جست‌وجوی استاد و پژوهشگر

Vassilis P. Plagianakosمشاهده پروفایل

دانشیار

• Machine Learning
• Neural Networks
• Bioinformatics
• +۵ مورد دیگر

Vassilis P. Plagianakos is an Associate Professor at the Department of Computer Science and Biomedical Informatics, University of Thessaly, Greece. He has held visiting academic roles at the University of the Aegean, University of Patras, and University of Central Greece. He currently serves as the Department Head and Director of the postgraduate program Informatics and Computational Biomedicine in the School of Sciences. His research focuses on machine learning, neural networks, bioinformatics, and parallel computing with applications in healthcare and education. Education : Bachelor’s in Mathematics (1996), University of Patras Ph.D. in Mathematics (2003), University of Patras Research Interests : Plagianakos explores neural networks, evolutionary algorithms, and machine learning applications in bioinformatics, medical diagnosis, and educational technology. His work bridges computational methods with real-world challenges in healthcare (e.g., precision medicine) and STEM education (e.g., flipped classrooms, AI integration). Recent Trends in Publications : Recent work emphasizes predictive precision medicine using big data, blockchain scalability solutions, and AI ethics in automated content detection. He has pioneered methods like the HCER hierarchical clustering-ensemble regressor and developed tools for analyzing single-cell RNA sequencing data. Professional Activities : Member of IEEE Neural Networks Society, IEEE BBTC, and former Board Member of the Hellenic AI Society. Active in collaborative projects like CrowdHEALTH for policy-driven health data analytics.

Nikolaos Papaspyrouمشاهده پروفایل

استاد

• Programming Languages
• Software Engineering
• Formal Verification
• +۴ مورد دیگر

Nikolaos Papaspyrou is a Professor at the School of Electrical and Computer Engineering of the National Technical University of Athens (NTUA) and a member of the Software Engineering Laboratory . His research focuses on the theory and implementation of programming languages, including semantics, type systems, compilers, static analysis, and formal verification. Since October 2021, he has been on leave from NTUA, working as a Software Engineer for Google in the memory management team for the V8 JavaScript and WebAssembly engine. He previously served as Director of the Division of Computer Science (2017-2019) and was on sabbatical with Google's compiler group in Munich (2015-2016). His work includes the RELEASE project (EU FP7 STREP) for reliable large-scale server software and uncertainty handling in distributed databases (European Social Fund). Ph.D. and Diploma in Electrical and Computer Engineering from NTUA M.Sc. in Computer Science from Cornell University His research interests span programming languages , software engineering , and formal verification , with recent publications on coinductive proofs in Liquid Haskell, concurrency semantics, and quantum compilation. He has supervised over 50 diploma projects and mentored numerous students now at institutions like MIT, Princeton, and UC Berkeley. Awards include conference organizing and program committee roles, though no formal scientific prizes are listed.

Diomidis Spinellisمشاهده پروفایل

استاد

• Software Engineering
• Programming Languages
• Computer Science
• +۵ مورد دیگر

Professor Diomidis Spinellis is a renowned academic in Software Technology at Athens University of Economics and Business (AUEB). He specializes in software engineering practices, code quality, AI ethics, and system architecture. His work bridges theoretical advancements with practical applications in industry, emphasizing reproducibility and empirical methods. Recipient of the IEEE Computer Society's prestigious 'Distinguished Contributor Recognition,' Spinellis is the sole Greek scientist to achieve this honor. His research spans software evolution, security, and open-source ecosystems, with a focus on methodologies like refactoring, static analysis, and debugging strategies. Key research interests include AI-generated content detection, modular data analytics, and incident management systems. His studies often leverage large-scale datasets (e.g., Unix evolution, Linux supercomputing analysis) to uncover patterns in software behavior and development practices. Publications frequently address emerging technologies' societal impacts, such as energy-efficient computing and ethical AI deployment. He advocates for reproducible research through tools like the Alexandria3k framework and contributes to open-source initiatives.

Evaggelia Pitouraمشاهده پروفایل

استاد

• Data Management
• Distributed Databases
• Database Systems
• +۷ مورد دیگر

Evaggelia Pitoura is a Professor in the Department of Computer Engineering and Informatics at the University of Ioannina, Greece, and a Lead Researcher at the Archimedes Research Unit, ATHENA Research Center. Her work spans data management, distributed systems, and mobile computing, with a strong focus on database personalization and diversity. Her research interests include data diversity, contextual preferences, XML data management, peer-to-peer systems, and mobile computing . She has pioneered work in result diversification, preference-aware querying, and distributed data indexing, publishing extensively in top venues such as PVLDB, ICDE, SIGMOD, and IEEE TPDS. The recent publications highlight a consistent trend in personalized, context-aware database systems , with emphasis on improving user experience through intelligent query processing, recommendation, and efficient data organization in distributed environments. Best Paper Award, SIGMOD 1999 Best Paper Award, PVLDB 2013 She has advised several PhD students, including Georgia Koloniari, Kostas Stefanidis, Marina Drosou, and Konstantinos Semertzidis, who now hold positions in academia and industry. She teaches courses in Databases and Information Retrieval and actively contributes to the academic community through program committee roles in major conferences like ICDE, VLDB, SIGMOD, and WWW. She leads the Distributed Management of Data Group , fostering innovation in scalable and intelligent data systems.

Minos Garofalakisمشاهده پروفایل

استاد

• Data Stream Management
• Complex Event Processing
• Differential Privacy
• +۵ مورد دیگر

Minos Garofalakis is a Professor at the School of Electronic & Computer Engineering at the Technical University of Crete, specializing in data stream management, complex event processing, and privacy-preserving analytics. His work bridges theoretical and applied computer science, with a focus on scalable algorithms for high-velocity data. Best Paper Award at VLDB 2024 for 'OmniSketch' Leader in sketch-based and distributed stream processing Pioneer in differential privacy for relational data Research interests span stream analytics , probabilistic databases , and interactive query systems . Recent work includes oblivious parallel joins (2025), relational data synthesis under privacy constraints (2024), and cross-platform analytics frameworks (2020). His publications demonstrate a consistent focus on error-controlled approximations and real-time distributed processing. Scientific contributions have been recognized at premier conferences like VLDB, with awards highlighting innovations in multi-dimensional stream analysis and privacy-preserving operations . Collaborations span academia and industry, particularly in bioinformatics and distributed systems.

• Data Science
• Mobility Data Management and Mining
• Knowledge Discovery in Data (KDD)
• +۴ مورد دیگر

Professor Nikolaos Pelekis is a faculty member at the University of Piraeus, Greece, holding the position of Professor in the Department of Statistics and Insurance Science within the School of Finance and Statistics. His academic career focuses on Data Science, with a specialized emphasis on Mobility Data Management and Mining, a field he has contributed to for over two decades. He has authored two monographs and over 100 peer-reviewed articles, earning five Best Paper Awards and over 5,000 citations. Research Interests: Mobility Data Management and Mining Big Data Analytics Machine Learning Geographical Information Systems His work spans trajectory analysis, maritime and vessel traffic forecasting, and spatiotemporal data management. Notable projects include leading roles in EU-funded initiatives like GREEN.DAT.AI and EMERALDS, focusing on energy-efficient AI and urban mobility analytics. Awards and Recognition : Five Best Paper Awards, including the Ralf H. Güting Best Research Paper Award (2021) and Best Demo Paper Awards at SIGSPATIAL (2021). He also ranked 1st in the SemEval-2017 Task 4 for sentiment analysis. Professional Contributions : Serves on editorial boards (e.g., ECML PKDD, DMKD) and organizes workshops like BMDA. His teaching spans undergraduate and graduate courses in Data Science, Big Data Management, and Statistical Data Mining. Labs and Teams : Co-founder of the Data Science Lab at the University of Piraeus, collaborating across 4 departments and multiple researchers. Current efforts include maritime digitalization (VesselAI) and real-time trajectory prediction frameworks like ARGO.

Kalogeraki Vanaمشاهده پروفایل

استاد

• Distributed Systems
• Real-Time Systems
• Big Data Systems
• +۸ مورد دیگر

Prof. Vana Kalogeraki is a Faculty Member at the Department of Informatics , Athens University of Economics and Business (AUEB) , and serves as the Dean of the School of Information Sciences and Technology and Director of the Computer Systems and Communications Laboratory . She has held academic positions at the University of California, Riverside and was a Research Scientist at Hewlett-Packard Labs . PhD: University of California, Santa Barbara M.S. & B.S.: University of Crete, Greece Her research focuses on Distributed and Real-Time Systems , Big Data Systems , Cloud Computing , Human-Centered Systems , and Crowdsourcing . She has published over 200 papers at top journals (IEEE TPDS, ACM TOS, etc.) and conferences (RTSS, DSN, ICDCS, VLDB, MDM), including co-authoring the OMG CORBA Dynamic Scheduling Standard . Her 2023-2025 publications address AI pipelines in serverless environments, edge computing for trauma detection via eye-tracking, and fairness in resource scheduling. She has received prestigious awards including an ERC Starting Grant , Best Paper Awards (DEBS 2017, IPDPS 2009), a Best Poster Award (EuroSys 2024), and multiple UC Research Awards . Her research is funded by the European Union (ARISTEIA, THALIS), NSF, and industry partners like SUN and Nokia. Advising Legacy : Supervised 10 PhD graduates (now at Google, Amazon, IBM, Apple) and over 60 MS/PhD committees Labs & Teams : Leads the Computer Systems and Communications Laboratory at AUEB, focusing on mobile human-centered systems and urban data analytics

Michael D. Bondمشاهده پروفایل

استاد

• Programming Languages
• Systems
• Security
• +۶ مورد دیگر

Michael D. Bond is a Professor in the Department of Computer Science & Engineering at Ohio State University's College of Engineering. He leads the Programming Languages and Software Systems (PLaSS) Research Group, which focuses on designing program analyses and software and hardware systems that enhance computing reliability, scalability, and security. His academic service includes general chair for PLDI 2027, program committee membership for multiple top conferences, and committee roles in SIGPLAN Research Highlights (2024-2027). Professor Bond's research spans programming languages, systems, and security, with particular expertise in memory management, concurrency, hardware transactional memory, information flow control, and predictive race detection. His work bridges theoretical foundations with practical implementations, as evidenced by numerous open-source projects accompanying his publications. The PLaSS group has made significant contributions to understanding and improving memory models, developing efficient garbage collection techniques for modern architectures, and creating novel approaches to secure programming in languages like Rust. Analysis of his recent publications reveals a clear trajectory toward addressing security and reliability challenges in modern computing systems, particularly through language-based approaches. His work increasingly focuses on Rust programming language security mechanisms, memory disaggregation for datacenters, and advanced techniques for detecting and preventing concurrency bugs. The research demonstrates strong continuity in exploring memory models and concurrency while adapting to emerging hardware trends and security challenges. Outstanding Teaching Award, Department of Computer Science and Engineering, Ohio State University (2018) Lumley Research Award, College of Engineering, Ohio State University (2016) OOPSLA 2015 Distinguished Paper and Artifact Awards NSF CAREER Award ACM SIGPLAN Outstanding Doctoral Dissertation Award Intel PhD Fellowship Professor Bond actively mentors several PhD students including Chujun Geng, Vincent Beardsley, Chris Xiong, Victor Chen, and Noah Charlton, with external co-advisee Zixian Cai at Australian National University. His research is currently supported by multiple NSF grants including SaTC-2348754 (2024-2027), CyberCorps-2336531 (2024-2029), and CSR-2106117 (2021-2025), reflecting sustained funding for his work in information flow control, security, and systems research. The PLaSS Research Group maintains a strong presence in both academic and industrial communities, with graduated PhD students securing positions at major technology companies like Google, Amazon Web Services, and Huawei, as well as academic positions at institutions like UIUC and IIT Kanpur. The group's work combines theoretical rigor with practical implementation, consistently producing open-source artifacts that enable reproducibility and further research in the systems and programming languages community.

Ruzica Piskacمشاهده پروفایل

استاد

• Software Verification
• Security and Applied Cryptography
• Automated Reasoning
• +۴ مورد دیگر

Ruzica Piskac is a Professor of Computer Science at Yale University, where she leads the Rigorous Software Engineering (ROSE) group. She has made significant contributions to the fields of software verification, security, automated reasoning, and code synthesis, focusing on improving software reliability and trustworthiness through formal techniques. Dr. Piskac received her PhD from the Swiss Federal Institute of Technology (EPFL) in 2011, where her dissertation won the Patrick Denantes Prize. Prior to joining Yale, she led an independent research group at the Max Planck Institute for Software Systems in Germany (2012-2013). Her research spans several key areas: symbolic execution for Haskell (G2), privacy-preserving formal methods (PPFM), functional reactive synthesis, verification of configuration files, and analysis of software updates. Her work consistently bridges theoretical formal methods with practical applications in real-world systems. Dr. Piskac's recent publications demonstrate a strong trend toward applying formal verification techniques to emerging challenges including large language models, quantum computing security, legal accountability of automated systems, and cyber-physical systems. Her research increasingly intersects with AI, cryptography, and legal domains while maintaining strong foundations in formal methods. Her scientific achievements have been recognized with numerous prestigious awards: Multiple Amazon Research Awards Yale University's Ackerman Award for Teaching and Mentoring Facebook Communications and Networking Award Microsoft Research Award for the Software Engineering Innovation Foundation (SEIF) Patrick Denantes Prize for her PhD dissertation Dr. Piskac has graduated five PhD students, four of whom have gone on to become assistant professors of computer science. She has served as Program Chair of the 37th International Conference on Computer Aided Verification and is on the Steering Committee of the Formal Methods in Computer-Aided Design conference. She leads the Rigorous Software Engineering (ROSE) group at Yale, which focuses on several key projects including: Symbolic Execution Engine for Haskell (G2) Privacy Preserving Formal Methods (PPFM) Functional Reactive Synthesis Verifications for Configuration Files Analysis of Software Updates and Configuration Files

• Distributed Systems
• IoT Protocols
• Big Data
• +۴ مورد دیگر

Dr. Sotirios Kontogiannis is a Researcher and Director of the Distributed MicroComputer Systems Laboratory (MCSL) at the Department of Mathematics, University of Ioannina. He holds a PhD in Software Engineering from Democritus University of Thrace (2012), with a focus on load balancing algorithms for distributed systems. His career spans academic and private sector roles, including software development, research in FP7 projects, and technical leadership at TEKMON Geomatics. He currently teaches courses on Database Systems, Parallel Algorithms, and Educational Technologies at the University of Ioannina. Education: 5-year Engineering Diploma (DUTH, 2003), MSc in Microelectronics and Information Systems (DUTH, 2006), PhD in Load Balancing Algorithms (DUTH, 2012). Research Focus: Distributed systems, IoT protocols, sensor networks, big data, and smart agriculture technologies (e.g., beekeeping monitoring systems, wine fermentation frameworks). His work integrates IoT, AI, and edge computing to address challenges in agriculture, accessibility, and environmental monitoring. Notable inventions include patented smart beehive systems and tactile navigation tools for visually impaired individuals.

Christos Tryfonopoulosمشاهده پروفایل

دانشیار

• Information Retrieval
• Information Filtering
• Personal Information Management
• +۲۰ مورد دیگر

Christos Tryfonopoulos is an Associate Professor and Head of the Department of Informatics & Telecommunications at the University of the Peloponnese, where he leads the Software and Database Systems (SoDa) Lab. His academic career spans prestigious institutions including the Max-Planck Institute for Informatics in Germany, where he led the P2P and Information Management research area from 2006-2009, and the Technical University of Crete, where he completed his PhD and MSc degrees. His research interests focus on information management, distributed systems, digital libraries, and data/user anonymity. His work bridges theoretical foundations with practical applications across diverse domains including environmental monitoring, cybersecurity, cultural heritage, and medical informatics. He has developed innovative frameworks for pollution prediction, cyber-threat intelligence, and academic expertise mapping that demonstrate the interdisciplinary nature of his research. Professor Tryfonopoulos has published over 80 papers in top-tier journals and conferences including TOIS, TKDE, SIGIR, and SIGMOD. His recent work shows a strong trend toward applying machine learning techniques to information management problems, with publications spanning environmental science, cybersecurity, and bibliometrics. His research group has developed several significant tools including VeTo+ for expert set expansion, inTIME for cyber-threat intelligence, and Hydria for cultural heritage analytics. Candidate for best research paper in ESWC 2016 conference Honorable mention for best poster (3rd place) in ESWC 2012 conference Award as Distinguished Scientist Excelling in Research Abroad (2008) Best student paper award in ECDL 2005 conference Heraclitus PhD fellowship from Greek Ministry of Education (2002-2005) National Scholarship Foundation of Greece (IKY) scholarship (1998) Professor Tryfonopoulos has supervised 5 PhD students (3 in progress), 19 MSc students, and 31 BSc students. He has led or participated in 13 competitive EU and national research projects including ENIRISST+ for shipping and transport infrastructure, WeCare for student support structures, and FORESIGHT for cybersecurity simulation. His current research focuses on intelligent infrastructure for transportation logistics, cyber-threat intelligence systems, and educational technologies for data science.

Chatziantoniou Damianosمشاهده پروفایل

استاد

• Big Data Systems
• Business Intelligence
• Large-Scale Analytics
• +۵ مورد دیگر

Professor Chatziantoniou Damianos holds a position at the Athens University of Economics and Business (AUEB) within the Department of Management Science and Technology (DMST), School of Business. He earned a B.Sc. in Applied Mathematics from the National & Kapodistrian University of Athens (1991), M.Sc. from New York University's Courant Institute of Mathematical Sciences, and a Ph.D. from Columbia University. His research focuses on big data systems, business intelligence, query processing, and real-time data analysis, with contributions influencing commercial database systems like Microsoft SQL Server and Oracle. As Director of AUEB's Master’s program in Business Analytics and Big Data, he previously served as an Assistant Professor at Stevens Institute of Technology (1997–1999). His industry collaborations include co-founding Panakea Software and VoiceWeb SA, and consulting roles at Aster Data Systems (now Teradata). He leads big data projects for companies like Cosmote, Piraeus Bank, and HEDNO. His research has been published in top venues including VLDB, ICDE, and SIGMOD, emphasizing practical applications in large-scale analytics and OLAP systems. He advises on strategic partnerships for the MSc program and maintains an active role in academic administration, including steering committees and quality assurance initiatives.

Garofalakis Minosمشاهده پروفایل

استاد

• Database Systems
• Data Streams
• Big Data Analytics
• +۷ مورد دیگر

Minos Garofalakis is a Professor of Computer Science at the School of Electrical and Computer Engineering (ECE) of the Technical University of Crete (TUC), where he directs the Software Technology and Network Applications Laboratory (SoftNet). He is also the Director of the Information Management Systems Institute (IMSI) at the Athena Research and Innovation Centre in Athens. Previously, he held roles at Yahoo! Research, Intel Research Berkeley, and Bell Laboratories, and was an Adjunct Associate Professor at UC Berkeley. Education: He earned a BSc in Computer Engineering from the University of Patras (1992), followed by MSc (1994) and PhD (1998) in Computer Science from the University of Wisconsin-Madison. Research Interests: His work focuses on Big Data analytics , including database systems, data streams, approximate query processing, probabilistic databases, and secure/private data analytics. Key areas include distributed stream processing, data synopses, and machine learning applications. He has authored over 150 papers and holds 29 patents, with an h-index of 63 and 13,500+ citations. Recent Work Trends: His recent articles emphasize scalable stream analytics (e.g., OmniSketch), privacy-preserving techniques, and distributed event processing. He explores challenges in handling high-velocity data streams, uncertainty in databases, and real-world applications like healthcare analytics. Scientific Awards: ACM Fellow (2018), IEEE Fellow (2017), TUC Excellence Award (2015), and multiple patents from Bell Labs/Yahoo/AT&T. Advising & Grants: He led EU projects such as FERARI, LEADS, and The Human Brain Project. His lab, SoftNet, develops tools for extreme-scale analytics and declarative networking. Current work includes interactive cross-platform analytics (Infore) and AI-driven medical data systems. Labs/Teams: Director of SoftNet Lab and IMSI. Collaborates with industry partners on distributed systems and privacy-preserving technologies.

Tsichlas Kostasمشاهده پروفایل

دانشیار

• Algorithms and Data Structures for Main and Secondary Memory
• Algorithms and Data Structures in Distributed Environments
• Computational Geometry
• +۵ مورد دیگر

Tsichlas Kostas serves as an Associate Professor in the Department of Computer Engineering and Informatics at the University of Patras, Greece, within the Division of Applications and Foundations of Computer Science. His research spans fundamental and applied computing domains with active involvement in the ML@Cloud laboratory. His expertise centers on algorithmic innovation across multiple dimensions: Memory-optimized algorithms for primary/secondary storage systems Distributed environment data structures and computational geometry Physics-informed computing and complex network analysis Specialized domains including alphanumeric and graph algorithms Recent publication trends (2022-2025) demonstrate concentrated research in historical graph management systems, temporal network analysis, and physics-computing intersections. Key contributions include vertex-centric partitioning strategies, temporal community detection frameworks, and machine learning applications for energy data motif discovery. He maintains active laboratory affiliations with the LARGE-SCALE CLOUD DATA MACHINE LEARNING WORKSHOP (ML@Cloud lab), Combinatorial Algorithms Laboratory, and Distributed Systems and Telematics Laboratory, contributing to Greece's computational research infrastructure.

• Data Science
• Data Mining
• Big Data Analytics
• +۸ مورد دیگر

Nikolaos Pelekis is a Professor at the Department of Statistics and Actuarial Science, School of Finance and Statistics, University of Piraeus, where he teaches courses in Data Science, Data Management, Information Systems, and Computer Programming. He has been actively involved in both undergraduate and postgraduate education, offering specialized courses such as "Statistical Data Mining Methods" in the Applied Statistics Master's program and "Big Data Management" in the Cybersecurity and Data Science postgraduate program. Born in 1975, Professor Pelekis earned his Bachelor's degree in Computer Science from the University of Crete (1998), followed by an MSc in Information Systems Engineering (1999) and a PhD in Moving Object Databases (2002) from UMIST University in the United Kingdom. His educational background laid the foundation for his distinguished career in data science and database management. Professor Pelekis' research spans multiple domains within data science and database management, with particular emphasis on mobility data analytics. His work focuses on data mining, big data management and analytics, with special attention to location and motion data including trajectories of moving objects. He has made significant contributions to spatial and spatiotemporal database management, moving object database systems, privacy-preserving data mining, and OLAP analysis. His research bridges theoretical foundations with practical applications, particularly in maritime and transportation domains. An analysis of Professor Pelekis' recent publications reveals a strong trend toward maritime data analytics and vessel traffic prediction. His work increasingly focuses on applying machine learning techniques to maritime trajectory data, developing systems for collision risk assessment, vessel location forecasting, and maritime route prediction. The research demonstrates a progression from foundational database management techniques to sophisticated analytics for time-critical mobility forecasting, with applications in aviation and maritime domains. Five best research paper awards 1st & 3rd place in the SemEval-2017 competition 3rd place in the ACM SIGSPATIAL Cup 2016 competition Best paper award at ACM SIGSPATIAL'14 (Path-based Queries on Trajectory Data) Best paper award at ER'13 (Baquara: A Holistic Ontological Framework for Movement Analysis with Linked Data) Best application paper award at ICDM'09 (Clustering Trajectories of Moving Objects in an Uncertain World) Ralf H. Güting best research paper award at SSTD'21 (A Novel Indexing Method for Spatial-Keyword Range Queries) Best Demo Paper award at SSTD'21 (MaSEC: Discovering Anchorages and Co-movement Patterns on Streaming Vessel Trajectories) Professor Pelekis has been actively involved in advising and research funding acquisition. He has participated in over 10 European and National Research and Development projects as principal investigator or key researcher. His leadership extends to directing research laboratories and coordinating large-scale collaborative projects. As co-founder of the Data Science Lab - DataStories at the University of Piraeus, he has mentored numerous researchers and students. His research has been supported by prestigious funding programs including Horizon Europe, Horizon 2020, and national research initiatives. Professor Pelekis co-founded and leads the Data Science Lab - DataStories at the University of Piraeus, which comprises 9 faculty members from 4 different Departments along with experienced and young researchers. He previously served as Head of Research for the Information Management Lab (InfoLab) at the Department of Informatics, University of Piraeus (2005-2014). His current research team is actively engaged in multiple European projects including "DAT.AI – Energy-efficient AI-ready Data Spaces" and "EMERALDS – Extreme-scale Urban Mobility Data Analytics as a Service," focusing on cutting-edge applications of data science in maritime and urban mobility contexts.