جست‌وجوی استاد و پژوهشگر

Wu Jieمشاهده پروفایل

استاد

• Mobile Computing
• Wireless Networks
• Cloud Computing
• +۵ مورد دیگر

Dr. Jie Wu is the Laura H. Carnell Professor and serves as Director of the Center for Networked Computing at Temple University's Department of Computer and Information Sciences. He has held leadership roles including Chair of the department (2009-2016), Associate Vice Provost for International Affairs (2015-2017), and Director of International Affairs in the College of Science and Technology. Previously, he was a distinguished professor at Florida Atlantic University (1989-2009) and held NSF program director roles (2007-2009). Education: PhD in Computer Engineering, Florida Atlantic University (1989) MSc in Computer Science, Shanghai University of Science and Technology (1985) BSc in Computer Science, Shanghai University of Science and Technology (1982) Research focuses on mobile/wireless networks, cloud computing, distributed systems, and cybersecurity. He has led NSF-funded projects and pioneered protocols for ad hoc networks. His work integrates machine learning with network trust mechanisms. Awards highlight his contributions: AAAS/IEEE Fellowships, ACM Distinguished Membership, and multiple best paper recognitions. He chairs major conferences like IEEE MASS and ICDCS, and serves on editorial boards for IEEE Transactions on Mobile Computing and others. Professional service includes leadership roles in IEEE Technical Committees, CCF (Chinese Computer Federation), and organizing over 20 international conferences. His lab at Temple University drives innovations in networked systems and distributed computing.

Willy Zwaenepoelمشاهده پروفایل

استاد

• Operating Systems
• Distributed Systems
• Database Replication
• +۴ مورد دیگر

Willy Zwaenepoel is a Professor and Dean of the Faculty of Engineering at the University of Sydney. He holds a B.S. from the University of Gent and M.S./Ph.D. from Stanford University. Previously, he served as Dean of the School of Computer and Communication Sciences at EPFL and was a faculty member at Rice University. His expertise spans operating systems, distributed systems, and high-performance computing. Education: B.S., University of Ghent, Belgium (1979) M.S., Stanford University (1980) Ph.D., Stanford University (1984) Research Interests: Dr. Zwaenepoel focuses on distributed systems, operating systems, and their applications in database replication, virtual machine performance, and software update mechanisms. His work includes foundational contributions to distributed shared memory (e.g., Treadmarks) and startups like iMimic Networking. Awards: ACM Fellow (2000) IEEE Fellow (1998) Fellow of the Australian Academy of Technical Sciences and Engineering (2020) Recipient of the IEEE Tsutomu Kanai Award (2007) Key Contributions: His research addresses challenges in distributed systems performance, such as latency reduction in key-value stores and efficient graph processing. Current projects explore I/O optimization in virtualized environments and causal consistency for geo-replicated systems. Students/Advising: Advises Ph.D. students and postdocs, including William in database replication. His mentorship led to the Rice University Teaching Award (2000).

Torsten Hoeflerمشاهده پروفایل

استاد

• Deep learning Systems
• Parallel programming models
• High performance and datacenter networking
• +۸ مورد دیگر

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.

• Edge Computing
• Fog Computing
• Cloud Computing
• +۴ مورد دیگر

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.

Diana Marinمشاهده پروفایل

پژوهشگر

• Computer Graphics
• Computational Geometry
• Point Cloud Processing
• +۳ مورد دیگر

Diana Marin is a PostDoc Researcher at TU Wien's Institute of Visual Computing & Human-Centered Technology. She holds a BSc, MEng, and Dr.techn. (PhD) in technical fields. Her research focuses on computational geometry, point cloud processing, and distributed computing for large-scale datasets. She has contributed to projects like Distributed Surface Reconstruction and RE:STOCK INDUSTRY. Education: BSc, MEng, Dr.techn. (PhD) Her work emphasizes curve and surface reconstruction from unorganized point clouds, leveraging proximity graphs and distributed computational methods. Key projects include optimizing surface reconstruction for massive datasets and developing parameter-free algorithms for connectivity analysis. Her publications span topics like SING neighborhood graphs, Riemannian manifold curve reconstruction, and distributed processing techniques. She collaborates on projects such as PostDisaster and Mixed Reality Lab.

• Database systems
• Large scale analytics
• Distributed systems

Beng Chin Ooi is a Lee Kong Chian Centennial Professor at the National University of Singapore (NUS), School of Computing. He has been with NUS since 1991, progressing through the ranks from Lecturer to his current distinguished position. He previously served as Dean of the School of Computing from 2007 to 2013 and as Director of the Smart Systems Institute from 2011 to 2021. His educational background includes: 1985: B.Sc. (1st Class Honors) from Monash University, Melbourne, Australia 1989: Ph.D. in Computer Science from Monash University, Melbourne, Australia Beng Chin Ooi's research focuses on database systems, large scale analytics, and distributed systems. His work has been instrumental in advancing the field of data management technology, particularly in the context of "big data" in large-scale parallel and distributed systems. He has made significant contributions to spatio-temporal and distributed data management, as well as pioneering research in distributed database management and peer-to-peer based enterprise quality management. His recent publications demonstrate a strong focus on blockchain technology, machine learning systems, and healthcare informatics. There's a clear progression from foundational database research to applications in emerging technologies like blockchain and AI. His work bridges theoretical advances with practical system implementations, as evidenced by multiple open-source projects associated with his publications. His notable awards include: 2021: NUS Research Recognition Award 2020: ACM SIGMOD E.F. Codd Innovations Award 2020: ACM SIGMOD Research Highlight Award 2019: VLDB Best Paper Award 2016: Fellow of Singapore National Academy of Science 2016: China Computer Federation Overseas Outstanding Contributions Award 2014: VLDB Best Paper Award 2014: IEEE TCDE CSEE Impact Award 2013: Singapore National Day's Public Administration Medal (Silver) 2013: NUS Outstanding Researcher Award 2012: IEEE Computer Society Kanai Award 2011: ACM Fellow 2011: Singapore President's Science Award 2009: IEEE Fellow 2009: ACM SIGMOD Contributions Award Throughout his career, Professor Ooi has demonstrated exceptional leadership in the database community, promoting high standards of database research at both international and regional levels. His BLOCKBENCH framework became the world's first benchmarking tool for private blockchains, and his work on data provenance on blockchain systems earned both the VLDB Best Paper Award and the ACM Research Highlight Award. He has led several major research initiatives, including the Smart Systems Institute at NUS. Professor Ooi has established multiple open-source projects including FabricSharp for blockchain data provenance and Cool for cohort online analytical processing. His research group has consistently produced high-impact work that bridges theoretical advances with practical system implementations.

• Systems
• Concurrency
• Memory Management
• +۵ مورد دیگر

Christoph Kirsch is a Professor and Chair of the Department of Computer Science at the University of Salzburg. He also serves as Chair of the Programming Research Laboratory at the Faculty of Information Technology, CTU Prague. His research focuses on systems, concurrency, memory management, and formal methods, with notable contributions including the Selfie educational software project and work on symbolic execution. He is a prolific author with over 50 publications in top venues like LCTES and EMSOFT. Education: Ph.D. in Computer Science (details not specified). His teaching includes courses on elementary computer science concepts and curricula development. He advises students such as Anna Bolotina and has graduated over a dozen PhD students. Research highlights include the Selfie system (self-referential C compiler and emulator), work on concurrency primitives like Scal and Timestamped Stack, and contributions to real-time systems (Logical Execution Time, Variable-Bandwidth Servers). His recent focus includes teaching digital thinking and evaluating eval in R programs. He has organized conferences like MPLR’24 and served on program committees for EuroSys and RTNS. His book Elementary Computer Science emphasizes foundational concepts for broad audiences.

• Database Theory
• Computational Logic
• Parameterized Complexity
• +۴ مورد دیگر

Reinhard Pichler is a Full Professor at the Vienna University of Technology (TU Wien), affiliated with the Faculty of Informatics and the Department of Databases and Artificial Intelligence . His research focuses on Database Theory , Computational Logic , and Parameterized Complexity . He leads multiple research projects like DeConquer (2023–2027) and HyperTrac (2018–2022), addressing challenges in query optimization and hypergraph decompositions. He holds the prestigious START Prize (2014–2022) for young researchers. His work spans theoretical foundations (e.g., hypertree decompositions) and practical applications (e.g., SPARQL query processing systems like SparqLog). He contributes to academic governance, serving on faculty councils and curriculum commissions. His research innovations bridge algorithmic theory and real-world database systems, emphasizing efficient query evaluation and tractability analysis. Key contributions include advancing fractional hypertree decompositions , SPARQL query optimization , and consistent query answering . His projects often involve collaborations with industry and international funders like the Austrian Science Fund (FWF) and Vienna Science and Technology Fund (WWTF). He actively publishes in top venues like Journal of the ACM , ACM Transactions on Database Systems , and Proceedings of the VLDB Endowment . His academic leadership extends to course design, teaching advanced topics like Complexity Theory and Theoretical Computer Science . He mentors doctoral students and oversees research teams exploring cutting-edge areas like uncertain databases and cloud-based computational social choice .

Oskar Mencerمشاهده پروفایل

استاد

• Numerical methods and simulations
• Imaging
• Discretization of space, time and value
• +۷ مورد دیگر

Oskar Mencer is a Professor in the Department of Computing at Imperial College London , where he has been a member of academic staff since 2000. He was also a Consulting Professor at Center for Computational Earth and Environmental Science , Stanford University (2009-2010). His research focuses on Multiscale Dataflow Computing , exploring the interaction of hardware and software systems through domain-specific representations, parallel programming, VLSI design, and compiler methodologies. He has contributed to fields including high-performance computing, FPGA optimization, and computational finance. Dr. Mencer's work has been recognized with a Special Award from Com.sult (2012), Imperial College Research Excellence Award (2007), and a Top EPSRC Advanced Fellowship (2001). He has received multiple best paper awards, including at ICFPT'08 and ASAP 2008, and his 2000 paper on stream architectures was recognized as historically significant in 2015. His publications demonstrate a strong emphasis on FPGA acceleration , custom architectures , and parallel processing across geophysics, finance, and neuroscience applications. Special Award for Dataflow Innovation (2012) Best Paper Award - ICFPT'08 Best Paper Award - ASAP 2008 He has served on technical committees for conferences such as FPL , DATE , and FPT , and leads the Computer Architecture Research Group (currently inactive).

• Medical Imaging
• MRI Reconstruction
• Real-Time MRI
• +۴ مورد دیگر

Martin Uecker is a Professor at the Institute of Biomedical Imaging at TU Graz. His research focuses on advanced MRI reconstruction techniques, real-time imaging, and open-source software tools like the Berkeley Advanced Reconstruction Toolbox (BART). He specializes in developing methods for fast and accurate medical imaging, including applications in cardiac MRI, fetal brain imaging, and disease monitoring. His work emphasizes reproducibility, quantitative imaging, and clinical translation. Key research areas include generative models for MRI reconstruction, model-based inversion of the Bloch equations, and interactive real-time MRI systems. His team collaborates on projects involving hardware-software integration, such as portable MRI scanners and MRI-guided interventions. Notable contributions include advancements in multi-echo radial FLASH techniques, motion-resolved T1 mapping, and Bayesian uncertainty estimation in imaging. Uecker’s publications highlight innovations in accelerating MRI acquisition and reconstruction, with applications in pulmonary function assessment, neonatal imaging, and cardiovascular diagnostics. His work bridges theoretical physics, computational methods, and clinical practice, fostering open-source frameworks to democratize access to cutting-edge imaging tools.

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

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.

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.