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Francois TrahayView profile

Associate Professor

• High Performance Computing
• Storage Systems
• Parallel and Distributed Systems
• +2 more

François Trahay is an Associate Professor at Telecom SudParis, affiliated with the SAMOVAR research laboratory. His research focuses on high-performance computing systems, storage optimization, and performance analysis tools for parallel and distributed environments. He completed his PhD at Université Bordeaux I (2009) and Habilitation (HDR) at Institut Polytechnique de Paris (2021). Research Interests: Trahay specializes in optimizing storage systems (SSDs, RAID configurations), developing performance analysis frameworks (e.g., EZTrace, NumaMMA), and enhancing energy efficiency in HPC. Key areas include I/O performance, parallel runtime systems, and adaptive computing for machine learning workloads. Publication Trends: His recent work (2018–2025) demonstrates strong focus on: (1) SSD/RAID management techniques for modern storage hardware, (2) HPC performance tools for tracing and analysis, and (3) optimization strategies for distributed deep learning systems. Laboratory Affiliation: Member of SAMOVAR Laboratory (UMR CNRS), conducting research in distributed systems, networks, and computational efficiency.

Alan J. SmithView profile

Professor

• Computer Architecture
• Computer Engineering
• Operating Systems
• +4 more

Alan J. Smith is a Professor in the Electrical Engineering and Computer Sciences department at the University of California, Berkeley, within the College of Engineering. With a distinguished career spanning several decades, he has made significant contributions to computer architecture, system performance analysis, and memory systems. Dr. Smith received his S. B. from MIT and a Ph.D. from Stanford University. His educational background provided the foundation for his extensive research in computer systems. Professor Smith's research focuses on computer architecture and engineering, particularly in system performance analysis, I/O systems, cache memories, and memory systems. His work has profoundly influenced how computer systems are designed and evaluated, with particular emphasis on optimizing storage systems, cache performance, and energy efficiency in computing platforms. His research has bridged theoretical analysis with practical implementation, resulting in numerous influential publications and real-world applications. His publication record shows a consistent focus on computer system performance, evolving from early work on cache memory and paging algorithms to more recent research on multimedia workloads, energy management, and storage systems. The breadth of his work spans fundamental computer architecture principles to applied system design, with particular emphasis on measurement-based analysis and optimization techniques. Harry Goode Award of the IEEE Computer Society (2006) IEEE Reynold B. Johnson Information Storage Systems Award (2008) A. A. Michelson Award of the Computer Measurement Group (2003) Fellow of the American Association for the Advancement of Science (2001) Fellow of the ACM (2000) Fellow of the IEEE (1988) Throughout his career, Professor Smith has actively contributed to the academic community through editorial roles, conference organization, and professional society leadership. He has served as Subject Area Editor for the Journal of Parallel and Distributed Computing since 1989, chaired ACM SIGARCH and SIGOPS, and participated in numerous technical committees. His research has been supported by various grants that enabled extensive experimental work and system development. Professor Smith has been instrumental in developing benchmarking methodologies and performance analysis techniques that have become standard practices in computer system evaluation. His work on cache memory systems, in particular his influential 1982 Computing Surveys paper "Cache Memories," has shaped the field for decades.

Wenfei FanView profile

Professor

• Database Theory
• Data Science
• Information Visualization
• +9 more

Wenfei Fan holds the Personal Chair in Web Data Management at the School of Informatics, University of Edinburgh . He is affiliated with the Database Group , LFCS (Laboratory for Foundations of Computer Science), Bell Labs , and the International Research Center on Big Data at Beihang University. His research spans database theory, data science, and big data systems. PhD in Computer and Information Science, University of Pennsylvania, USA MS in Computer Science, Peking University, China BS in Computer Science, Peking University, China His research interests focus on database theory and systems , including big data, data quality, data integration, database security, distributed query processing, query languages, social networks, and XML. He has pioneered techniques for graph pattern matching, data dependencies, and scalable algorithms. Recent publications emphasize graph data management , rule-based systems , and ML-data quality integration . Key themes include incremental computation, GPU-accelerated graph cleaning, entity linking, and logic-driven ML. Articles like 'Rock' and 'MiniClean' demonstrate hybrid approaches for real-world data challenges. Fellow of the Royal Academy of Engineering (FREng), 2023 Foreign Member, Chinese Academy of Sciences (ForMemCAS), 2019 Fellow of the Royal Society (FRS), 2018 ERC Advanced Fellowship, 2015 ACM Fellow (FACM), 2012 Roger Needham Award, 2008 He leads the ERC project: Resource-Bounded Graph Query Answering and contributes to systems like GRAPE and GraphScope , which parallelize sequential algorithms and process large graphs. He mentors students and collaborators globally, with a focus on data quality and graph analytics.

• Educational Technology
• Higher Education Internationalization
• Natural Language Processing
• +7 more

Maria Teresa Abad Soriano is affiliated with the Universitat Politècnica de Catalunya (UPC), specifically within the Faculty of Computer Science (FIB), Department of Computer Sciences. She is a researcher in the GPLN - Natural Language Processing Group and the TALP Research Center, contributing to both educational technologies and computational linguistics. Her work spans decades, showing sustained academic engagement. Her research interests focus on educational technology, higher education internationalization, computer-supported collaborative learning, distance learning systems, knowledge representation, and academic mentorship . These are reflected in her long-term involvement in projects related to e-learning platforms, tutoring systems, and institutional development in computing education. The analysis of her recent publications (2019–2024) reveals a strong trend towards the internationalization of higher education in computing, with detailed studies on mobility, academic policies, and institutional impact. Earlier works (1990s–2000s) center on algorithmic education, groupware modeling, and intelligent tutoring systems, showcasing a career that evolved from technical AI and educational software to broader educational policy and management. She has contributed to competitive R&D+i projects such as OPENMT and SKATeR, and has co-authored technical reports, conference papers, and indexed journal articles. Her collaborations include key figures like Nuria Castell, Juan Antonio Pastor, and Maria Felisa Verdejo. Scientific Awards: No scientific awards were mentioned in the provided text. She has supervised or contributed to the Doctoral Program in Business Administration and Management, and her technical and educational outputs suggest an advisory role in research, though specific students are not listed. She has participated in multiple competitive research projects funded under Spain’s National Research Plans, indicating success in grant acquisition. Her work with open datasets and technical documentation supports open science and institutional transparency. She is actively involved in research groups such as GPLN and TALP, which focus on natural language processing and language technologies, contributing to both theoretical and applied advancements in the field.

Rafael Pereira PiresView profile

Lecturer

• Distributed Systems
• Machine Learning
• Privacy-Preserving Technologies
• +3 more

Rafael Pereira Pires is a Lecturer and researcher at École polytechnique fédérale de Lausanne (EPFL) , affiliated with the Scalable Computing Systems Laboratory (SACS) and IC-SIN units. His research focuses on systems solutions at the intersection of privacy, efficiency, and machine learning in distributed environments. Education PhD in Computer Science (2019, University of Neuchâtel, Switzerland) Professional Master in Mechatronics (2014, IFSC, Brazil) Master in Computer Science (2009, UFSC, Brazil) His work explores privacy-preserving decentralized learning , trusted execution environments , and resource-efficient distributed systems . Recent publications address techniques like model fragmentation, approximate caching, and secure aggregation in decentralized learning contexts. Key trends in his 2023-2025 publications include: Advancements in federated learning and Mixture-of-Experts (MoE) models Applications of Trusted Execution Environments (SGX) to decentralized systems Optimization techniques for energy-aware and low-cost learning Scientific recognition includes the 2019 Léon Du Pasquier et Louis Perrier award for his PhD thesis. He has contributed to open-source tools like DecentralizePy and served as reviewer/PC member for top conferences including NeurIPS , Middleware , and ICDCS .

• Grid Computing
• Parallel Computing
• Cloud Computing
• +4 more

Vladimír Siládi, PhD, serves as Assistant Professor and Head of the Department of Computer Science at Matej Bel University in Banská Bystrica, Slovakia, where he has held academic positions since 1995. His current roles include Project Coordinator for the Virtual University initiative and Registration Authority for SlovakGrid, with prior experience as a part-time Assistant Professor at Slovak University of Technology. Educational Background: PhD in Computer Science, Slovak University of Technology in Bratislava (1997-2007) Master's in Theology, Comenius University in Bratislava (2003-2008) Master's in Secondary Education and Teaching (cum laude) and PaedDr. (EdD), Matej Bel University (1988-1993, 2005) High School Diploma, GMN Banská Štiavnica (1984-1988) His research centers on Grid Computing architectures , parallel processing techniques , and security frameworks for distributed systems . Specialized expertise includes GPU-accelerated algorithms for NP-hard problems, trust models in ad hoc grid environments, and cloud-based educational platforms. His interdisciplinary work bridges computer science with environmental modeling and psychological applications through virtual reality systems. Publication analysis reveals a consistent focus on computational optimization across 12 major works (2006-2014), with recent contributions emphasizing trust intersection models for decentralized grids (2012-2013) and cloud-based educational infrastructure (2013). Earlier works established foundations in GPU-accelerated network topology optimization and genetic algorithms for irregular systems (2006-2010). Scientific Awards: No awards documented in source materials Project leadership includes the Virtual University of Matej Bel University (ITMS 26110230077) coordinating 85 team members across 280 courses, plus TEMPUS-FLACE distance learning development (1998-2000). His registration authority role for SlovakGrid since 2009 supports national research infrastructure. Departmental leadership involves managing the Computer Science team while teaching core courses in algorithms, grid technologies, and GPU programming, maintaining consultation hours for student engagement.

Burhaneddin SandikciView profile

Associate Professor

• Decision-Making Under Uncertainty
• Medical Decision Making
• Healthcare Operations
• +3 more

Burhaneddin Sandikci is an Associate Professor of Operations Management at the Booth School of Business, University of Chicago . His research focuses on decision-making under uncertainty in medical decision-making and healthcare operations , using advanced methodologies such as Markov decision processes , stochastic programming , and simulation . His recent work includes: Equilibrium analysis of marginal organ transplantation to address shortages. Modeling breast cancer screening with supplemental tests for high-risk patients. Developing parallel bounding methods for multistage stochastic programs . His publications appear in top-tier journals like Operations Research , Management Science , and Hepatology . He has received prestigious awards including the IIE Pritsker Doctoral Dissertation Award and INFORMS Bonder Scholarship . His research bridges operations management with healthcare policy , impacting organ allocation, transplant outcomes, and hospital capacity optimization.

Xiaoyan HongView profile

Associate Professor

• Distributed Systems
• Internet of Things (IoT)
• Wireless Communications
• +4 more

Dr. Xiaoyan Hong is an Associate Professor in the Department of Computer Science at The University of Alabama's College of Engineering. Her research focuses on mobile/wireless networks, vehicular networks, and delay-tolerant systems. Ph.D., Computer Science, University of California-Los Angeles (2003) M.S., Computer Science, Zhejiang University (2000) Research spans Internet of Things (IoT) , Connected Vehicles , and Underwater Wireless Networks . Key projects include NSF-funded underwater robot communication infrastructure and smart traffic light systems. Recent work explores Named Data Networking (NDN) in vehicular environments, Task Synchronization for autonomous vehicles, and V2I Communication for traffic optimization. NSF Research Experience for Undergraduates (REU) grant recipient $1.5M NSF grant for underwater robotics networking Her research integrates with multiple engineering centers, including the Center for Advanced Vehicle Technologies and Center for Transportation Operations .

Lauren E. GillespieView profile

Assistant Professor

• Machine Learning
• Global Ecology
• Genomics
• +5 more

Dr. Lauren E. Gillespie is an Assistant Professor in the Department of Geospatial Data Sciences at the University of Michigan, specializing in AI-integrated approaches for large-scale ecosystem monitoring. With a background in computer science and biology, her research focuses on developing foundation models to analyze noisy environmental data from remote sensing and citizen science platforms, aiming to enhance ecological forecasting under rapid climate change. PhD : Computer Science, Stanford University BS : Computer Science & Chemistry, Southwestern University Her work bridges machine learning , global ecology , and remote sensing , with recent publications on biodiversity mapping using deep learning, domain adaptation in citizen science datasets, and genetic diversity loss in the Anthropocene. She actively explores ethical frameworks for scalable environmental AI applications. Key scientific awards include the Best Paper Award at AAAI 2025, Fulbright Program support (2024), and NSF Graduate Research Fellowship (2019). Her projects have received grants such as the Climate Change AI Innovation Grant for ForestBench (2022) and the Ethics, Society and Technology Hub grant for Scenes from the Anthropocene (2022).

• Web Security
• Identity Management
• System Security
• +3 more

Dr. Wanpeng Li is a Lecturer in Cyber Security within the Department of Computer Science at the University of Liverpool. Prior to this role, he held lecturer positions at the University of Aberdeen and Manchester Metropolitan University, and worked as a postdoctoral researcher at City, University of London. His research focuses on critical areas in cyber security including web security, identity management, authentication mechanisms, and malware detection using machine learning. Research Trends: His recent publications span both cyber security and mathematical modeling domains. Key security themes include automated vulnerability detection, federated learning attacks, and privacy-preserving protocols for vehicular networks and IIoT systems. Parallel studies in grey system models explore energy consumption forecasting and environmental impact analysis using fractional calculus and neural network integrations. Advising: Dr. Li actively accepts PhD students in cyber security-related fields.

Ke (Cory) WangView profile

Assistant Professor

• Computer Architecture
• Interconnection Networks
• Machine Learning
• +8 more

Dr. Ke (Cory) Wang serves as Assistant Professor at the University of North Carolina at Charlotte in the Department of Electrical and Computer Engineering, where he conducts research in computer architecture and parallel systems. Ph.D. in Computer Engineering (2022), George Washington University M.Sc. in Electrical Engineering (2015), Worcester Polytechnic Institute B.Sc. in Computer Science (2013), Peking University His research focuses on machine learning-enabled computer architecture with emphasis on network-on-chip design , domain-specific accelerators , and cross-layer optimization for manycore systems. Specific areas include anomaly detection, graph neural network acceleration, and fault-tolerant communication frameworks. Recent publications demonstrate increasing integration of deep learning techniques with traditional architecture design, particularly for graph convolutional networks and heterogeneous systems . His work addresses multi-objective optimization across performance , energy efficiency , and security dimensions . Key scientific recognitions include: National Science Foundation award (CSR: Small: Cross-layer Design, 2023) National Science Foundation award (CRII: SHF: Flexible Design Framework, 2023) Dr. Wang leads the Intelligent Computer Architecture & Systems Laboratory , which develops advanced frameworks for network-on-chip optimization and AI-driven system design.

Michael DinitzView profile

Associate Professor

• Theoretical Computer Science
• Approximation Algorithms
• Online Algorithms
• +5 more

Michael Dinitz is an Associate Professor in the Department of Computer Science at Johns Hopkins University with a secondary appointment in the Department of Applied Mathematics and Statistics . He is a member of the Algorithms and Complexity group and the Mathematical Institute for Data Science . His research focuses on Theoretical Computer Science , with emphasis on approximation algorithms , online algorithms , and distributed algorithms , particularly in applications to computer networking , distributed systems , and machine learning . His recent work involves differential privacy , dynamic networks , and resilient network design . His publications cover diverse topics in graph theory , privacy-preserving algorithms , and online optimization , with a focus on practical applications of theoretical results. He has received multiple NSF grants including a CRII award and Algorithms in the Field funding, and was honored with the Professor Joel Dean Excellence in Teaching Award . He advises a research group with PhD, MSE, and undergraduate students , and serves on program committees for leading theory conferences like FOCS , STOC , and ICALP . Education PhD in Computer Science, Carnegie Mellon University (2010), advised by Anupam Gupta AB in Computer Science, Princeton University (2005), advised by Sanjeev Arora Grants & Awards NSF CRII Grant (2015) NSF Algorithms in the Field Grant (2016) Multiple NSF Algorithmic Foundations grants (2019, 2022, 2025) NSF Graduate Research Fellowship (2005-2010) ARCS Foundation Scholarship (2005-2010) Best Paper Awards at ICDCS (2014) and DISC (2017)

Mathieu BrédifView profile

Researcher

• Lidar Processing
• 3D Reconstruction
• Geovisualization
• +5 more

Mathieu Brédif is a Permanent Researcher at LASTIG, Gustave Eiffel University, affiliated with the National School of Geographic Sciences (ENSG) and IGN. He serves as co-chair of ISPRS Working Group II/3 on Point Cloud Processing (2016-2020) and chaired ISPRS Working Group III/5 on Graphics and Remote Sensing (2012-2016). His academic appointments include Assistant Professor at École Polytechnique teaching Image Analysis and Computer Vision (INF573) and 3D Computer Graphics (INF443) since 2019-2020. Telecom ParisTech PhD (2005-2010) Stanford University Master in Computer Science (2004) École Polytechnique Engineering Degree (2000-2005) Brédif's research focuses on Lidar processing, 3D reconstruction, and geovisualization , with significant contributions to point cloud analysis, urban scene modeling, and historical image integration. His work bridges computer vision, photogrammetry, and geographic information systems, emphasizing practical applications in urban planning and cultural heritage. He has developed novel algorithms for point cloud inpainting, visibility estimation, and distributed 3D reconstruction. His publications reveal consistent focus on urban modeling through point cloud processing (58% of works), image-based rendering techniques (22%), and geovisualization systems (15%). The research trajectory shows increasing emphasis on deep learning applications for LiDAR data since 2016, alongside continued development of geometric algorithms for photogrammetric processing. ANR project leadership in geospatial data valorization (structurAtion et vaLorisation du patrimoinE géoGraphique - 9) iSpace&Time 4D web GIS development (5) European project participation in high-volume point cloud analysis (8) Brédif actively mentors doctoral candidates, currently supervising Melvin Hersent, Alexane Nghien, and Florent Geniet, with 8 completed PhDs including Pierre Biasutti and Murat Yirci. His laboratory work centers on the GEOVIS research team , developing the iTowns open-source framework for 3D geospatial visualization, which powers the Géoportail's 3D data engine and supports multiple ANR projects in cultural heritage visualization.

Chen FengView profile

Associate Professor

• Information Theory
• Coding Theory
• Blockchain Technology
• +4 more

Chen Feng is an Associate Professor in the Department of Electrical Engineering at the School of Engineering, University of British Columbia (UBC), Okanagan campus. He holds the Tier-2 Principal's Research Chair in Blockchain and serves as the Co-Cluster Lead for Blockchain@UBC. Dr. Feng joined UBC in July 2015 after completing postdoctoral fellowships at Boston University and EPFL. Dr. Feng received his B.Eng. degree from Shanghai Jiao Tong University in 2006, and his M.A.Sc. and Ph.D. degrees from the University of Toronto in 2009 and 2014, respectively. Dr. Feng's research focuses on the intersection of information theory, coding theory, and blockchain technology. His work spans several key areas including: Information and Coding Theory for wireless communications Blockchain and distributed ledger technologies Quantum communications and cryptography Cloud computing optimization and analysis Stochastic analysis of distributed systems His recent research output demonstrates a strong trajectory in blockchain consensus protocols, private information retrieval, and the application of information theory to distributed systems. Dr. Feng has been actively publishing in top-tier venues with a focus on improving the performance, security, and scalability of blockchain systems. Dr. Feng has received several prestigious awards including: Best Paper Award at IEEE MSN (2021) Tier-2 Principal's Research Chair Award (2020) Visiting Fellow Scholarship at the University of Melbourne (2019) Emerging Professor Award from UBC-Okanagan School of Engineering (2017) Teaching Excellence Award (2017/18) As a graduate student supervisor, Dr. Feng teaches a range of courses from undergraduate to graduate levels, with a particular emphasis on blockchain technologies, wireless communications, and advanced engineering topics. He serves as a Senior Research Consultant for Subspace Labs and a Scientific Consultant for Creative Destruction Lab, bridging academic research with industry applications. Dr. Feng leads the Blockchain@UBC initiative, which focuses on advancing blockchain research and applications across multiple domains including clean energy, distributed systems, and secure communications.

• Dependability Engineering
• Performability Analysis
• Cloud Computing
• +7 more

Ermeson Carneiro de Andrade is a Professor at the Department of Systems and Computer Engineering within the Center of Informatics at the Federal University of Pernambuco (UFPE) in Brazil. His research focuses on dependability engineering, performability analysis, and fault tolerance in distributed and embedded systems. Over his career spanning more than 15 years, he has established himself as a prominent researcher in the field of system reliability through numerous publications in top-tier journals and conferences. Dr. Andrade's research interests primarily center on the analysis and modeling of system dependability, with particular expertise in UAV-based monitoring systems, cloud computing environments, and IoT architectures. His work bridges theoretical modeling with practical applications, particularly in environmental monitoring, disaster recovery solutions, and mission-critical systems. He has made significant contributions to understanding software aging phenomena in various computing environments and developing performability-aware solutions for real-time systems. The analysis of his recent publications reveals a strong focus on UAV systems for environmental monitoring, particularly deforestation detection, with increasing attention to weather impacts and vehicle density-aware traffic monitoring. His research demonstrates a consistent pattern of applying stochastic modeling techniques to solve practical problems in distributed systems, with recent work expanding into NoSQL database performance, satellite constellation dependability, and the performance-interpretability trade-offs in machine learning models. This evolution shows his ability to adapt to emerging technologies while maintaining core expertise in system reliability. Dr. Andrade has been actively involved in mentoring students and collaborating with researchers across Brazil and internationally. His work often involves interdisciplinary teams addressing complex system challenges. While specific awards aren't detailed in the available publication records, his consistent output in high-impact venues demonstrates recognition within the dependability engineering community. His laboratory work appears to focus on system modeling and analysis, with particular emphasis on experimental validation through simulation and real-world testing. Current projects suggest involvement in UAV-based monitoring systems for environmental applications, with strong connections to public sector institutions in Pernambuco state.