جست‌وجوی استاد و پژوهشگر

Amalia Fokaمشاهده پروفایل

استادیار

• Artificial Intelligence Applications in Arts
• Computer Science for Creative Practices
• Digital Interaction
• +۴ مورد دیگر

Amalia Foka is an Assistant Professor in Computer Science Applications for the Arts at the Department of Fine Arts & Art Sciences , School of Fine Arts , University of Ioannina , Greece. She has held academic positions at the University of Patras (2005-2013), University of Ioannina (2005-2008), and Computer Technology Institute & Press "Diophantus" (2014-2015). Her research bridges Artificial Intelligence with Digital Art , focusing on Generative AI , Social Media Mining , and Human-Computer Interaction within artistic contexts. Education: BEng in Computer Systems Engineering (1998) from the University of Manchester Institute of Science & Technology (UMIST) , UK MSc in Advanced Control (1999) from UMIST PhD in Robotics (2005) from the Department of Computer Science , University of Crete Her artistic research includes projects like Bushwalking (StyleGAN2 landscape generation), Breaking the Silence (NLP analysis of taboo topics), and The Invisible Structures of the Artworld (social media-driven network visualization). She leads the Multimedia Lab at the University of Ioannina, focusing on AI in Creative Processes and Digital Interaction methodologies.

Mohsen Lesaniمشاهده پروفایل

دانشیار

• Reliability of software systems
• Security of software systems
• Concurrent systems
• +۱۲ مورد دیگر

Mohsen Lesani is an Associate Professor in the Computer Science and Engineering Department at the University of California, Santa Cruz's Baskin School of Engineering. His research focuses on reliability and security of software systems, particularly concurrent and distributed systems, with recent emphasis on secure replicated systems and distributed machine learning. Dr. Lesani received his PhD from UCLA, MS in artificial intelligence from Sharif University of Technology, and BS in software engineering from University of Tehran. He was previously a postdoc at MIT. His educational background provides a strong foundation for his interdisciplinary research spanning programming languages, distributed systems, and security. His research interests center on creating reliable and secure distributed systems. Current projects include resilient and secure distributed systems, heterogeneous and reconfigurable secure distributed systems, automatic analysis and synthesis of replicated objects, verification of distributed systems, data analytics, secure exchange across blockchains, machine learning for performance models, domain-specific languages and type systems, and automatic fence insertion for concurrent systems. His work bridges theoretical foundations with practical implementations to address real-world challenges in distributed computing. Lesani's research has been recognized with several prestigious awards including the NSF CAREER award in 2020 and DARPA YFA award in 2022. His work has also received the SIGPLAN Research Highlight in 2019, a distinguished paper award at OOPSLA 2018, and a best paper award at ISSRE 2015. These accolades reflect the impact and quality of his contributions to the field. He actively mentors PhD students in the Safe and Secure Software (S3) lab, including Xiao Li, Eric Chan, Javad Saber-Latibari, and Tejas Mane. His research has been supported by multiple NSF grants, demonstrating sustained funding for his innovative work. Lesani serves on program committees for major conferences including POPL, PLDI, OOPSLA, and DISC, contributing to the academic community. Lesani leads the Safe and Secure Software (S3) lab at UC Santa Cruz, where his team works on cutting-edge research in distributed systems, programming languages, and security. The lab fosters a collaborative environment where theoretical insights are translated into practical systems that address real-world challenges in reliability and security of distributed applications.

Theodora Varvarigouمشاهده پروفایل

استاد

• Cloud Computing
• Multimedia Content Processing
• Social Networking Technologies
• +۳ مورد دیگر

Theodora Varvarigou is a Professor in the Department of Electrical and Computer Engineering at the National Technical University of Athens (NTUA). She holds a B.Eng. from NTUA and M.Eng. and Ph.D. degrees from Stanford University. Her career includes research at AT&T Bell Labs and roles at the Technical University of Crete. From 2008-2012, she served as director of NTUA's 'Technoeconomic Systems' postgraduate program. Her research focuses on Cloud Computing, Multimedia Content Processing, Social Networking Technologies, and emerging areas like blockchain, edge computing, and cybersecurity. She has published over 200 papers and led numerous European research projects, emphasizing scalable systems, data management, and smart infrastructure applications. Her work spans technical innovations such as intrusion detection systems, edge resource optimization, and blockchain-based solutions for IoT, healthcare, and smart cities. Recent publications highlight advancements in AI-driven resource allocation, privacy-preserving blockchain designs, and predictive analytics for edge computing environments. Professor Varvarigou has contributed to interdisciplinary initiatives, including cohort data harmonization in biomedical research and social media analytics for urban planning. Her teaching includes courses on digital systems, network programming, and fault-tolerant systems.

Ion Androutsopoulosمشاهده پروفایل

استاد

• Artificial Intelligence
• Natural Language Processing
• Machine Learning
• +۷ مورد دیگر

Ion Androutsopoulos is a Professor of Artificial Intelligence in the Department of Informatics at Athens University of Economics and Business (AUEB), where he also serves as Head of Department. He is founder and co-director of AUEB's Natural Language Processing Group and an Adjunct Researcher at the Digital Curation Unit and "Archimedes" Research Unit of the Research Centre "Athena". His research spans multiple dimensions of Artificial Intelligence with a focus on Natural Language Processing. Key interests include: Machine learning in NLP, particularly deep learning and large language models Question answering and retrieval augmented generation for document collections Dialog systems for new languages and knowledge domains Sentiment analysis and emotion recognition from text and speech Detecting toxic posts and disinformation online Image-to-text generation for medical diagnostics NLP applications in biomedical, legal, and financial domains His recent publications demonstrate strong activity across medical AI (particularly ImageCLEFmed Caption competitions where his group consistently ranks 1st-2nd), legal NLP (LexGLUE benchmark), financial NLP (EDGAR-CRAWLER), and multilingual challenges. His work shows increasing emphasis on large language models, explainability, and practical applications. Notable awards include: Top 2% scientist worldwide (Stanford University database, 2023) Multiple AUEB Excellent Teaching Awards (2017-18, 2021-22, 2023-24) Three consecutive BioASQ awards (2018-2020) Multiple 1st/2nd place rankings in ImageCLEFmed Caption competitions (2021-2025) He actively organizes major events including the Athens Natural Language Processing Summer School (AthNLP) and SemEval tasks. His group maintains strong industry and research collaborations, particularly in medical AI applications where they've developed systems that generate diagnostic captions from medical images with state-of-the-art performance.

Christos Makrisمشاهده پروفایل

دانشیار

• Data Structures
• Information Retrieval
• Data Mining
• +۵ مورد دیگر

Christos Makris is an Associate Professor in the Department of Computer Engineering and Informatics at the University of Patras, Greece. His academic career spans over two decades with significant contributions to computer science, particularly in data structures, algorithms, and information systems. He maintains active research collaborations and supervises graduate students in his areas of expertise. Dr. Makris's research spans several key areas in computer science with a strong focus on efficient data organization and processing. His work encompasses Data Structures , Information Retrieval , Data Mining , String Management and Processing Algorithms , Computational Geometry , Internet Technologies , Bioinformatics , and Multimedia Databases . His interdisciplinary approach bridges theoretical computer science with practical applications across various domains including web technologies, bioinformatics, and emergency response systems. Analysis of Dr. Makris's publication record reveals a consistent research trajectory focused on efficient algorithms for information management. His work demonstrates evolution from foundational data structure research in the 1990s to more applied work in web technologies, social media analysis, and machine learning applications in recent years. A notable pattern is his ability to adapt core algorithmic techniques to emerging application domains while maintaining theoretical rigor. Dr. Makris maintains an impressive scholarly record with over 3,000 citations, an h-index of 29, and an i10-index of 71 according to Google Scholar metrics. These indicators reflect the significant impact of his research within the computer science community. As an active faculty member, Dr. Makris maintains regular office hours on Tuesdays from 18:00-20:00 and Thursdays from 12:00-14:00. He is accessible via email at makri@ceid.upatras.gr or makri@upatras.gr for academic inquiries and student supervision.

• Database Information Management
• Big Data Management Systems
• Data Structures
• +۲ مورد دیگر

Ioannis Tsaknakis is an Associate Professor at the Department of Electrical & Computer Engineering, School of Engineering, University of Peloponnese. He holds a PhD in computational geometry and multidimensional data structures from the University of Patras (2004) and has been actively involved in software systems research since 2004. His work spans Database Information Management , Big Data Systems , and Knowledge Mining , with a focus on data structures and computational geometry. Research Interests : Information Management in Databases Big Data Management Systems Computational Geometry Knowledge Mining in Databases/Web Publications highlight his contributions to IoT-driven educational frameworks, machine learning applications, and cryptographic systems for data security. He has taught courses on software design and data management since joining the University of Peloponnese in 2019. Contact : jtsaknakis@uop.gr . Office hours are in Building K (Monday & Tuesday, 8:00-9:00).

Laxman Dhulipalaمشاهده پروفایل

استادیار

• Parallel Algorithms
• Graph Processing
• Parallel Graph Algorithms
• +۷ مورد دیگر

Laxman Dhulipala serves as an Assistant Professor in the Department of Computer Science at the University of Maryland, College Park, while also working as a research scientist at Google Research with the Graph Mining team. Dr. Dhulipala earned his Ph.D. from Carnegie Mellon University under Guy Blelloch's supervision and completed a postdoctoral fellowship at MIT with Julian Shun. His research centers on efficient parallel algorithms, particularly for parallel clustering and graph processing, along with developing computational models for emerging hardware technologies. His scholarly output demonstrates significant expertise across parallel computing domains, with particular emphasis on scalable graph algorithms, dynamic data structures, and computational geometry. Dr. Dhulipala's work bridges theoretical computer science with practical systems implementation, producing algorithms that achieve both theoretical optimality and real-world performance. His research group has made substantial contributions to benchmarking frameworks including the Graph Based Benchmark Suite (GBBS) and ParClusterers Benchmark Suite, establishing standardized evaluation methods for graph processing systems. The collective work shows progression from theoretical foundations to practical implementations that handle massive-scale datasets. Best Paper Award at SPAA 2022 Best Paper Runner Up at VLDB 2022 Distinguished Paper Award at PLDI 2019 Memorable Paper Award Finalist at NVMW'20 CMU's SCS Dissertation Award Honorable Mention As an educator, Dr. Dhulipala mentors numerous graduate students while teaching advanced courses in algorithm design and parallel computing. His research collaborations span multiple institutions including Carnegie Mellon University, MIT, and Google Research, reflecting his position at the intersection of academia and industry research.

Yannis Theodoridisمشاهده پروفایل

استاد

• Moving Objects Databases
• Location-Based Services
• Data Mining for Spatial Objects
• +۳ مورد دیگر

Yannis Theodoridis is a Professor at the Department of Informatics, University of Piraeus, leading the Information Systems Laboratory (InfoLab). He specializes in spatiotemporal databases, mobility analytics, and maritime data science. His research focuses on trajectory analysis, location-based services, and big data frameworks for transportation and maritime surveillance. Key projects include the MOD (Moving Objects Databases) initiative, the ARGOS framework for real-time trajectory prediction, and contributions to the HERMES trajectory database engine. He has advised 7 PhD students and co-authored numerous papers in IEEE and ACM venues. His work addresses challenges like vessel collision risk assessment, urban mobility optimization, and maritime event detection. He serves on the editorial board of the International Journal of Data Warehousing and Mining and contributes to conferences like PCI and ECML PKDD. His labs emphasize interdisciplinary approaches to mobility data science, integrating machine learning with domain-specific analytics.

Nikitas Karanikolasمشاهده پروفایل

استاد

• Natural Language Processing and Understanding
• Computational Linguistics
• Computational Phonology
• +۷ مورد دیگر

Nikitas Karanikolas serves as Professor in the Department of Informatics and Computer Engineering at the University of West Attica since March 2018, following a distinguished career progression from Assistant Professor (2004) to Associate Professor (2010) and Professor (2014) at the Technological Educational Institute of Athens. His professional trajectory includes significant roles as Systems Head of TEI Athens Library (1996-1997) and Chief of Informatics at Aretaieio University Hospital (1997-2004), alongside leadership positions in the Greek Computer Society as Board Member (2004-2006) and Secretary General (2006-2008). His academic foundation includes: Bachelor's in Statistics and Informatics from Athens University of Economics and Business (1988) PhD in Applied Informatics from Athens University of Economics and Business (1994) with thesis "Technological and Linguistic approaches in Natural Language Understanding" Dr. Karanikolas maintains an exceptionally broad research portfolio spanning Natural Language Processing , Computational Linguistics , Medical Informatics , and Green Energy systems. His work consistently bridges theoretical computational frameworks with practical healthcare applications, particularly evident in recent dementia care technologies and Greek language processing systems. The interdisciplinary nature of his research connects computational phonology with medical diagnostics and e-government applications. Analysis of his 15 most recent publications reveals a pronounced shift toward AI-driven healthcare solutions (particularly dementia patient monitoring), multilingual NLP systems (Greek and Polish), and urban safety applications . His work demonstrates consistent methodology development in ontological representations and multimodal fusion techniques, with increasing emphasis on real-world clinical and governmental implementations since 2023. No scientific awards were documented in the source materials. With 16 journal papers, 68 conference publications, and six authoritative Greek university textbooks, Dr. Karanikolas maintains an active research trajectory. His advising capacity is evidenced through extensive publication mentorship, particularly in medical informatics and NLP projects. While specific grant details are unavailable, his hospital information system implementations and textbook authorship suggest successful research funding acquisition. Current research activities focus on multimodal aggression prediction systems for dementia care, Greek language ontological frameworks, and urban navigation safety applications, primarily conducted through the University of West Attica's informatics infrastructure.

Gerhard Weikumمشاهده پروفایل

پژوهشگر

• Computer Science
• Database Systems
• Information Retrieval
• +۳ مورد دیگر

Gerhard Weikum is a renowned computer scientist and Director at the Max Planck Institute for Informatics in Saarbrücken, Germany. He holds the title of Scientific Member of the Max Planck Society. Previously, he served as a Professor at ETH Zurich (1990–1994) and Saarland University (1994–2003). His career includes roles as a Research Associate and Postdoc at TU Darmstadt, MCC in Austin, and ETH Zurich. Born in 1957, he earned his doctoral degree in computer science from TU Darmstadt in 1986. Education: Bachelor/Master studies in Computer Science at TU Darmstadt Doctoral Dissertation: TU Darmstadt (1986) His research interests span foundational areas of computer science, including database systems, information retrieval, and distributed computing. While specific publications are not listed here, his work aligns with the institute’s focus on cutting-edge informatics research. Grants and Advising: Details on grants, advising, or lab affiliations are not explicitly mentioned in the provided text. Labs/Teams: As a Director at the Max Planck Institute for Informatics, he likely contributes to interdisciplinary teams and research groups within the institute’s computational science initiatives.

• Database Systems
• Distributed Systems
• Machine Learning Systems
• +۳ مورد دیگر

Tim Kraska is an Associate Professor in the Department of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology (MIT), affiliated with the Computer Science and Artificial Intelligence Laboratory (CSAIL) within the School of Engineering. His research spans foundational areas in modern data systems: Database Systems Distributed Systems Machine Learning Systems Learned Indexes Cloud Databases Dr. Kraska pioneers the integration of machine learning into core database components, developing "learned systems" that replace traditional algorithms with ML models for significant performance gains. His work on learned indexes redefined indexing paradigms, while recent research extends this approach to garbage collection, query optimization, and concurrency control. His publication trends reveal a strategic shift toward applying ML to low-level systems problems, particularly in memory management and runtime optimization as demonstrated by his PLDI 2020 paper on Learned Garbage Collection. Award highlights include: ACM SIGMOD Jim Gray Doctoral Dissertation Award VLDB Early Career Research Contribution Award Marie Curie Fellowship At MIT, he leads a research group focused on next-generation data systems, securing grants from NSF and industry partners to explore the theoretical and practical boundaries of learned components in database engines. His team collaborates extensively with industry research labs on real-world deployment challenges. As a core member of CSAIL's distributed systems group, he contributes to MIT's leadership in reimagining data infrastructure for the AI era through cross-lab initiatives on scalable machine learning systems.

Heather Millerمشاهده پروفایل

استادیار

• Distributed Systems
• Concurrent Programming
• Programming Languages
• +۴ مورد دیگر

Heather Miller is a tenure-track Assistant Professor in the Software and Societal Systems Department within Carnegie Mellon University's School of Computer Science. Her academic journey includes prior roles as an Assistant Clinical Professor at Northeastern University's College of Computer and Information Science and as Executive Director of the Scala Center at EPFL. Miller's research centers on distributed and concurrent computation through the lens of programming languages, with particular emphasis on data-centric systems, big data processing, and edge computing. A defining theme throughout her work is composability - enabling construction of complex distributed systems through composition of components that are correct by construction. Her projects span distributable closures, flexible serialization techniques, futures and promises for asynchronous programming, and deterministic concurrent dataflow models. Her recent publications demonstrate strong trends in applying programming language theory to practical distributed systems challenges, with increasing focus on WebAssembly instrumentation, microservice resilience, and language model pipelines. This evolution reflects her commitment to bridging theoretical foundations with real-world system requirements. Dahl-Nygaard Junior Prize (2023) Mentorship forms a significant component of Miller's academic work. She actively supervises multiple PhD, MS, and undergraduate researchers at CMU, including Christopher Meiklejohn, Matthew Weidner, Huairui Qui, Ria Pradeep, and Luke Dramko. Her service contributions span numerous top-tier conferences including PLDI, SPLASH, ECOOP, and ICSE where she has served as committee member, chair, and keynote speaker. Miller co-founded the Curry On conference to foster industry-academia dialogue, hosting successful editions in Prague, Rome, Barcelona, Amsterdam, and London. She leads research groups focused on distributed programming models and maintains strong industry connections through Two Sigma, where she holds an affiliation. Her work consistently emphasizes practical open-source implementations, primarily within the Scala ecosystem where she's been a core contributor since 2011.

Manolis Koubarakisمشاهده پروفایل

استاد

• Artificial Intelligence
• Data Science
• Linked Data
• +۳ مورد دیگر

Manolis Koubarakis is a Professor and Director of Graduate Studies at the Department of Informatics and Telecommunications, National and Kapodistrian University of Athens. He is affiliated with the Archimedes Unit at Athena Research Center and is a member of ELLIS. His research focuses on Artificial Intelligence and Data Science, particularly in Linked Geospatial Data, Earth Observation, and Knowledge Graphs. Education: PhD in Computer Science (National Technical University of Athens), M.Sc. in Computer Science (University of Toronto), and B.Sc. in Mathematics (University of Crete). Research Interests: His work spans AI applications in geospatial data, entity resolution, ontology-based data access (OBDA), and semantic web technologies. He leads projects like ExtremeEarth (AI for Copernicus data) and LEO (linked Earth Observation data). Awards: 2015: Fellow of the European Association of Artificial Intelligence (EurAI) 2022: Best Demo Award at CIKM for Copernicus App Lab Advising & Grants: Supervises students in AI and data science. Collaborates on EU-funded projects like BigDataEurope and participates in initiatives like the Standing Scientific Committee for AI in Greece's justice system. Labs & Teams: Heads the AI Lab (ai.di.uoa.gr) and contributes to the MaDgIK group, focusing on data and knowledge management systems.

Antonios Deligiannakisمشاهده پروفایل

استاد

• Databases
• Sensor Networks
• Analytical Data Processing
• +۴ مورد دیگر

Antonios Deligiannakis is a Professor at the School of Electronic and Computer Engineering of the Technical University of Crete, specializing in database systems and distributed data processing. His academic career includes a postdoctoral position at the National and Kapodistrian University of Athens (2006-2007) and a visiting researcher role at AT&T Labs-Research (2003). His educational background includes: PhD in Computer Science, University of Maryland, USA (2005) Master's Degree in Computer Science, University of Maryland, USA (2001) Diploma in Electrical and Computer Engineering, National Technical University of Athens (1999) Professor Deligiannakis's research spans Databases , Stream Processing , and Sensor Networks , with pioneering work in Approximate Query Evaluation for massive datasets and Complex Event Processing in distributed environments. His contributions enable efficient analytics in resource-constrained settings through techniques like synopses-based engines and windowed outlier detection. His 15 most recent publications (2020-2025) reveal a dominant focus on distributed streaming analytics, with recurring themes of cross-platform integration, federated learning, and extreme-scale interactive systems. Key innovations include the INFORE framework for interactive analytics, DAG* for IoT workflow optimization, and communication-efficient federated learning techniques—demonstrating consistent translation of theoretical advances into production-ready platforms. Scientific Awards: No specific awards were listed in the provided material. Information about advisees and research grants was not provided in available documentation, though his leadership in the Distributed Information Systems and Applications laboratory suggests active mentorship and project direction. He directs research in the Distributed Information Systems and Applications laboratory, developing systems for real-time analytics across domains including maritime surveillance, financial technology, and IoT platforms, with emphasis on scalability and fault tolerance in geo-distributed environments.

• Spatial Databases
• Geoinformatics
• Internet of Things (IoT)
• +۵ مورد دیگر

Anastasios Zafeiropoulos serves as Assistant Professor at Harokopio University of Athens, specializing in Spatial Data Management and Analysis within the Postgraduate Studies Program for “Applied Geography and Spatial Management” (Direction C: Geoinformatics). His academic role encompasses teaching “Spatial Databases” and advancing research at the intersection of geospatial technologies and distributed computing systems. His research program focuses on Spatial Databases, Internet of Things (IoT), Cloud/Edge Computing, and 6G Network Orchestration, with significant extensions into Knowledge Graph applications for Sustainable Development Goals (SDGs) and socio-emotional learning in education. Key innovations include the EduCardia methodology for student competency assessment and frameworks for climate vulnerability analysis using knowledge graphs. Analysis of his 2024-2025 publications reveals three dominant thrusts: (1) AI-driven orchestration of 6G services across the computing continuum using reinforcement learning; (2) Knowledge Graph applications for SDG interlinkage analysis and materials science; (3) EU-funded IoT/Edge Computing project ecosystems. His work consistently bridges theoretical networking concepts with practical sustainability and educational applications. Dr. Zafeiropoulos actively contributes to EU-funded initiatives in IoT and Edge Computing standardization, particularly through AIOTI WG Standardisation. His project portfolio includes NEPHELE multi-cloud ecosystem development and O-RAN slice admission control research, demonstrating strong industry-academia collaboration in next-generation networking. He leads the development of innovative tools including Palindrome.js for distributed system visualization and the EmoSocio open-access emotional intelligence model, reflecting his commitment to translating research into practical educational and environmental solutions.