جست‌وجوی استاد و پژوهشگر

• Data Warehousing
• OLAP
• Data Mining
• +۵ مورد دیگر

Ioannis Kotidis is an Associate Professor in the Department of Informatics at the Athens University of Economics and Business (AUEB), School of Information Sciences and Technology. He holds a Diploma in Electrical and Mechanical Engineering from the National Technical University of Athens (1995), and Master's and Ph.D. degrees from the University of Maryland (1997, 2000). Prior to joining AUEB, he worked as a Senior Technical Specialist at AT&T Labs-Research in Florham Park, New Jersey until January 2006. His research spans multiple areas of database systems with particular focus on On-Line Analytical Processing (OLAP) and data warehousing, data mining, sensor/P2P networks, mobile data management, data fusion & dissemination, data streams, RFID data management, approximate query answering, and database preservation . His work bridges theoretical foundations with practical implementations, as evidenced by numerous publications in top-tier database conferences and journals. Professor Kotidis leads several significant research projects including RECOST (REal time management of COmplex STreams), DBSENSE (Information Management in Wireless Sensor Networks), INFORE (Interactive Extreme-Scale Analytics and Forecasting), and DeLorean (Storage, Indexing and Analysis Techniques for Time-Series Management). His recent work focuses on blockchain applications for decentralized OLAP processing, complex event processing frameworks, and advanced techniques for managing complex data streams. Among his notable achievements is the best paper award at the ACM SIGMOD International Conference on Management of Data for his work on DynaMat: A Dynamic View Management System for Data Warehouses. His publications consistently address challenging problems in database systems with innovative approaches that have influenced both academic research and practical implementations. He has supervised numerous undergraduate theses on topics including blockchain-based OLAP view management, complex event processing using FlinkCEP, and graph similarity learning. His research has attracted significant funding through various research programs at AUEB, including Basic Research Funding Programs 1 & 2.

• Design Models for Technologically Supported Learning
• Innovative Interactive Learning Systems
• Educational Games Development
• +۳ مورد دیگر

Retalis Symeon is a Professor at the Department of Digital Systems within the School of Information and Communication Technologies at the University of Piraeus. He specializes in Design Models for Technologically Supported Learning and has established himself as a leading researcher in educational technology. His research focuses on designing innovative interactive learning systems and games that contribute to children's skill acquisition. Over the past 15 years, Professor Symeon has been instrumental in advancing educational technology through his research and development work. He has authored over 150 research articles published in scientific books, journals, and conferences, and has delivered approximately 30 invited speeches at international conferences worldwide. Professor Symeon has been actively involved in research funding, having participated as a principal investigator and coordinator in more than 30 projects funded by the European Union, national grants, and major software companies including SmartEducation and Google. His work spans international collaborations with Higher Education Institutions across the globe. Scientific Director of CoSyLlab (Computer Supported Learning Engineering Lab) Reviewer for well-known international journals in Learning Technologies Developer of multiple innovative educational tools Professor Symeon has received significant recognition for his work, including a prestigious distinction from ACM Computing Reviews as the reviewer with great influence in June 2017. His contributions to educational technology have positioned him as a key figure in the field of digital learning systems.

• Large-scale Scientific Computing
• Computational Linear Algebra
• Parallel and Distributed Processing
• +۴ مورد دیگر

Professor Efstratios Gallopoulos is a faculty member at the Department of Computer Engineering & Informatics , University of Patras, where he holds the Division of Computer Software . He currently serves as Deputy Department Chair and Director of the High Performance Information Systems Laboratory (HPCLab) . His academic career spans multiple institutions including the University of Illinois at Urbana-Champaign, University of California Santa Barbara, and collaborations with INRIA Rennes and NASA Goddard Space Flight Center. Education : B.Sc. in Mathematics (First Class Honours) from Imperial College London (1979) Ph.D. in Computer Science from University of Illinois at Urbana-Champaign (1985) Research Focus : His work centers on Large-scale Scientific Computing with emphasis on Computational Linear Algebra , Parallel/Distributed Processing , and Data Mining . Recent publications highlight innovations in Randomized Numerical Linear Algebra , Heterogeneous Cluster Scheduling , and GPU-Accelerated Inversion Techniques . Article Trends : His research bridges High-Performance Computing with Data Science , focusing on scalable algorithms for Matrix Computations , Recommender Systems , and Biomarker Analysis . The work spans theoretical advancements (e.g., Givens Rotations ) and practical implementations (e.g., pylspack library). Scientific Awards : NASA Group Achievement Award for Massively Parallel Processor (MPP) development ACM SIGWEB Hypertext Ted Nelson Newcomer Award (2012) Advising and Grants : He has advised numerous research projects funded by European Research Council , Hellenic Foundation for Research and Innovation (HFRI) , and international bodies like the US National Science Foundation. Notably, he co-organized the 2015 Gene Golub SIAM Summer School and served as Chair of the SIAM Gene Golub Summer School Committee (2020-24). Labs and Teams : He leads the High Performance Information Systems Laboratory (HPCLab) and co-directs the interdisciplinary graduate program Data Driven Computing and Decision Making . His teams have contributed to the Cedar vector multiprocessor project at UIUC and Text-to-Matrix Generator (TMG) tools for data mining.

Sotirios Xydisمشاهده پروفایل

استادیار

• Hardware/Software Co-design
• High Level Synthesis
• Hardware Accelerators
• +۷ مورد دیگر

Sotirios Xydis is an Assistant Professor in the Division of Computer Science at the School of Electrical and Computer Engineering, National Technical University of Athens (NTUA), with prior faculty appointment at Harokopion University of Athens (2020-2023). He maintains ongoing collaboration with the Institute of Communication and Computer Systems (ICCS) since 2014 and previously served as an engineer at HEDNO (2015-2018) and postdoctoral researcher at Politecnico di Milano (2011-2013). His academic credentials include: BSc in Electrical and Computer Engineering, NTUA (2005) MSc in Techno-Economic Systems, NTUA (2011) PhD in Electrical and Computer Engineering, NTUA (2011) Dr. Xydis specializes in hardware/software co-design , energy-efficient hardware acceleration , and memory management for embedded and cloud-edge systems. His research bridges low-power circuit design , heterogeneous architecture optimization , and resource management frameworks , with particular emphasis on AI workloads and serverless infrastructures. Current projects target Edge AI accelerators (CONVOLVE), disaggregated memory systems, and LLM inference optimization through hardware-aware algorithms. Analysis of his 2023-2025 publications reveals three dominant trends: (1) Energy-efficient hardware accelerators for Edge AI using approximate computing techniques, (2) Memory/resource management innovations for disaggregated serverless environments, and (3) GPU/FPGA optimization for LLM inference through dynamic frequency scaling and predictive throttling. These works consistently address the power-performance tradeoffs in heterogeneous computing systems. His scientific recognition includes: Best Paper Award, IEEE/NASA/ESA AHS (2007) Best Paper Award, ACM PARMA (2013) Best Paper Award, ACM Computing Frontiers (2020) Hipeac Award at DAC (2019, 2020) Dr. Xydis has secured over 15 European/national research grants as Principal Investigator and Technical Coordinator, focusing on hardware acceleration frameworks and energy-efficient computing. His advising encompasses graduate research in hardware design and optimization, though specific student names aren't publicly listed. Current projects include CONVOLVE for Edge AI and CollectiveHLS for collaborative hardware synthesis. He is a core member of NTUA's Microelectronics Laboratory (Microlab) and collaborates with ICCS on hardware acceleration projects. His team develops frameworks like CollectiveHLS and throttLL'eM, with active participation in DATE, DAC, and ISCA conference communities.

Adrian Sampsonمشاهده پروفایل

دانشیار

• computer architecture
• programming languages
• compilers
• +۵ مورد دیگر

Adrian Sampson is an Associate Professor in the Department of Computer Science at Cornell University, where he is part of the Computer Systems Laboratory and the programming languages group. He joined Cornell in 2016 as an Assistant Professor and was promoted to Associate Professor in 2022. Prior to Cornell, he was a Visiting Researcher at Microsoft Research (2015-2016). He received his Ph.D. from the University of Washington in 2015 under advisors Luis Ceze and Dan Grossman, with a dissertation on Hardware and Software for Approximate Computing. His research focuses on breaking down abstraction barriers and rethinking the hardware-software interface. He is particularly known for his work on approximate computing, which explores how computers can be more efficient by allowing them to make controlled mistakes. He leads the Capra research group at Cornell, which investigates programming languages and computer architecture. Sampson's recent publications demonstrate a strong focus on hardware acceleration, FPGA programming, compiler design, and programming language theory. His work often bridges the gap between high-level programming abstractions and low-level hardware implementation, with particular attention to predictability, verification, and energy efficiency. He has made significant contributions to geometry types for graphics programming, timeline types for modular hardware design, and virtual machines for FPGA programming. Among his notable recognitions are the IEEE TCCA Young Computer Architect Award (2021), NSF CAREER award (2019), and multiple Distinguished Artifact Awards at major conferences. He has advised numerous Ph.D. students who have gone on to positions at institutions like Wellesley College, Northwestern University, and Amazon. Sampson is actively involved in academic service, serving on program committees for major conferences including PLDI, ASPLOS, and ISCA. He has also held leadership roles such as ACM SIGARCH Board of Directors (2023-2025) and SIGPLAN Information Director. His teaching at Cornell includes courses on computer systems, programming languages, and advanced compilers.

Zhenman Fangمشاهده پروفایل

دانشیار

• Hardware Acceleration
• Computer Architecture
• Big Data Computing
• +۷ مورد دیگر

Dr. Zhenman Fang is an Associate Professor in the School of Engineering Science (Computer Engineering Option) and Associate Member in the School of Computing Science at Simon Fraser University, Canada. He founded and directs the HiAccel Lab, focusing on accelerator-rich architectures. His PhD (2014) is from Fudan University, China, with 15 months spent at the University of Minnesota. Prior to SFU, he was a Staff Software Engineer at Xilinx (2017-2019) and a postdoc at UCLA (2014-2017). His research spans: Hardware acceleration for ML, big data, genomics, and HPC FPGA-based customizable computing and near-data processing Compiler/runtime systems for heterogeneous platforms Performance/reliability optimization of accelerator-rich systems His recent publications (2024-2025) focus on FPGA acceleration for machine learning (e.g., on-device training, quantization), computational chemistry, image/video compression, database systems, and reconfigurable computing, demonstrating cross-domain applications of specialized hardware. Awards & Honors: Best Paper Awards: FPL 2024, MEMSYS 2017, TCAD 2019 Best Paper Nominations: ICCAD 2025, FCCM 2025, HPCA 2017, ISPASS 2018 SFU Research Excellence Horizon Award (2025) NSERC Alliance, CFI JELF, and Xilinx University Awards He advises 20+ PhD/Master's students in HiAccel Lab, focusing on accelerator design. Major grants include NSERC Alliance (2020) and CFI JELF (2019). The lab operates a 10-node cluster with FPGA/GPU infrastructure.

Ilias Diakonikolasمشاهده پروفایل

استاد

• Robust Statistics
• Machine Learning Theory
• Algorithmic Game Theory
• +۲ مورد دیگر

Ilias Diakonikolas is the Sheldon B. Lubar Professor in the Department of Computer Sciences at UW-Madison, with affiliations in Statistics, the Wisconsin Institute for Discovery, and the Data Science Institute. He holds a Ph.D. from Columbia University and previously held positions at USC, University of Edinburgh, and UC Berkeley. Research examines: Tradeoffs between statistical efficiency, computational efficiency, and robustness in machine learning High-dimensional robust statistics and information-computation tradeoffs Foundations of deep learning and nonparametric estimation Publications establish fundamental limits for learning algorithms and develop efficient methods for distribution testing and robust estimation. Awards include Sloan and Romnes Fellowships, NSF CAREER Award, and Best Paper at NeurIPS 2019. Advises PhD students in theory of computing and machine learning, leading the Algorithmic High-Dimensional Robust Statistics research program. Organizes workshops on computational-statistical frontiers and authored the Cambridge University Press textbook on robust statistics.

Georgios Kossiorisمشاهده پروفایل

استاد

• Partial Differential Equations
• Applied Mathematics
• Stochastic Modeling
• +۵ مورد دیگر

Georgios Kossioris is a Professor at the Department of Mathematics and Applied Mathematics of the University of Crete . He holds a Ph.D. in Applied Mathematics from Brown University (1991) and a Diploma in Naval Architecture from the National Technical University of Athens (1986). His research focuses on Partial Differential Equations and Applications , with significant contributions to stochastic equations, Hamilton-Jacobi modeling, and interdisciplinary work in environmental and biomedical domains. His publications span Numerical Analysis , Stochastic Modeling , and Environmental Economics , including key works on the Shallow Lake Problem , Wind Energy Assessment , and Abdominal Aortic Aneurysm Segmentation . He has secured major grants for projects like Extreme Weather Phenomena Prediction (SYNERGASIA, 2011-2014) and Optimal Control of Dynamic Systems (THALIS, 2012-2014). He has organized workshops such as the 2019 SDEs/SPDEs: Theory, Numerics, and Data Science and taught courses like Weak Theory of PDEs , Differential Equations , and Dynamic Meteorology . His computational methodologies bridge mathematics, economics, and biomedical engineering.

• Machine Learning
• Theoretical Computer Science
• Algorithms
• +۳ مورد دیگر

Christos Tzamos is an Associate Professor at the National and Kapodistrian University of Athens. His research focuses on the intersection of machine learning, theoretical computer science, and algorithmic game theory. He has made significant contributions to topics like online learning, optimization under noise, and mechanism design. His work often bridges foundational theory with practical algorithmic solutions. Position: Associate Professor Affiliation: National and Kapodistrian University of Athens Key research interests include: Machine Learning (e.g., robust classification, active learning) Algorithms (e.g., optimization, approximation algorithms) Computational Economics (e.g., auction design, Pandora’s box problems) His most recent articles (2023–2025) explore advanced topics such as statistical query hardness, noise-robust learning frameworks, and optimized mechanisms for multi-item markets. Notable trends in his work include developing algorithms resilient to adversarial noise and designing efficient learning strategies under constraints. No scientific awards are explicitly listed in the provided texts, though his prolific publication record reflects strong academic standing. Labs, teams, or collaborations are not detailed here, but his research often involves interdisciplinary collaborations with leading institutions.

Peter W. O'Hearnمشاهده پروفایل

استاد

• Programming Languages
• Formal Verification
• Separation Logic
• +۵ مورد دیگر

Peter W. O'Hearn is a Professor of Computer Science at University College London and a Research Scientist at Meta AI (FAIR). He has held academic positions at Syracuse University, Queen Mary University of London, and University College London, before joining Facebook (now Meta) in 2013 as part of the acquisition of the verification startup Monoidics. His career spans over 25 years of research in programming languages and logic, with significant contributions to both theoretical foundations and practical industrial applications. O'Hearn's research primarily focuses on formal reasoning about programs, with his most notable contributions being the co-invention (with John Reynolds) of Separation Logic and the development of Incorrectness Logic. His work bridges the gap between theoretical computer science and practical software engineering, emphasizing how fundamental theory, tool development, and real-world application can mutually reinforce each other. He has consistently advocated for the integration of formal methods into industrial software development practices. His research has led to the development of the Infer program analyzer, which runs internally on Meta's code bases and has detected over 100,000 bugs that have been fixed by developers. Infer is also used in production at other major companies including Amazon, Mozilla, Spotify, and Marks and Spencer. His recent work on Incorrectness Logic represents a paradigm shift from traditional program verification approaches, focusing on bug finding rather than correctness proving. O'Hearn has received numerous prestigious awards recognizing both his theoretical contributions and practical impact: Fellow of the Royal Society (elected 2018) Fellow of the Royal Academy of Engineering (2016) 2016 Gödel Prize 2016 CAV Award Two POPL MIP awards Honorary doctorate from Dalhousie University (2018) 2021 IEEE Cybersecurity Award for Practice Throughout his career, O'Hearn has successfully translated theoretical advances into practical tools used at scale in industry. His work on Separation Logic led directly to Infer, while his more recent work on Incorrectness Logic aims to provide foundations for next-generation bug catching tools. He has maintained a strong academic presence while working in industry, continuing his professorship at UCL alongside his role at Meta. O'Hearn leads research efforts at the intersection of formal methods and practical software engineering at Meta, focusing on scaling static analysis techniques to handle the massive codebases typical of modern technology companies. His work has significantly influenced how large tech companies approach software verification and bug detection.

George A. Gravvanisمشاهده پروفایل

استاد

• Computational Methods
• Mathematical Modeling
• Parallel Computing
• +۱۰ مورد دیگر

Dr. George A. Gravvanis is a Professor of Applied Mathematics and Numerical Computations at the Department of Physics and Applied Mathematics, Democritus University of Thrace. He also serves as Coordinator and SEP Member for Thematic Units at the Hellenic Open University. B.Sc. (1982) in Science (Joint Honours), University of Salford B.A. (1986), Mathematics, National and Kapodistrian University of Athens M.Sc. (1984), Numerical Analysis, Brunel University PhD (1992), Computer Science, Athens University of Economics and Business His research focuses on computational and numerical methods, including Mathematical Modeling , Parallel Algorithmic Design , Numerical Algorithms , Sparse Matrix Techniques , and PDE Solvers . He integrates these into Mathematical Software and Computer Science Mathematics . Recent article trends highlight his work in Sparse Regression for data imputation, Hybrid Multi-Projection Methods for distributed systems, and Unified Transform Techniques for PDEs. Subfields span High-dimensional Data , GPU Clusters , and Self-Organizing Clouds . He has taught undergraduate courses in Mathematical Software , Applied Numerical Analysis , and Scientific Calculations . He has coordinated research projects such as the CloudLightning initiative under Horizon 2020. His editorial contributions include roles on international journal boards and special edition editing. Dr. Gravvanis has reviewed for major academic organizations and journals, including ACM Computing Reviews and Mathematical Reviews (AMS) . His career spans academic roles and technical positions in national and EU social security informatics.

Christoforos Kachrisمشاهده پروفایل

استادیار

• Hardware Accelerators
• FPGAs
• Edge AI
• +۵ مورد دیگر

Christoforos Kachris is an Assistant Professor at the Department of Electrical and Electronics Engineering, University of West Attica since 2023. Previously, he co-founded and led InAccel, a startup pioneering FPGA deployment in the cloud, securing €500k in funding and winning awards like the Venture Impact Award (2021) and DeepBlue Cup (2019). He led EU projects such as VINEYARD (€6.3M, 2016–2018), the first to deploy FPGAs in cloud data centers. His research spans reconfigurable computing, hardware accelerators, cloud computing, and optical interconnects, with over 90 publications and 2,700+ citations. Education: Ph.D. (2007, Delft University of Technology), M.Sc. (2003, Technical University of Crete), and Diploma (2001, Technical University of Crete). His Ph.D. focused on FPGA-based network processing, with internship at Xilinx Research Labs, resulting in a US patent on configurable transactional memories. Research interests include machine learning on embedded systems, FPGAs, edge AI, reconfigurable computing, and optical interconnects. He has advised numerous students, many now in tech roles at Cisco, IBM, Ericsson, and startups. Notable contributions include a highly cited survey on optical interconnects in data centers and leadership in projects like VINEYARD and CloudAccel (Principal Investigator). Awards include Venture Impact Award and recognition in international hardware competitions.

• Water Resources Management
• Groundwater Flow and Pollutant Transport
• Geoenvironmental Engineering
• +۳ مورد دیگر

Georgios P. Karatzas is a Professor at the Department of Environmental Hydraulics, Coastal Engineering and Geoenvironmental Engineering (IV) within the Technical University of Crete. His research focuses on Water Resources Management , Groundwater Flow and Pollutant Transport , and Geoenvironmental Engineering . He leads the Laboratory of Geoenvironmental Engineering and has developed innovative methodologies like the 'Outer Approximation Method' Optimization adopted by major US agencies. His academic credentials include a Ph.D. (1992), M.Sc. (1987), and B.Sc. (1985) from Rutgers University, with prior education in Forestry from Aristotle University of Thessaloniki (1982). He has received international recognition, including adoption of his optimization methods by the Federal Remediation Technologies Roundtable (2003-present) and EPA (1999). His research integrates Groundwater Simulation Models with Optimization Methods for sustainable aquifer management, addressing challenges like Coastal Aquifer Salinization , Karst Aquifer Dynamics , and Flood Risk Assessment . Recent projects include InTheMED (€220,000) and Sustain–COAST (€290,000) focused on Mediterranean groundwater sustainability. Notable scientific awards include the 2014 Outstanding Teaching Award at Technical University of Crete and multiple grants from PRIMA, Interreg, and LIFE+ programs. His work combines advanced computational methods with practical environmental risk mitigation strategies.

Ioannis Dimitriouمشاهده پروفایل

استادیار

• Queueing Theory
• Applied Probability
• Stochastic Processes
• +۶ مورد دیگر

Ioannis Dimitriou is an Assistant Professor at the Department of Mathematics, University of Patras, Greece, since August 2019. Previously, he held academic positions at Imperial College London, FORTH Greece, Aristotle University of Thessaloniki, and INRIA Sophia Antipolis. Research Interests: His work focuses on Queueing theory Applied probability Stochastic processes Stochastic performance modeling Wireless network analysis Recent Publications: His recent work explores multidimensional queueing models, stability analysis in cooperative networks, and stochastic resource allocation with applications in IoT and 5G networks. Key trends include Retrial queue systems Markov-modulated random walks Network-level cooperation Power-saving mechanisms Stable throughput regions Scientific Awards: Marie Curie Fellow (ERCIM ABCDE program) Postdoctoral 'Research Excellence' Fellowship at Aristotle University Travel Grant for StochMod 2018 Teaching & Mentorship: He teaches Probability, Stochastic Processes, and Queueing Theory at both undergraduate and MSc levels. Mentored 9 MSc/BSc students, focusing on queueing applications in wireless networks, stochastic models, and performance evaluation.

Spyridon Kamvissisمشاهده پروفایل

استاد

• Mathematical Physics
• Integrable Systems
• Nonlinear Partial Differential Equations
• +۴ مورد دیگر

Spyridon Kamvissis is a Professor of Integrable Systems in Mathematical Physics at the University of Crete and a Member of the Institute of Applied and Computational Mathematics at the Foundation for Research & Technology - Hellas (FORTH). His office is located in room Δ338 of the Mathematics Building at the University of Crete campus in Voutes, Greece, with contact telephone +30 2810 393714. His academic credentials include: Ph.D. from the Courant Institute (1991) Habilitation from the University of Paris VII (Jussieu) (1996) Kamvissis specializes in infinite dimensional Hamiltonian systems that admit a Lax pair or zero curvature condition, which can be studied via inverse scattering/spectral methods. His research focuses on mathematically rigorous treatments of asymptotic problems for nonlinear dispersive systems, including long time behavior, semiclassical limits, and continuum limits of solutions to partial differential equations and nonlinear lattices. He has developed what he describes as a "nonlinear/non-commutative microlocal analysis" that extends classical stationary phase and steepest descent methods. His publication record shows a clear evolution from foundational work on the Toda lattice (1993-1996) through nonlinear Schrödinger equation studies (2003-2016) to his current focus on semiclassical WKB problems for non-self-adjoint Dirac operators (2020-2024). His approach integrates techniques from PDE theory, complex analysis, harmonic analysis, potential theory, and algebraic geometry, with particular attention to sophisticated models displaying instabilities. Professor Kamvissis maintains an active teaching schedule with courses planned through Spring 2026, including RIEMANN-HILBERT METHOD (Spring 2024), VON NEUMANN ALGEBRAS (Fall 2024), DIFFERENTIAL GEOMETRY (Spring 2025), RIEMANNIAN GEOMETRY (Fall 2025), and STOCHASTIC CALCULUS (Spring 2026).