptive algorithms with practical computational efficiency, addressing challenges in nonsymmetric and semilinear PDEs. Education: PhD in Technical Mathematics, TU Wien (2024), supervised by Dirk Praetorius MSc in Technical Mathematics, TU Wien (2020), supervised by Winfried Auzinger Research Interests: His interdisciplinary work centers on developing adaptive FEM strategies for cost-optimal solutions to PDEs. Key areas include: Contractive iterative solvers for nonlinear systems Goal-oriented error estimation for targeted accuracy Quasi-optimal computational cost in adaptive algorithms His methods prioritize minimizing computational resources while maintaining solution fidelity, with applications to elliptic and semilinear PDEs. Awards: 2025 Study Prize (ÖMG) for PhD thesis Grants & Funding: FWF Projects P33216 and P28367 Vienna School of Mathematics membership (2020–present) Labs/Teams: Core member of the Numerics of PDEs research group, part of TU Wien's ASC unit. Active in collaborative projects with international conferences and workshops.

Sebastian Forsterمشاهده پروفایل

استاد

• Algorithms
• Graph Theory
• Network Science
• +۴ مورد دیگر

Sebastian Forster is a Professor at the University of Salzburg , affiliated with the Faculty of Digital & Analytical Sciences and the Department of Computer Science . He leads the Big Data Algorithms Group and holds administrative roles as Vice Dean, Local Coordinator of CIVIS Hub 5, and coordinator of the supplementary study programme "Informatikkompetenz für alle." His research focuses on algorithms for big and fast data, particularly distributed and dynamic algorithms applied to graphs, networks, and complexity theory. Education: Ph.D. in Computer Science (University of Vienna, 2011–2015) M.Sc. in Computational Intelligence (Vienna University of Technology, 2008–2011) B.Sc. in Computer Science (University of Passau, 2005–2008) Research Agenda: Forster's work addresses the theoretical and mathematical challenges of prior-free algorithms in the post-Moore's Law era. His key contributions include advancements in graph algorithms , fine-grained complexity , and network science . Recent publications span distributed Laplacian methods , dynamic graph sparsifiers , and approximate shortest path solutions , reflecting a blend of algorithmic design and hardness analysis. Scientific Awards: Heinz Zemanek Award (OCG) Award of Excellence (BMWFW) Academic Service: He has served on program committees for ICALP 2025, STACS 2024, FOCS 2023 , and other major conferences. He actively reviews for journals like Journal of the ACM and funding bodies such as BSF and ISF . Co-organized the Dagstuhl Seminar 22461 on Dynamic Graph Algorithms.

Pingali Keshavمشاهده پروفایل

استاد

• Programming Languages
• Parallel Computing
• High-Performance Computing
• +۴ مورد دیگر

Dr. Keshav Pingali is the W.A. 'Tex' Moncrief Chair of Computing and Professor of Computer Science at The University of Texas at Austin, where he also directs the Center for Grid and Distributed Computing at the Oden Institute. Previously, he held the India Chair of Computer Science at Cornell University (2003–2006) and served as a professor in Computer Science and Electrical Engineering at Cornell (1999–2006). He completed his B.Tech. at IIT Kanpur (1978), followed by S.M., E.E., and Sc.D. degrees from MIT (1983, 1986). Research Interests: Focuses on programming languages, compilers, and runtime systems for parallel computing, with emphasis on optimizing irregular applications in domains like graphics and data mining. His work addresses challenges in high-performance computing and multicore processor programming methodologies. Awards & Honors: ACM SIGPLAN Programming Languages Achievement Award (2024) ACM/IEEE CS Ken Kennedy Award (2023) IEEE Charles Babbage Award (2023) Foreign Member of Academia Europaea (2020) Fellow of ACM (2012), AAAS (2010), and IEEE (2010) NSF Presidential Young Investigator Award (1989–1994) President’s Gold Medal, IIT Kanpur (1978) Professional Activities: Keynote speaker at major conferences like ACM PACT (2018), HPCA/PPoPP/CGO (2016), and HIPEAC (2012). Served as editor-in-chief of ACM TOPLAS (2007–2010) and on NSF advisory committees. Currently teaches courses on compiler optimization and performance programming.

Bernhard Kerblمشاهده پروفایل

پژوهشگر

• Real-time graphics
• High-performance rendering
• Virtual Reality (VR)
• +۳ مورد دیگر

Bernhard Kerbl is a Researcher and Teaching Assistant at the Institute of Computer Graphics and Vision, Technical University of Graz (TU Graz). He holds a Master’s degree in Software Engineering and Economics. His research focuses on parallel and distributed processing, with special emphasis on adaptive rendering and GPU optimization under Prof. Dieter Schmalstieg and Dr. Markus Steinberger. His interests include real-time graphics, high-performance rendering, and Virtual Reality (VR). He contributes to teaching by organizing lectures on computer graphics. His recent work involves publications in areas like adaptive radiance caching and distributed rendering systems. Collaborations include projects with industry and academic partners, though specific grants or lab affiliations are not detailed in the provided texts.

• Optimizing Compilers
• Program Analysis
• Embedded Systems
• +۴ مورد دیگر

Jens Knoop is a Full Professor at TU Wien, leading the Department of Information Systems Engineering (E194) and the Research Unit Compilers and Languages (E194-05). His roles include Head of Institute for Information Systems Engineering and membership in the Curriculum Commission for Informatics. He specializes in compiler design, program analysis, and embedded systems, with a focus on worst-case execution time (WCET) analysis and formal methods. His research interests span optimizing compilers, programming languages, and real-time computing. Notable contributions include the Platin tool suite for WCET analysis and contributions to the T-CREST project on time-predictable multi-core architectures. He has authored and edited multiple influential publications, including proceedings of international conferences such as Code Generation and Optimization (CGO) and ARCS. Professor Knoop has supervised numerous theses, including works on effect systems in Haskell, mutation testing in Rust, and robotic systems. He has received the Most Influential PLDI Paper Award (2002) for foundational work in compiler optimization.

• Algorithms
• Graph Neural Networks
• Problem decomposition techniques
• +۴ مورد دیگر

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.

Minos Garofalakisمشاهده پروفایل

استاد

• Big Data Analytics
• Private Data Analytics
• Machine Learning
• +۳ مورد دیگر

Minos Garofalakis is a Professor at the School of Electrical and Computer Engineering , Technical University of Crete, and serves as Director of the Information Management Systems Institute at the Athena Research & Innovation Center in Athens. He has held senior research roles at Bell Labs, Intel Research, Yahoo! Research, and academic positions at UC Berkeley as an Adjunct Associate Professor. Currently, he is a Senior Research Consultant at Huawei Edinburgh Research Center and co-founder of Agora Labs , focusing on medical data privacy. Research Interests His work centers on Big Data Analytics , encompassing private data analytics , machine learning , federated analytics , and blockchain systems . He has pioneered advancements in data stream management , query optimization , and approximation algorithms , with applications in distributed systems and privacy-preserving technologies. Scientific Awards ACM Fellow (2018) IEEE Fellow (2017) Excellence in Research Award, Technical University of Crete (2015) FP7 Marie-Curie International Reintegration Fellowship (2010-2014) Bell Labs President’s Gold Award (2004) Central Bell Labs Teamwork Award (2003) Patents and Citations Garofalakis holds 29 issued US patents (36 filed) with applications in data management and analytics. His research has garnered over 16,000 citations on Google Scholar and an h-index of 69.

Karoński Michałمشاهده پروفایل

استاد

• Random discrete structures
• Probabilistic combinatorics
• Graph theory
• +۱ مورد دیگر

Michał Karoński is a Professor of Mathematics at the Faculty of Mathematics and Computer Science, Adam Mickiewicz University, Poznań, Poland, and serves as head of the Department of Discrete Mathematics. He has held visiting professorships at Emory University, The Johns Hopkins University, Purdue University, and Southern Methodist University since 1975, with ongoing engagements at Emory University since 1992. Research Focus: Discrete mathematics, random discrete structures, graph theory, and theoretical computer science. Leadership Roles: Editor-in-Chief of Random Structures & Algorithms (since 1990), Chairman of the Council of National Science Centre (2010–2016), and organizer of 17 bi-annual conferences on random structures. His research group in random structures gained international recognition in the 1970s. He has authored 60 publications, delivered over 30 plenary lectures, and collaborated globally at institutions like Microsoft Research, Bellcore, and BRICS. Scientific Awards: 2016 Medal 'Homini Vere Academico' (AMU Rector) 2013 Polonia Restituta Officer Cross (President of Poland) 1990 Minister of Science and Higher Education Prize His work spans probabilistic combinatorics, algorithm theory, and graph irregularity, with influential publications on stochastic Kronecker graphs, random intersection graphs, and distributed complexity in matchings.

Volker Mehrmannمشاهده پروفایل

استاد

• Numerical mathematics
• Matrix theory
• Control theory
• +۶ مورد دیگر

Volker Mehrmann is a full professor at the Department of Mathematics and Natural Sciences, Technische Universität Berlin. He previously served as Chair of the DFG Research Center MATHEON (2008-2016) and held faculty positions at TU Chemnitz (1993-2000) and RWTH Aachen (1990-1992). His career spans 40+ years, including roles at Universität Bielefeld (1980-1993) and visiting positions at Kent State University and IBM Scientific Center. Education: Habilitation in Mathematics (1988), PhD in Mathematics (1982), Diploma in Mathematics & Physics (1979), all from Universität Bielefeld Research Interests: Mehrmann's work focuses on numerical mathematics, particularly differential-algebraic equations (DAEs), matrix theory, control theory, and operator theory. His research includes nonlinear eigenvalue analysis, optimal control, model order reduction, and parallel computing for mathematical problems. He has authored over 787 citations (as of 2006) and pioneered numerical methods for unstructured nonlinear DAEs and structured polynomial eigenvalue problems. Scientific Trends: His publications reveal a progression from foundational work in linear quadratic control (1991) to modern challenges in nonlinear eigenvalue problems (2013), with consistent emphasis on DAEs, matrix theory, and numerical methods. Collaborations include major industrial partnerships with DaimlerChrysler, Audi, and CST GmbH. 2011: ERC Advanced Grant for Numerical Mathematics 2006-2013: Leadership in nonlinear eigenvalue problems 1999-2006: Development of SLICOT control theory software 1991-2005: Advancements in DAE analysis and control Honours: Mehrmann is a SIAM Fellow (2011), recipient of the Radon Lecture (2017), Gauss Lecture (2015), and ICIAM Plenary speaker (2015). He served as President of GAMM (2011-2013) and Vice President of the European Mathematical Society (2017-2018). Professional Service: He has held numerous leadership roles including Editor-in-Chief of Linear Algebra and its Applications (1999-), and advisory board positions at RICAM Linz (2014-), Fraunhofer ITWM (2013-), and CERFACS (2009-).

• Physical processes at Earth's surface
• Landscape evolution
• Fluvial processes
• +۵ مورد دیگر

Sean Douglas Willett is a Full Professor at ETH Zurich, Switzerland (since 2006), specializing in Earth surface processes and tectonic geomorphology. Previously, he held positions as Assistant/Associate Professor at the University of Washington (1998-2006), Assistant Professor at Pennsylvania State University (1994-1998), and completed postdoctoral research at Dalhousie University. He was also a Visiting Professor at the University of Bologna (2004-2005). Education: Ph.D. in Geophysics, University of Utah (1988) B.S. in Geology and Geophysics, University of Utah (1982, cum laude) Research Focus: Integrates numerical modeling with field observations to study landscape evolution, mountain-building processes, fluvial/glacial erosion dynamics, low-temperature thermochronology, and orogenic wedge mechanics. His work bridges tectonics, climate science, and surface processes. Publications: His recent articles (2012-2015) demonstrate advanced computational methods for landscape modeling and focus on Alpine/European tectonic evolution, river basin reorganization, and exhumation mechanisms. Earlier foundational work established mechanical models for mountain belts. Awards/Honors: Fellow, Canadian Institute for Advanced Research (1995-2014) Elected Member, Academia Europaea (2015) Professional Service: Extensive editorial contributions including Associate Editor for American Journal of Science and Terra Nova , organizer of TOPO-Europe conferences, and committee roles for European Science Foundation programs. His scholarly impact includes 5,700+ citations and h-index of 36 (2015).