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Doulkeridis ChristosView profile

Professor

• Big Data
• Data Management in Cloud Computing
• Query Processing
• +5 more

Christos Doulkeridis is a Professor at the Department of Digital Systems, University of Piraeus. Specializing in big data management, distributed systems, and mobility analytics, he has led projects such as CHOROLOGOS (ELIDEK-funded) and contributed to EU initiatives like datAcron and Track&Know. He holds Marie-Curie and ERCIM fellowships, and his work emphasizes energy-efficient data architectures and semantic trajectory analysis. Education: PhD in Informatics, Athens University of Economics and Business (2007) MSc in Informatics, Athens University of Economics and Business (2003) Diploma in Electrical & Computer Engineering, National Technical University of Athens (2001) Research Interests: Big data analytics, cloud computing, spatiotemporal query processing, mobility forecasting (e.g., traffic patterns, maritime monitoring), and semantic trajectory modeling. His work bridges theory with practical applications in smart cities and environmental sustainability. Awards: Winner of SemEval’17 Task4 (sentiment analysis) Best Paper Award at EuroVA’19 Michalis Dertouzos Award (2004) for Human Face of Computing Grants & Projects: Principal Investigator for CHOROLOGOS (semantic spatiotemporal data) Core contributor to datAcron (maritime data ontology) European projects: BigDataStack, RoadRunner (ARISTEIA II) Labs & Teams: Leads research teams developing frameworks like SPARTAN (semantic integration) and ARGO (trajectory prediction). Collaborates on open-source tools like ST_VISIONS (spatiotemporal visualization) and NoDA (unified NoSQL access).

Christos NomikosView profile

Associate Professor

• Algorithm Design and Analysis
• Approximation Algorithms
• Computational Complexity
• +3 more

Christos Nomikos is an Associate Professor at the Department of Computer Science and Engineering, University of Ioannina. He holds a PhD from the National Technical University of Athens (NTUA) and has been a faculty member since 2003. His roles include teaching and research supervision in computer science disciplines. Education: Diploma in Electrical Engineering, NTUA, 1992 PhD in Computer Science, NTUA, 1997 Research Interests: Christos Nomikos focuses on theoretical computer science and logic, including algorithm design and analysis, computational complexity, formal languages, logic programming, and graph theory. His work explores foundational aspects of programming languages and their semantics, as well as applications in knowledge representation and automated reasoning. Teaching: In the 2024-25 academic year, he teaches Discrete Mathematics II , Principles of Programming Languages , Computational Complexity , and Approximation Algorithms . He emphasizes structured learning approaches and maintains a dedicated ecourse page for students. Advising & Grants: He supervises undergraduate thesis projects in computer science, with a focus on theoretical topics like Turing machine transformations and Boolean grammar algorithms. No explicit grant information is provided in the texts. His advising process involves rigorous academic evaluation and prefers candidates with strong performance in core computer science courses. Labs/Teams: While no specific lab or team affiliations are mentioned, his research collaborations include work with international conferences and journals, indicating active participation in academic networks.

• Applied Mathematics
• Computational Science
• Groundwater Management
• +4 more

Professor Elena Papadopoulou is a faculty member at the Technical University of Crete within the School of Mineral Resources Engineering . Her research focuses on applied mathematics and computational science , addressing problems in groundwater dynamics, tumor modeling, and numerical methods for partial differential equations. Key Research Areas: Stochastic optimization for coastal aquifer management GPU-accelerated simulations for biomedical applications High-order numerical schemes for reaction-diffusion systems Unified transforms in multi-domain PDEs She has published extensively on saltwater intrusion modeling , brain tumor invasion , and parallel computing algorithms . Her work integrates mathematical modeling with environmental and medical challenges , emphasizing computational efficiency and environmental sustainability. Contact : epapadopoulou@tuc.gr

• Parallel Computing
• Distributed Systems
• Multiprocessor Operating Systems
• +5 more

Vasilios Mamalis is a Professor at the Department of Informatics and Computer Engineering, University of West Attica, and a member of the Collaborating Scientific Staff at the Hellenic Open University's Informatics program. His academic career spans decades with significant contributions to parallel and distributed computing, wireless sensor networks, and cloud technologies. Education: Diploma in Computer Engineering and Informatics, University of Patras (1993) PhD in Computer Engineering and Informatics, University of Patras (1998) Research Interests focus on parallel algorithms, distributed systems, wireless sensor networks, cloud computing, and information retrieval. His work addresses energy efficiency in ad-hoc networks, optimization techniques, and educational technology applications. Publication Trends show extensive work on WSN clustering, cloud task scheduling, parallel simplex methods, and fog computing applications in education and urban systems. He combines metaheuristics with infrastructure optimization in large-scale networks. Scientific Contributions include editorial roles in the Journal of Balkan Libraries Union and program committee memberships in international conferences. He actively reviews for journals and conferences in computing. Teaching Expertise covers operating systems, parallel computing, distributed systems, and cloud technologies at both undergraduate and postgraduate levels. His Research Leadership involves EU/Greek-funded projects on communication protocols, parallel content-based retrieval, and wireless sensor networks.

George LentarisView profile

Assistant Professor

• Computer Engineering
• Hardware Engineering
• Digital Signal Processing
• +3 more

George Lentaris is an Assistant Professor at the Department of Computer Engineering, School of Engineering, University of West Attica. He is also a researcher at the National Technical University of Athens (associate, first level). Education: PhD in 'Parallel Architectures and Algorithms for Digital Signal and Image Processing' from National & Kapodistrian University of Athens Master's in 'Logic and Theory of Algorithms and Computation' Master's in 'Electronic Automation' Bachelor's in Physics from National & Kapodistrian University of Athens Research Interests: Design of hardware units and high-performance embedded systems FPGA and multi-core architectures HW/SW heterogeneity and optimization Acceleration of algorithms for space, telecommunications, and edge computing applications Professional Contributions: Participated in 18+ research projects funded by European Space Agency, Horizon, and NSRF Published 60+ scientific articles, including 21+ in journals like IEEE/ACM Transactions and 40+ in international conferences

• Computer Engineering
• Embedded Systems
• Image Processing
• +3 more

Kranitis Nektarios is a Lecturer at the Department of Informatics and Telecommunications, National and Kapodistrian University of Athens. His research focuses on FPGA-based hardware architectures, space-grade computing, and image compression standards like CCSDS, with applications in satellite systems and reliable data processing. Primary affiliation: National and Kapodistrian University of Athens Department: Informatics and Telecommunications Research interests center on space-grade SRAM FPGAs , LDPC encoding , hyperspectral image compression , and software-based self-test methodologies for embedded systems. His work addresses high-speed data processing and fault tolerance in satellite communications. Key trends in his publications include CCSDS standard implementations , hardware accelerators for image compression, resilience to SEUs , and energy-efficient testing techniques for microprocessors. Topics span space systems , parallel computing , and digital circuit design .

• Scientific Calculations
• Parallel Algorithms
• Operational Research

Tzaferis Philippos is an Assistant Professor at the Department of Informatics , School of Sciences , National and Kapodistrian University of Athens (NKUA), with a career spanning since 1982. His primary academic roles include teaching and research in theoretical computer science, focusing on scientific calculations, parallel algorithms, and operational research. Education : Bachelor of Mathematics (1980), Master's in Informatics and Operations Research (1982), PhD in Computer Science (1994) from NKUA. Research Interests center on high-performance computing, numerical methods for linear systems, and algorithm optimization. His work bridges theoretical computer science with practical applications in parallel processing and mathematical modeling. Professional Career Highlights : Assistant Professor at NKUA Department of Informatics (2009–Present) Lecturer at NKUA Department of Informatics (1995–2009) Scientific Associate roles in Informatics and Mathematics departments (1986–1995)

George PapadimitriouView profile

Assistant Professor

• Computer Architecture
• Energy-Efficient Architectures
• Microprocessor Reliability
• +7 more

George Papadimitriou is an Assistant Professor in the Computer Engineering & Informatics Department at the University of Patras , Greece, hosted within the School of Engineering . His primary affiliation lies with the Computer Hardware and Architecture division, where he leads research and teaching activities focused on dependable, energy-efficient computer architectures. Education: PhD in Computer Science, Department of Informatics & Telecommunications, National and Kapodistrian University of Athens (2019) Post-doctoral researcher, Computer Architecture Lab, National and Kapodistrian University of Athens Research Interests: Dr Papadimitriou’s research lies at the intersection of computer architecture , energy efficiency , and microprocessor reliability . His work specifically targets: Robust and energy-efficient CPU/GPU/accelerator architectures Post-silicon validation techniques for catching elusive hardware bugs Silent data corruption detection and mitigation across the compute stack Characterization of voltage margins and power consumption in modern microprocessors Modeling and simulation of domain-specific accelerators for low-power, dependable operation More recently, his team has been extending these methodologies to RISC-V and neuromorphic photonic accelerators within large European consortia. Scientific Awards & Recognition: Eight HiPEAC Paper Awards for top-tier conference publications (MICRO, HPCA, ISCA) between 2017–2024 IEEE Transactions on Computers 2022 Best Paper Award for the article “Anatomy of On-Chip Memory Hardware Fault Effects Across the Layers” TTTC/ITC Gerald W. Gordon Student Award 2023 Research Funding & Projects: Dr Papadimitriou is principal investigator or key technical contributor in multiple Horizon Europe and industry-backed projects that collectively exceed €50 M in funding. Current leadership roles include: DARE (Digital Autonomy for RISC-V in Europe) NEUROPULS (Neuromorphic Energy-Efficient Secure Accelerators) REBECCA (Reconfigurable Heterogeneous Highly Parallel Processing Platform) Vitamin-V (Virtual Environment & Tool-boxing for Trustworthy RISC-V Cloud Services) Intel, IBM, and Thales bilateral research contracts on energy-efficient and resilient microarchitectures Laboratory & Team: He leads the Energy-Efficient and Dependable Architectures (EEDA) research group at University of Patras, operating laboratory facilities for silicon measurement, FPGA emulation, and full-system simulation (gem5, MARSS, custom tools). The team currently comprises 3 PhD candidates, 2 post-docs, and several MSc thesis students collaborating with European and US partners.

• Social Data Science
• Digital Humanities
• Quantitative and Computational Social Science
• +4 more

Panagiotis Michailidis is a Professor at the Department of Balkan, Slavic and Oriental Studies, School of Economic and Regional Studies, University of Macedonia. His academic work focuses on Computational Methods and Informatics, integrating technological expertise with regional studies. BSc (1998) and PhD (2004) in Applied Informatics from University of Macedonia Academic career progression: Lecturer (2004-2013), Assistant Professor (2014-2019), Associate Professor (2019-2023), now Professor Research spans computational approaches to social science and humanities, with significant contributions to: Social Data Science Digital Humanities Quantitative Social Science Parallel/Distributed Computing String Matching Algorithms Scientific Computing Recent publications reveal interdisciplinary focus combining: Augmented Reality applications for cultural heritage Machine Learning for Greek language sentiment analysis High-performance computing implementations Metaheuristic optimization techniques Scientometric analyses of research fields Active in academic service through: IEEE memberships Conference program committee roles Guest editor for Algorithms special issue Research program participation Reviewing for multiple journals Teaching portfolio includes: DIGITAL SOCIAL RESEARCH METHODS INFORMATION, TECHNOLOGY AND SOCIETY QUANTITATIVE METHODS OF SOCIAL SCIENCES SPACE AND CULTURAL MANAGEMENT COMPUTER SCIENCE TOPICS

• Operating Systems
• Parallel Computing
• Scheduling in Parallel Systems
• +3 more

Ioannis Venetis is an Assistant Professor at the University of Piraeus, School of Information and Communication Technologies, Department of Informatics, specializing in Operating Systems and Parallel Computing. He earned his PhD from the Department of Computer Engineering and Informatics at the University of Patras. His research spans programming models for parallel systems, scheduling optimization, and applications in computational neuroscience and seismology. Research Interests Operating Systems Parallel Computing Scheduling Algorithms High-Performance Computing Computational Neuroscience Seismology Projects Participation in European and national research programs Development of Gisola (GPU-accelerated seismic inversion tool) His teaching portfolio includes courses like Operating Systems, Parallel Processing, and Symbolic Programming. Articles highlight expertise in GPU acceleration, tridiagonal solvers, sensor networks, and many-core architectures. Notable contributions include work on Chimera states in neuronal dynamics and hierarchical workload scheduling frameworks.

Dimitrios SoudrisView profile

Professor

• Computer Engineering
• Embedded Systems
• Reconfigurable Architectures
• +5 more

Dimitrios Soudris is a Professor at the School of Electrical and Computer Engineering, National Technical University of Athens (NTUA), leading the Microprocessor and Digital Systems Lab (MicroLab). Previously, he served as Lecturer, Assistant, and Associate Professor at Democritus University of Thrace from 1995 to 2008. Diploma in Electrical Engineering (1987), University of Patras PhD in Electrical Engineering (1992), University of Patras His research focuses on Embedded Systems , Reconfigurable Architectures (FPGAs) , Hardware Accelerators for data centers/space/cloud, Edge Computing , and Low Power VLSI Design . Recent publications highlight trends in: AI/ML acceleration for edge and space applications Secure FPGA architectures for 6G networks Energy-efficient heterogeneous memory systems Approximate computing techniques Transformer optimization for low-power contexts Scientific Awards: INTEL and IBM awards (project LPGD #25256) HiPEAC, DAC, and ISCA awards (2010–2024) XILINX Open Hardware Design Contest (2017, 2019, 2021) He has coordinated >70 R&D projects funded by the European Commission, ENIAC-JU, ESA, and industry partners. As Associate Editor of ACM TODAES and conference chair (PATMOS, VLSI-SOC), he contributes to academic leadership. His lab, MicroLab, specializes in hardware-software co-design for emerging computing paradigms.

Gilbert BernsteinView profile

Assistant Professor

• Computer Graphics
• Programming Languages
• High-Performance DSLs
• +7 more

Gilbert Bernstein is an Assistant Professor in the Computer Science & Engineering department within the College of Engineering at the University of Washington. His research bridges computer graphics and programming languages, with a focus on high-performance domain-specific languages. Previously, he was a post-doctoral scholar at UC Berkeley and MIT working with Jonathan Ragan-Kelley, and received his PhD from Stanford University under Pat Hanrahan. His research interests span Computer Graphics, Programming Languages, High-Performance DSLs, Physical Simulation, Geometry & Topology, Differentiable Programming, Hardware DSLs, Tools for Artists, Fabrication, and Human-Computer Interaction. Bernstein develops languages and compilers that enable efficient computation for creative applications, physical simulations, and graphics rendering systems. His recent publications reveal strong trends in differentiable programming for graphics applications, domain-specific languages for hardware acceleration, and computational approaches to traditional crafts like quilting and knitting. His work consistently combines formal language theory with practical applications in graphics and fabrication. Bernstein actively mentors students across multiple institutions including current advisees Felix Hahnlein (UW Postdoc), Ryan Zambrotta (UW PhD), Haoran Peng (UW PhD), and previous students including Alex Reinking (UC Berkeley PhD 2022, now at Qualcomm) and MacKenzie Leake (Stanford PhD 2021, now at Adobe Research). His lab works on diverse projects including debugging CAD programs, compilers for finite element methods, semantics for knitting machines, algebraic scheduling of tensor programs, and exocompilers for hardware accelerators. Bernstein also collaborates on DSLs for networking, Counterstrike bots, gradient-based optimization, memory management, hardware design, and garment design tools.

Byron CookView profile

Professor

• Verification
• Automated Reasoning
• Program analysis
• +8 more

Byron Cook is Professor of Computer Science at University College London (UCL) and Director of Automated Reasoning at Amazon Web Services. He leads Amazon's Automated Reasoning Group (ARG) and has driven the broad adoption of formal methods across AWS services. His career spans academia and industry, with significant contributions to program verification and automated reasoning. His research focuses on verification, automated reasoning, program analysis, computer/network security, programming languages, theorem proving, logic, and applications to hardware design, operating systems, and biological systems. Cook's work bridges theoretical foundations with practical applications in cloud security and system reliability, particularly through his leadership in applying formal methods to AWS infrastructure. Cook's recent publications demonstrate a strong focus on applying automated reasoning to cloud security challenges, particularly around access control policies, network reachability, and cryptographic implementations. His work shows a clear trajectory from theoretical program verification toward practical security applications in large-scale cloud environments, with emphasis on making formal methods accessible to developers through "one-click" verification tools. Scientific Awards: FREng (Fellow of the Royal Academy of Engineering) As an academic advisor, Cook has mentored numerous PhD students and interns who have gone on to significant careers in programming languages and verification research. His work at Amazon has secured substantial research funding for developing and deploying automated reasoning tools across AWS services. Cook founded and leads Amazon's Automated Reasoning Group (ARG), which develops tools like IAM Access Analyzer, Tiros, Zelkova, and T2. Previously, he managed the Programming Principles and Tools (PPT) group at Microsoft Research Cambridge, where he co-founded projects including TERMINATOR, SLAyer, and the Bio Model Analyzer (BMA).

Laura DietzView profile

Associate Professor

• Information Retrieval
• Machine Learning
• Natural Language Processing
• +6 more

Laura Dietz is a tenured Associate Professor in the Department of Computer Science at the University of New Hampshire, where she leads the TREMA lab. Her academic journey began with a PhD from the Max Planck Institute for Informatics in Saarbruecken, Germany (2011), followed by postdoctoral positions at the University of Massachusetts Amherst (2010-2015) and University of Mannheim (2015-2016). Her educational background includes PhD studies at both the Max Planck Institute for Informatics (2007-2011) under Prof. Gerhard Weikum and Prof. Tobias Scheffer, and earlier research at Humboldt University in Berlin. She has built a distinguished career bridging theoretical computer science with practical applications in information retrieval and machine learning. Dietz's research primarily focuses on the intersection of information retrieval, natural language processing, and knowledge graphs, with a parallel research initiative in watershed data science. She is particularly known for her work on entity-aspect linking, complex answer retrieval, and the vision of automatic Wikipedia construction. Her approach integrates fine-grained knowledge annotations with text understanding to create comprehensive information systems that go beyond traditional 10-blue-links search paradigms. In watershed data science, she applies similar machine learning techniques to environmental data streams, focusing on solute transport analysis during storm events. Her recent publications reveal a strong trend toward fine-grained semantic understanding, particularly in entity-oriented search tasks. She has pioneered methods for entity-aspect linking that significantly improve retrieval accuracy by capturing different contexts in which entities appear. Her work increasingly integrates knowledge graphs with neural architectures, showing sophisticated understanding of how to leverage both structured and unstructured information for better search experiences. Best paper award at JCDL 2018 for work on entity-aspect linking NSF CAREER Award (2019-2023) for "Utilizing Fine-grained Knowledge Annotations in Text Understanding and Retrieval" OSSI Award 2013 from UMass ICB3 for open-source hardware/software Dietz actively mentors PhD and Masters students through the TREMA lab, with current research focusing on entity ranking, topic extraction, conversational search, and watershed forecasting. Her grant portfolio includes the NSF CAREER award and funding from the Northeast Big Data Innovation Hub for forecasting salinity in rivers during storm events. She has also coordinated the TREC Complex Answer Retrieval track (2017-2019), creating important benchmarks for the IR community. The TREMA lab (Text Retrieval, Entity Modeling, and Applications) serves as the hub for Dietz's research activities, bringing together students and collaborators to work on cutting-edge problems in information access. The lab's work spans both theoretical contributions to information retrieval and practical applications in domains ranging from environmental science to scientific publication analysis.

Rajiv GuptaView profile

Professor

• Parallel Computing
• Compilers
• Computer Architectures
• +4 more

Rajiv Gupta is a Distinguished Professor and the Amrik Singh Poonian Professor of Computer Science at the University of California, Riverside (UCR), where he serves as Associate Dean for Academic Personnel in the Bourns College of Engineering (BCOE). He is a member of the RIPLE research group and has co-authored 327 papers with an h-index of 69 and over 16,600 citations. His extensive service includes chairing major conferences such as FCRC 2015, PPoPP 2020, ASPLOS 2011, and PLDI 2008. Professor Gupta's research focuses on Programming, Compiler, Runtime & Architectural Support for Parallel & Distributed Heterogeneous Systems and Software Tools for Monitoring and Managing Runtime Behavior . His work spans graph analytics with scalability and performance, understanding and managing the dynamic behavior of parallel programs, software speculation for irregular parallelism, dynamic program analysis for secure and reliable computing, and compiler optimizations with architectural support. His research has significant applications in high-performance computing, GPU programming, and distributed systems. Analysis of his recent publications reveals a strong focus on graph processing systems, with particular emphasis on evolving and streaming graph analytics. His work addresses critical challenges in memory management for large-scale graph processing, hardware acceleration for graph algorithms, and optimization techniques for concurrent and distributed graph computations. The research demonstrates a progression from foundational compiler and architecture work to increasingly sophisticated systems for handling modern data-intensive computing challenges. Fellow of the ACM (2009) Fellow of the IEEE (2008) Fellow of the AAAS (2011) NSF Presidential Young Investigator Award (1991) UCR Doctoral Dissertation Advisor/Mentor Award (2012) Multiple best paper awards across major conferences Two students won ACM SIGPLAN Outstanding Doctoral Dissertation Award Five advisees received NSF CAREER Award Professor Gupta has supervised 42 PhD students to completion and currently advises several doctoral candidates. His advising success is reflected in his students' achievements, including multiple award-winning dissertations and significant career accomplishments in academia and industry. His research has been supported by numerous grants from NSF, DARPA, and industry partners, enabling sustained investigation into parallel computing systems. The RIPLE research group under his leadership has produced influential work that bridges theoretical foundations with practical system implementations. As the leader of the RIPLE research group at UC Riverside, Professor Gupta oversees a vibrant team focused on innovative approaches to parallel and distributed computing. The group maintains strong collaborations with industry partners and other academic institutions, contributing to the development of next-generation computing systems. Current projects include GRASP (Graph Analytics with Scalability & Performance) and research on understanding and managing the dynamic behavior of parallel programs, reflecting the group's continued focus on cutting-edge computing challenges.