جست‌وجوی استاد و پژوهشگر

• Algorithms and Complexity
• Combinatorial Optimization
• Graph Theory
• +۳ مورد دیگر

Ioannis Milis is a Professor at the Department of Informatics, School of Information Sciences and Technology, Athens University of Economics and Business (AUEB). He holds a PhD in Computer Science from AUEB (1989) and a BS in Electrical Engineering from Democritus University of Thrace (1983). As a Marie Curie fellow, he conducted post-doctoral research at LRI Orsay, INRIA-Sophia Antipolis, and NTUA (1992-1996). Education: BS, Electrical Engineering, Democritus University of Thrace (1983) PhD, Computer Science, Athens University of Economics and Business (1989) His research focuses on algorithms and complexity, particularly exact and approximation algorithms for optimization problems in computer/communication systems, combinatorial optimization, graph theory, and game theory. He is a member of AUEB's Theory Group. The recent articles span areas like Scheduling MapReduce jobs , Densest k-subgraph algorithms , Bin packing with colocations , and Speed scaling for lateness minimization . These works emphasize theoretical computer science, optimization, and energy-aware computing. He has contributed to organizing major conferences including the Athens Colloquium on Algorithms and Complexity (ACAC) , ISCO Symposia , and APEX Workshops . His involvement in program committees and research projects under Greek national programs (PENED, HRAKLEITOS II) and AUEB's Basic Research Funding Program highlights his academic leadership. As a teacher, he has delivered courses on Algorithms , Design and Analysis of Algorithms , and Advanced Algorithms at both undergraduate and postgraduate levels at AUEB.

Bradford L. Chamberlainمشاهده پروفایل

استاد مدعو

• Parallel Computing
• Programming Languages
• High-Performance Computing
• +۳ مورد دیگر

Bradford L. Chamberlain is a Distinguished Technologist at Hewlett Packard Enterprise and an Affiliate Professor in the Paul G. Allen School of Computer Science and Engineering at the University of Washington. With over two decades of experience in high-performance computing, he has made significant contributions to parallel programming languages, particularly as the technical lead of the Chapel programming language project since 2006. His educational background includes: Ph.D. in Computer Science & Engineering from the University of Washington (2001) M.S. in Computer Science & Engineering from the University of Washington (1995) B.S. in Computer Science from Stanford University (1992) Chamberlain's research focuses on improving programmer productivity for high-performance computing through innovative language design, compiler techniques, and runtime systems. His work centers around the Chapel programming language, which aims to provide a multiresolution programming model that allows developers to express parallelism at varying levels of abstraction while maintaining performance across diverse architectures from laptops to supercomputers. His research spans parallel language design, compiler optimization, data distribution strategies, locality management, and performance portability. Chapel builds on his earlier work with the ZPL language, where he developed region-based approaches for sparse parallel computing. His publication record over the past fifteen years demonstrates a consistent focus on practical approaches to parallel programming, with recent work emphasizing data locality, heterogeneous architectures, and performance portability. His articles show an evolution from foundational language design concepts to increasingly sophisticated implementations addressing real-world HPC challenges, particularly in the areas of domain mapping, iterator abstractions, and memory management for large-scale systems. As a Distinguished Technologist at HPE, Chamberlain has played a key role in growing the Chapel project from a modest effort to one involving nearly 20 full-time developers. His leadership has positioned Chapel as one of the most promising languages for addressing the challenge of productive parallel programming at scale. He has secured funding, established collaborations with academia and industry, and performed extensive outreach through talks, tutorials, and research visits. At the University of Washington, Chamberlain serves as a liaison between academia and industry, participating in student committees, teaching graduate courses like Parallel Computation, and fostering communication between the department and HPE/Cray. His teaching experience spans from undergraduate data structures to graduate seminars on parallel programming environments. He has also volunteered as a tutor for underrepresented students in computer science.

• Compilers
• Computer Architecture
• High-Performance Storage
• +۵ مورد دیگر

Mahmut Taylan Kandemir is a Professor in the Department of Computer Science at Pennsylvania State University. His research spans optimizing compilers, runtime systems, embedded systems, I/O, high-performance storage, and power-aware computing. He leads the Microsystems Design Lab and collaborates with institutions like Argonne National Lab, Microsoft, and Intel. Education: B.S. Computer Engineering, Istanbul Technical University (1988) M.S. Computer Engineering, Istanbul Technical University (1992) Ph.D. Computer Science, Syracuse University (1999) Research Focus: Dr. Kandemir's work integrates hardware-software co-design to address challenges in multi-core architectures, non-volatile memory systems, and energy efficiency. His recent projects explore 3D NAND flash optimization, near-data computing, and reliability in heterogeneous systems. Key themes include reducing data movement overhead, enhancing storage longevity, and developing compiler-directed solutions for emerging hardware. Publications: His articles frequently appear in premier venues (PLDI, ASPLOS, HPCA) and emphasize memory hierarchy optimization, security, and parallelism. Trends include hardware-assisted resilience, approximate concurrency, and energy-efficient VR streaming. Awards: Premier Research Award, Penn State Engineering Society (2017) IEEE Fellow NSF CAREER Award (2000) Best Paper Awards (IPDPS 2008, ICPADS 2006) Top ACM Digital Library Download (2006) Advising & Grants: He has graduated 32 Ph.D. and 20 master's students, with 15 Ph.D. and 5 master's students currently advised. His research is funded by NSF, DARPA, DOE, and industry partners. Active projects include: NSF/OAC: Re-Engineering Galaxy for Performance (2019-2023) NSF/SHF: 3D NAND Flash Optimization (2019-2022) NSF/SPX: Heterogeneous Intermittent Accelerators (2018-2022) Labs & Teams: Leads the Microsystems Design Lab, focusing on architecture-compiler co-design. Collaborates with the Storage Systems Research Center and heterogeneous computing groups at Penn State.

Saday Sadayappanمشاهده پروفایل

استاد

• Compiler Optimization
• High-Performance Computing
• Sparse/Dense Matrix Computations
• +۳ مورد دیگر

P. (Saday) Sadayappan is a Professor at the University of Utah's School of Computing, specializing in high-performance computing and compiler optimizations. His research focuses on performance optimization for parallel systems, particularly for tensor computations, sparse matrix operations, and machine learning workloads. He leads multiple NSF and DARPA-funded projects focused on GPU optimization, tensor computations, and scalable machine learning frameworks. Research Interests: Dr. Sadayappan's work spans compiler optimizations for high-performance systems, optimization of sparse/dense matrix/tensor computations, scalable machine learning, and algorithm-architecture co-design. His recent projects include developing performance-portable frameworks for tensor applications and optimizing data locality for scientific computing. Publication Trends: His recent publications (2020-2022) predominantly focus on GPU acceleration of machine learning workloads (especially CNNs), automated I/O complexity analysis, and optimization techniques for sparse matrix/tensor operations. Earlier work (2018-2019) established foundations in GPU code generation for tensor contractions and cache optimization. Awards and Honors: ACM SIGPLAN Most Influential PLDI Paper Award (2018) for A Practical Automatic Polyhedral Parallelizer and Locality Optimizer Active Grants and Projects: NSF: A Comprehensive Framework for Efficient, Scalable, and Performance-Portable Tensor Applications (2022-2027) NIH SBIR: Enabling next generation machine learning for large scale image analysis (2023-2025) NSF: AI Institute for Intelligent CyberInfrastructure (ICICLE) (2021-2026) NSF: Data Locality Optimization for Sparse Matrix/Tensor Computations (2020-2024) DARPA SBIR: Performance Portable Framework for Developing Graph Applications (2017-2022) Teaching: He currently teaches CS 4230/6230 (Parallel and High-Performance Computing) at the University of Utah.

Leonidas Akritidisمشاهده پروفایل

مدرس

• Natural Language Processing
• Deep Machine Learning
• Data Mining
• +۵ مورد دیگر

Leonidas Akritidis serves as a Lecturer at the Department of Science and Technology within the School of Science and Technology at International Hellenic University. He holds a PhD and Diploma in Electrical and Computer Engineering from University of Thessaly and Aristotle University of Thessaloniki respectively. His educational background includes: PhD in Electrical and Computer Engineering, University of Thessaly (2007-2013) Diploma in Electrical and Computer Engineering, Aristotle University of Thessaloniki (1997-2003) Akritidis specializes in Natural Language Processing, Deep Machine Learning, and Data Mining with particular expertise in short text clustering, dimensionality reduction, and rank aggregation techniques. His research addresses challenges in sparse data environments and high-dimensional feature spaces, developing novel algorithms for text representation and processing. He has contributed significantly to parallel and distributed computing approaches for big data analytics. His publication trends reveal a consistent focus on NLP and machine learning applications, with recent work expanding into generative models for tabular data, medical image analysis, and advanced fault detection systems. The research demonstrates progression from foundational text processing techniques to more complex applications in healthcare, e-commerce, and software engineering. Akritidis has taught multiple courses including Big Data and Cloud Computing, Machine Learning Principles and Concepts, Mobile Application Development, and Web Programming. His research projects include CyberPi (intelligent cyber threat detection), NANOTRIM (transistor sizing optimization), and iMuSe (virtual museum platform). He collaborates extensively with researchers like Panayiotis Bozanis, Miltiadis Alamaniotis, and Athanasios Fevgas, primarily within the Greek academic community.

Theodore Kaskalisمشاهده پروفایل

استاد

• Digital Design
• Embedded Systems
• Computer Programming
• +۳ مورد دیگر

Professor Theodore Kaskalis is a faculty member at the Department of Applied Informatics within the School of Information Sciences at the University of Macedonia, Thessaloniki, Greece. He holds the position of Professor in "Informatics - Digital Systems' Programming", appointed in 2024. His educational background includes: Computer & Informatics Engineer from the Polytechnic School of Patras (1993), graduated with honors (8.62/10). Ph.D. in Parallel Distributed Processing from the Department of Applied Informatics, University of Macedonia (1998), with honors and supported by the Greek State Scholarships Foundation. Graduate of the School of Educational Officers for Vocational and Technical Education (SELETE) (1999), with honors (9.00/10). Professor Kaskalis' research spans several key areas in computing and informatics. His primary interests include Digital Design , Embedded Systems , and Computer Programming , which form the foundation of hardware and software development. Additionally, he focuses on Internet Computing , Parallel and Distributed Processing , and Grid Technologies , reflecting his expertise in large-scale computing environments and networked systems. His work bridges theoretical concepts with practical applications, particularly in educational technology as evidenced by his teaching of courses on digital environments in education. His scientific awards and honors are notable: Graduated with honors (8.62/10) as a Computer & Informatics Engineer from the Polytechnic School of Patras (1993). Ph.D. with honors, supported by a 3-year fellowship from the Greek State Scholarships Foundation (1998). Graduate of SELETE with honors (9.00/10) (1999). Regarding academic advising and research grants, the available information does not specify current students or detailed grant history. However, his extensive publication record (9 books, 19 journal articles, 41 conference papers, and 5 other works) suggests active research and mentorship. His teaching portfolio includes courses such as Application Development and Big Data, Web Programming, and Digital Systems Design, indicating a strong commitment to education. Information about specific laboratories or research teams led by Professor Kaskalis is not provided in the given text.

Christos Papadopoulos Filelisمشاهده پروفایل

استادیار

• Computational Mathematics
• Mathematical and Computational Physics
• Numerical Methods
• +۶ مورد دیگر

Christos Papadopoulos Filelis is an Assistant Professor at the Department of Electrical and Computer Engineering, Democritus University of Thrace, where he conducts research and teaches courses in computational mathematics and physics. His academic journey began with a Diploma in Electrical and Computer Engineering from Democritus University of Thrace in 2010, followed by a PhD in Numerical Analysis and High Performance Computing from the same institution in 2014. His research interests span Computational Mathematics, Mathematical and Computational Physics, Numerical Methods, Scientific Calculations, High Performance Computing, and Machine Learning applications in Mathematics and Physics. He has made significant contributions to pre-coordinated iterative methods, multi-grid and multi-level methods, parallel computing, cloud computing, and big data analytics. His work bridges theoretical mathematics with practical computational applications across multiple domains. Analysis of his recent publications reveals a strong focus on developing advanced computational techniques for solving complex mathematical problems, with particular emphasis on matrix computations, preconditioning methods, and time series analysis. His research demonstrates a consistent trajectory toward more efficient algorithms for high-performance computing environments, with increasing applications in machine learning and environmental sustainability. Dr. Papadopoulos Filelis has taught undergraduate courses including Physics, Numerical Analysis, Mathematical Software, Scientific Calculations, and Calculus of Changes. He has participated in European (H2020) and National funded projects such as the SFI FinTechNext project (UCC, Ireland), demonstrating his ability to secure competitive research funding. His work with the Physics Laboratory at Democritus University of Thrace involves developing computational frameworks that integrate theoretical physics with advanced numerical methods. He has collaborated extensively with researchers across Europe, particularly in cloud computing and high-performance computing projects that address real-world computational challenges.

• Software Engineering
• Cloud Computing
• Internet of Things
• +۳ مورد دیگر

Ευριπίδης Γ.Μ Πετράκης is a Professor & Laboratory Director at the School of Electrical and Computer Engineering, Technical University of Crete (TUC) since 1999. He holds a Ph.D. in Computer Science (University of Crete, 1993) and a B.Sc. in Physics (National University of Athens, 1985). His research focuses on Cloud Computing, IoT, Semantic Web, and Image Indexing, with over 175 publications and top international recognition including the 2024 AINA Best Paper Award and Stanford's Top 2% Global Impact ranking (2021-2023). Key projects include leading roles in Horizon 2020-funded BorderUAS (2020-2023), MARS smart farming initiative (2018-2021), and FP7-funded FI-STAR (2013-2016). He has pioneered solutions for IoT security (iBoT), edge-cloud computing (DeFog), and semantic service frameworks (OASL). His academic contributions span advanced distributed systems, including Apache Flink-based real-time video processing (Video2Flink) and Kubernetes optimization strategies. He also actively contributes to standards development for IoT interoperability and semantic web services.

• Stochastic Optimization
• Numerical Simulation
• Environmental Engineering
• +۳ مورد دیگر

Prof. Saridakis Yiannis is a Professor in the School of Production Engineering and Management at the Technical University of Crete. His research focuses on stochastic optimization, numerical simulation, and mathematical modeling of environmental systems and biomedical processes. He develops advanced numerical methods such as the Fokas transform, Hermite collocation, and Runge-Kutta schemes for solving reaction-diffusion equations, groundwater management challenges, and tumor growth models. His work integrates computational techniques like GPU acceleration and parallel algorithms for efficient problem-solving. Key research areas include: Stochastic optimization for coastal aquifer management Numerical treatment of discontinuous systems in environmental and biomedical models Development of high-performance computing strategies for complex PDEs Prof. Saridakis has contributed to over 50 peer-reviewed articles since 1985, exploring topics ranging from soliton cellular automata to modern GPU-based iterative methods. His research bridges applied mathematics, environmental engineering, and computational biology. His publications highlight innovative approaches in: Groundwater sustainability through stochastic algorithms Mathematical modeling of tumor invasion dynamics Parallel computing architectures for scientific problems Despite extensive contributions, no scientific awards are explicitly listed in the provided materials. His academic profile emphasizes technical expertise in numerical methods and their applications in interdisciplinary fields.

Vangelis Markakisمشاهده پروفایل

دانشیار

• Theoretical Computer Science
• Game Theory
• Mechanism Design
• +۳ مورد دیگر

Vangelis Markakis is an Associate Professor at the Department of Informatics, Athens University of Economics and Business (AUEB), where he has been a faculty member since 2009. He holds a PhD in Theoretical Computer Science from Georgia Institute of Technology (2005), an M.Sc. in Computer Science (Georgia Tech 2004), and a Diploma in Electrical and Computer Engineering from NTUA (2000). His academic career includes postdoctoral research at the University of Toronto and CWI (Amsterdam). Research Interests: Theoretical computer science, algorithm design, game theory, mechanism design, social networks, combinatorial optimization Awards: Recipient of the 2025 ACM SIGecom Test of Time Award for foundational work on fair allocations (2004) and the 2003 ACM EC Best Student Paper Award His work bridges algorithmic game theory, fair division, and computational economics, with notable contributions to approximation algorithms for Nash equilibria and auction mechanisms. He has supervised numerous PhD and MSc students, including prominent researchers now at institutions like University of Essex, NTU Singapore, and Yale. Scientific activities include extensive program committee memberships (ACM EC, AAAI, AAMAS, SAGT, WWW) and organizing conferences like ISCO 2012 and ACAC 2009. His teaching portfolio covers game theory, data structures, and advanced algorithms.

• Production Systems
• Business Processes
• Supply Chain Optimization
• +۴ مورد دیگر

George Ioannou is a Professor of Production Management and Business Processes at the Athens University of Economics and Business, where he leads the MBA International Postgraduate Program and the Center for Business Processes and ERP Systems at the Laboratory of Management Science. Previously, he served as Assistant Professor at Virginia Tech's Department of Production and Systems Engineering. His academic journey includes a B.Sc. in Mechanical Engineering from National Technical University of Athens, an M.Sc./DIC in Industrial Robotics/Production Automation from Imperial College London, and a Ph.D. in Mechanical Engineering from the University of Maryland. Current Academic Roles: Professor, Director of MBA Program, Head of ERP Systems Center Prior Academic Roles: Assistant Professor at Virginia Tech Education: B.Sc., M.Sc./DIC, Ph.D. His research focuses on integrating web-based technologies with operational research to optimize production systems, business processes, and supply chains. This spans applications in plant spatial planning, ERP systems, and cultural heritage digitization. He has secured research funding from global organizations including NSF, European Commission, and private sector leaders like Microsoft. Scientific awards include Microsoft's Excellence in Education Award and multiple teaching excellence recognitions for MBA programs. Ioannou serves on the Technical Chamber of Greece (TEE) and the editorial board of Production Planning & Control , with extensive consulting experience for public and private sector entities.

Dionysis Reisisمشاهده پروفایل

استاد

• Parallel Architectures
• Signal Processing
• Telecommunications
• +۳ مورد دیگر

Dionysis Reisis is Professor at the Department of Physics of the National and Kapodistrian University of Athens, leading the Digital Systems Team since 1991. His PhD in Electrical and Computer Engineering informs his research in parallel architectures, high-performance computing, and real-time systems for signal/image processing and telecommunications. He has served as Director of interdisciplinary MSc programs combining Electronics, Radioelectrology, Control and Computing. Research spans high-throughput systems for space applications, 5G telecommunications, and video encoding/decoding. Recent projects include FPGA-based accelerators for ESA space missions and award-winning student competitions in embedded systems design.

• Computer Architecture
• Memory Systems
• Hardware/OS Interaction
• +۷ مورد دیگر

Vasileios Karakostas is an Assistant Professor at the Department of Informatics and Telecommunications, National and Kapodistrian University of Athens. He is a member of the Computer Architecture Lab and focuses on computer architecture, memory systems, and resource management. Previously, he was a postdoctoral researcher at the National Technical University of Athens' Computing Systems Lab. He holds a PhD in Computer Architecture from Universitat Politècnica de Catalunya and Barcelona Supercomputing Center. Education: Ph.D. in Computer Architecture, Universitat Politècnica de Catalunya (2016) M.Sc. in Computer Architecture, Networks, and Systems, UPC (2012) B.Eng. in Electrical and Computer Engineering, NTUA (2009) Research Interests: Memory systems (virtual memory, NVM) Hardware/OS interaction Resource management in data centers Parallel systems and serverless computing RISC-V architectures and cloud infrastructure Projects: Active in Horizon Europe projects Vitamin-V, Neuropuls, and REBECCA. Previously contributed to DAPHNE and ACTiCLOUD (EU H2020). Awards: 2024: Distinguished Artifact Award (ASPLOS) 2011: Best Paper Award (ICPE) Selected for IEEE Micro's Top Picks (2015, 2016) Teaching: Courses include Logic Design, Parallel Systems, and Large-scale Computing Systems at undergraduate and graduate levels. Labs/Teams: Leads research in the Computer Architecture Lab, collaborating on resilient architectures and cloud computing innovations.

• Algorithmic Game Theory
• Approximation Algorithms
• Facility Location Problems
• +۲ مورد دیگر

Dimitris Fotakis is Professor of Computer Science at the National Technical University of Athens (NTUA) and Collaborating Senior Researcher at the Archimedes Unit/ATHENA RC. His research in theoretical computer science focuses on algorithmic game theory, approximation algorithms, and facility location problems. He leads research projects including BALSAM (Beyond Worst-Case Analysis in Approximation Algorithms) funded by HFRI. With publications in ICALP, NeurIPS, and STOC, his work develops efficient algorithms for optimization under uncertainty. Fotakis serves on program committees of major conferences including ICALP and SAGT.

• High-Performance Computing
• Parallel Processing
• Code Optimization
• +۳ مورد دیگر

Georgios Goumas is an Associate Professor in the Division of Computer Science at the School of Electrical and Computer Engineering, National Technical University of Athens. His research focuses on high-performance computing, parallel systems, and efficient resource management for modern computing platforms. Research domains: Serverless computing scalability and memory management Quantum algorithm design for classification Virtual memory optimization Hardware acceleration for sparse computations NUMA-aware concurrent data structures Recent innovations include DaeMon for disaggregated systems, eBPF-based Linux memory management, and multi-GPU matrix multiplication optimizations. Publications demonstrate consistent advancement in low-level system efficiency across quantum, serverless, and heterogeneous computing domains. Dr. Goumas teaches undergraduate and graduate courses on Operating Systems, Parallel Processing, and Code Optimization Techniques. His lab develops open-source tools like Paralia runtime for auto-tuning linear algebra and FPGA-based accelerators for scientific computing.