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Nikos MamoulisView profile

Professor

• Spatial Data Management
• Big Data Analytics
• Data Privacy
• +5 more

Prof. Nikos Mamoulis is a Professor at the Department of Computer Science & Engineering, University of Ioannina, and a Lead Researcher at Archimedes Research Unit, ATHENA RC. He holds a PhD from Hong Kong University of Science and Technology (HKUST) and a Diploma from the University of Patras. His research focuses on spatial data management, big data analytics, data privacy, and uncertain data systems. Education : Ph.D., Computer Science, Hong Kong University of Science and Technology (2000) 5-year Diploma, Computer Engineering and Informatics, University of Patras (1995) Research Interests : Complex data management (spatial, spatio-temporal, time-series, text, graphs), big data analysis, privacy preservation, and uncertain data systems. He develops scalable algorithms and systems for modern data management challenges, with applications in transportation, social networks, and geospatial analytics. Projects & Grants : MESA: In-memory Spatial Analytics Made Scalable (HFRI-funded, PI) MORE: Real-time Energy Data Management (H2020, Senior Researcher) Smart City Bus Platform (ERDF-funded, PI/Coordinator) Awards : Outstanding Young Researcher Award (2008-2009, HKU) Best Paper Award at SSTD 2015 Test of Time Award at MDM 2022 Labs & Collaborations : Leads the Archimedes Research Unit at ATHENA RC, collaborating with institutions like HKUST and Uppsala University on spatial and big data systems. Active in organizing top-tier conferences like SIGMOD, EDBT, and ICDE.

Ioannis EmirisView profile

Professor

• Computational Geometry
• Algebraic Algorithms
• Robotics
• +4 more

Ioannis Z. Emiris is a Professor in the Department of Informatics & Telecoms at the National & Kapodistrian University of Athens and concurrently serves as President and General Director of the ATHENA Research Center in Greece. He holds a BSc in Computer Science from Princeton University (1989) and a PhD in Computer Science from UC Berkeley (1994). His research spans computational geometry, algebraic algorithms, robotics, structural bioinformatics, and optimization. He is a leading expert in sparse elimination theory, geometric modeling, and algorithmic algebra. Affiliations: ATHENA Research Center, National & Kapodistrian University of Athens, INRIA Sophia Antipolis (France via joint AROMATH team). Education: BSc (Princeton), PhD (UC Berkeley). Research Interests Emiris's work focuses on geometric algorithms, algebraic systems, and their applications. His contributions include advancements in sparse elimination theory, computational geometry for high-dimensional data, and robotics. He has developed algorithms for polynomial system solving, Voronoi diagrams, and geometric predicates for ellipses. Articles Overview His recent work bridges theoretical advances with practical applications, such as deep learning for protein structure prediction (HydraProt) and geometric algorithms for high-dimensional data analysis. He explores intersections between algebraic geometry and computational methods, with applications ranging from robotics to bioinformatics. Scientific Awards Best Paper Award at ISSAC 2003 and 2010 MSCA Network GRAPES (2019-2023) Advising & Grants Emiris has supervised numerous students and researchers, contributing to interdisciplinary projects. He has secured grants for initiatives like the GRAPES network and has led teams in algorithm design and geometric software development. His work on MARS (Maple/Matlab/C Resultant-Based Solver) exemplifies his focus on practical algorithm implementation. Labs & Teams He directs the Lab of Geometric & Algebraic Algorithms and collaborates with the AROMATH team at INRIA. His research group develops open-source tools for computational geometry and algebraic computations.

Pavel PanchekhaView profile

Assistant Professor

• Programming Languages
• Program Synthesis
• Verification
• +4 more

Pavel Panchekha is an Assistant Professor in the School of Computing at the University of Utah, where he holds the Warnock Chair for Junior Faculty. His research spans programming languages, web browsers, and numerical analysis, with a focus on developing programming language techniques to address challenges across computer science. Dr. Panchekha received his educational training at prestigious institutions: PhD in Computer Science from the Paul G. Allen School for Computer Science and Engineering at the University of Washington, advised by Michael D. Ernst and Zachary Tatlock BS in Mathematics from MIT Panchekha's research program has two major thrusts. First, he works on web browser internals , with projects including fuzzing layout invalidation, multi-tenant garbage collection, and optimizing 2D graphics. He is also authoring a textbook on web browsers that informs much of this research. Second, he focuses on automatic numerical analysis , with projects such as automatic accuracy improvement, synthesis via term rewriting, scalable static accuracy analysis, and math library implementation. He leads the FPBench and Herbie projects, which are major deployments of his research. His scholarly output demonstrates consistent contributions across programming languages, verification, and numerical methods. Recent work shows a growing emphasis on bidirectional typing systems, layout invalidation in browsers, and robust floating-point error analysis. His publications reveal a trajectory from foundational work on floating-point accuracy (notably the Herbie tool that won a Distinguished Paper Award at PLDI 2015) toward more comprehensive systems for program synthesis, verification, and browser optimization. Panchekha has received significant recognition for his research contributions: NSF Fellowship ARCS Foundation Fellowship Adobe Research Fellowship Wissner-Slivka Foundation Fellowship 2015 PLDI Distinguished Paper Award for work on the Herbie numerical analysis and repair tool As an advisor, Panchekha mentors a substantial group of students across multiple levels. He currently advises six students: Marisa Kirisame (PhD), Bhargav Kulkarni (PhD), Yumeng He (PhD), Artem Yadrov (MS), Jesus Ponce (BS), and Jonas Regehr (BS). Previously, he has advised over twenty students including PhD candidates like Ian Briggs and numerous MS and BS students. His advising spans theoretical topics in programming languages and practical applications in web browsers and numerical computing. Panchekha leads research groups focused on programming languages applications to web browsers and numerical analysis. His work on the Herbie tool for floating-point accuracy improvement has become influential in the programming languages community, and his more recent work on browser internals is shaping how researchers understand and optimize modern web rendering engines. He is currently developing a textbook on web browsers that aims to synthesize knowledge about browser architecture and implementation.

Christos MakrisView profile

Associate Professor

• Data Structures
• Information Retrieval
• Data Mining
• +5 more

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.

• Computational Complexity
• Graph Algorithms
• Distributed Algorithms
• +6 more

Aris T. Pagourtzis is a Professor of Computer Science at the School of Electrical and Computer Engineering of the National Technical University of Athens (NTUA), where he also serves as the Head of the Computer Science Division. He is additionally a Lead Researcher at the Archimedes Research Center, Athena RC. His academic career includes positions at the University of Ioannina, the University of Liverpool, the ETH Zuerich, the University of Athens, and the Athens University of Economics and Business. Education: Diploma in Electrical Engineering (1989) and Ph.D. in Electrical and Computer Engineering (1999), both from the National Technical University of Athens Professor Pagourtzis's research spans multiple areas of theoretical computer science, with particular emphasis on computational complexity, graph algorithms, distributed algorithms, approximation algorithms, network algorithms, cryptography, and counting complexity. His work often bridges theoretical foundations with practical applications in network design, security protocols, and optimization problems. He has developed novel algorithms for problems ranging from community detection in networks to Byzantine fault-tolerant protocols and privacy-preserving voting systems. His recent publications show a continued focus on fundamental algorithmic problems while expanding into newer areas like temporal graph analysis, blockchain applications, and privacy-preserving technologies. There's a clear trend toward addressing real-world challenges through rigorous theoretical frameworks, particularly in distributed systems, secure computation, and optimization under constraints. Professor Pagourtzis has served on program and organizing committees for numerous theoretical computer science and cryptography conferences, co-chairing CIAC 2017 and FCT 2021. His research has received funding from diverse sources including US, UK, French, EU, and Greek national resources. He is actively involved in teaching both undergraduate and graduate courses at NTUA, including Algorithms and Complexity, Foundations of Computer Science, Computational Cryptography, and Network Algorithms and Complexity. He leads the Computation and Reasoning Laboratory (corelab) at NTUA, which focuses on theoretical computer science research.

Laxman DhulipalaView profile

Assistant Professor

• Parallel Algorithms
• Graph Processing
• Parallel Graph Algorithms
• +7 more

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.

• Multibody dynamics
• Control of nonlinear systems
• Model predictive control

Michael Mühlebach is a Lecturer at the Department of Information Technology and Electrical Engineering at ETH Zurich, affiliated with the Max Planck Institute for Intelligent Systems in Tübingen, Germany. He received Bachelor (2010) and Master (2013) degrees from ETH Zurich, awarded the Outstanding D-MAVT Bachelor Award and Willi-Studer Prize for top performance. His research specializes in multibody dynamics , control of nonlinear systems , and model predictive control , with applications in robotics and aerospace systems. Publications demonstrate consistent focus on theoretical control frameworks validated through experimental platforms like ducted fans and reaction-wheel systems. Awards: Outstanding D-MAVT Bachelor Award Willi-Studer Prize (Best Master in Robotics, Systems, and Control)

Efthymios N. KaratzasView profile

Assistant Professor

• Numerical Analysis
• Computational Mathematics
• Optimal Control
• +5 more

Efthymios N. Karatzas serves as an Assistant Professor in the Department of Mathematics at Aristotle University of Thessaloniki, Faculty of Sciences, within the Computer Science and Numerical Analysis Section. He maintains an active research profile in computational mathematics with strong institutional affiliations including collaborations with SISSA mathLab and FORTH Institute of Applied and Computational Mathematics. His academic credentials include: PhD in Mathematics, National Technical University of Athens (2015) Master's in Applied Mathematical Sciences – Computational Mathematics, NTUA (2009) Master's in Applied Mathematics, University of Patras (2001) Bachelor's in Mathematics (Computational Mathematics), University of Patras (1999) Dr. Karatzas' research program centers on advanced numerical techniques for partial differential equations , with pioneering work in reduced order modeling , embedded boundary methods , and optimal control systems . His expertise spans computational fluid dynamics, uncertainty quantification, and biomechanical applications, characterized by methodological innovation in handling geometrically complex domains through cut finite element approaches and shifted boundary formulations. Analysis of his 15 most recent publications reveals a cohesive research trajectory focused on developing efficient numerical frameworks for parametrized PDE systems. His work consistently bridges theoretical rigor with practical implementation, particularly in advancing reduced basis methods for fluid-structure interaction and biological modeling, demonstrating significant contributions to computational mathematics through high-impact journal publications. No major scientific awards are documented in the available sources. Dr. Karatzas demonstrates research leadership through project management roles including Scientific Manager for the ELIDEK project at NTUA (2019-2021) and Project Manager for the European Social Fund HEaD initiative at SISSA (2017-2019). His grant administration experience encompasses coordinating interdisciplinary teams and securing external funding for computational mathematics research. He maintains active collaborations with the SISSA mathLab in Trieste (particularly with Prof. Gianluigi Rozza's group) and the FORTH Institute in Crete, participating in international workshops including the Reduced Order Methods in CFD Summer School (2019) and SIAM UQ conferences. His research network spans computational mathematics groups across Europe with emphasis on advancing numerical methodologies for real-world engineering and biological applications.

Bletsas AggelosView profile

Professor

• Wireless Transmission
• Wireless Relay Networks
• Software-Defined Radio
• +3 more

Aggelos Bletsas is a Professor at the School of Electrical and Computer Engineering, Technical University of Crete. He holds a PhD from MIT (2005) and has expertise in wireless communication, backscatter networks, and RFID systems. His research focuses on scalable wireless networks, ultra-low-cost sensor technologies, and signal processing. Education: PhD, MIT Media Lab (2005) MSc, MIT Media Lab (2001) Diploma in Electrical & Computer Engineering, Aristotle University of Thessaloniki (1998) Research Interests: His work spans wireless transmission techniques, backscatter sensor networks, and RFID systems. Key areas include: Ultra-low-cost sensor deployment RFID localization and multi-static systems Energy-efficient hardware implementations Probabilistic inference in distributed networks Awards: IEEE Marconi Prize Paper Award (2008) Technical University of Crete Research Excellence Award (2012-2013) Multiple best paper awards at RFID-TA, ISWCS, and SENSORS Academic Contributions: He advises students who have won IEEE best thesis awards and leads projects funded by ERC grants. His laboratory focuses on practical implementations of wireless sensor networks and backscatter systems. Labs & Affiliations: Director of the Telecommunications Laboratory and affiliated with the Telecommunication Systems Institute (TSI).

Foto N. AfratiView profile

Professor

• Parallel and distributed computation
• Processing of very large data
• MapReduce
• +6 more

Professor Foto N. Afrati is a Distinguished Faculty Member at the National Technical University of Athens, specifically within the School of Electrical and Computing Engineering and the Division of Communication, Electronic and Information Engineering. She has held this position since 1993, following previous academic ranks at the same university as Associate Professor (1989-1993), Assistant Professor (1985-1989), Lecturer (1982-1985), and Research Fellow (1980-1982). She completed her PhD in Electrical Engineering at Imperial College of the University of London in March 1980, with a dissertation focused on Error Correcting Codes by Algorithms. Her academic journey also included a Diploma from Imperial College (March 1980) and an earlier Diploma in Electrical and Mechanical Engineering from the National Technical University of Athens (June 1976). Professor Afrati's research interests span several critical areas in computer science: Parallel and distributed computation Processing of very large data (including MapReduce) Data and web mining Database Systems Information integration Query optimization Computation and complexity of algorithms Approximation algorithms Her most recent publications demonstrate expertise in MapReduce environments, query optimization with views, and data exchange frameworks. These works are published in prestigious venues like EDBT, VLDB, PODS, and ICDT, with specific focus areas including adaptive sampling techniques, data source integrity, and algorithm complexity in database environments. Professor Afrati has received significant recognition in her field, including Fellow of the Association for Computing Machinery (ACM) Best Paper Award at the International Conference on Database Theory (ICDT) 2009 She has advised numerous PhD students throughout her career, including Theodoros Mitakos, Ezz Hattab, Nikos Kiourtis, and Angelos Vasilakopoulos. Her current PhD students include Victor Kyritsis and Nikos Stassinopoulos. Professor Afrati maintains strong professional networks through her various visiting positions at institutions such as Google, Stanford University, IBM Research Center, University of Helsinki, University of Paris, DIMACS, and others. She has served as associate editor and reviewer for major academic journals and conferences including IEEE TKDE, ACM Transactions of Database Systems (TODS), Journal of ACM (JACM), and Theoretical Computer Science (TCS). Her extensive work in research projects spans both national and international initiatives, with funding from sources including the European Union's Thalis project, ESPRIT working groups, HCM networks, and Greek General Secretariat of Research and Technology grants.

Antonios DeligiannakisView profile

Professor

• Databases
• Sensor Networks
• Analytical Data Processing
• +4 more

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.

• Wireless transmission
• Wireless relay networks
• Software-defined radio
• +7 more

Aggelos Bletsas Aggelos Bletsas is a Professor at the School of Electrical and Computer Engineering (ECE) at the Technical University of Crete (TUC). He holds a PhD from MIT and has expertise in wireless communication, backscatter radio, and IoT. His research focuses on ultra-low-cost sensor networks and ambiently-powered systems. Education PhD in Media Arts and Sciences, MIT (2005) MSc in Media Arts and Sciences, MIT (2001) 5-year Diploma in Electrical & Computer Engineering, Aristotle University of Thessaloniki (1998) Research Interests Bletsas' work spans scalable wireless networks, backscatter radio, RFID systems, and energy harvesting. He pioneers batteryless IoT devices and environmental sensing technologies. His lab develops hardware and algorithms for low-cost, long-range communication. Awards & Recognition IEEE Fellow (2023) 2012-2013 TUC Research Excellence Award Multiple Best Paper Awards (ISWCS, RFID-TA, SENSORS) IEEE ComSoc and RFID Council Distinguished Lecturer (2022-2025) Labs & Projects Bletsas leads the Telecommunications Laboratory at TUC, focusing on batteryless sensors, scatter radio, and robotic inventory systems. Key projects include 'Internet of Plants' and ambiently-powered inference networks.

Archontia C. GiannopoulouView profile

Associate Professor

• Graph Algorithms
• Structural Graph Theory
• Parameterized Algorithms and Complexity
• +3 more

Archontia C. Giannopoulou is an Associate Professor at the Department of Informatics and Telecommunications, National and Kapodistrian University of Athens, Greece. Her research focuses on Graph Algorithms, Structural Graph Theory, and Parameterized Algorithms and Complexity. She explores advanced topics such as matching minors, tree-cut width, immersion minors, and kernelization. Her work emphasizes algorithmic design and structural graph theory with applications in combinatorial optimization. Giannopoulou’s academic contributions include seminal papers on edge deletion problems, cutwidth obstructions, and polynomial kernelization. Notable publications include studies on bipartite graphs and their structural properties, as well as algorithmic advancements in parameterized complexity. Her research bridges theoretical foundations with practical algorithmic solutions. Her contact information includes an email at archontia.giannopoulou@gmail.com and a postal address at the University of Athens. Her work spans international collaborations, reflected in co-authored articles with leading researchers in the field.

Nikos GiatrakosView profile

Assistant Professor

• Big Data Management
• Internet of Things (IoT)
• Distributed Systems
• +3 more

Nikos Giatrakos is an Assistant Professor at the School of Electronic & Computer Engineering, Technical University of Crete, and a core member of the Software Technology and Network Applications Lab (SoftNet) . His work bridges Big Data systems, IoT, and advanced analytics, with a focus on real-time processing and scalable architectures. Previously, he served as a postdoctoral researcher at the same laboratory. Education PhD in Computer Science, University of Piraeus (2012) Postgraduate Diploma in Information Systems, Athens University of Economics and Business (2008) BSc in Computer Science, University of Piraeus (2006) Research Focus : Nikos specializes in software architectures for Big Data streaming, including Distributed Big Data Processing , Federated Machine Learning , Cloud-to-Edge Data Management , and Approximate Query Processing . His work has also advanced Complex Event Processing and Outlier Detection in decentralized environments. Scientific Contributions : His research has led to the DAG* workflow optimizer for IoT, the SuBiTO framework for real-time neural learning, and the INFORE approach for cross-platform analytics. He received the Best System Demonstration Award at ACM CIKM 2020 for INforE. Academic Leadership : Nikos teaches Object-Oriented Programming, Data Science, and Distributed Systems. He has supervised numerous European and national grants as Principal Investigator and served on program committees for top-tier conferences like SIGMOD, VLDB, and DEBS.

• Machine Learning
• Reinforcement Learning
• Decision Making Under Uncertainty
• +6 more

Michail G. Lagoudakis is a Professor at the Department of Electronic and Computer Engineering, Technical University of Crete. His academic journey includes a Ph.D. in Computer Science from Duke University (2003), an M.Sc. from the University of Louisiana, Lafayette (1998), and a B.Sc. from the University of Patras (1995). He has held prestigious positions such as Postdoctoral Fellow at Georgia Institute of Technology's School of Industrial and Systems Engineering. Research Interests : Spanning machine learning (especially reinforcement learning), decision-making under uncertainty, robotics, algorithm selection, computational biology, and human-computer interaction. Publications : Over 15 recent works, including key contributions to robotics (auction-based multi-robot routing), medical diagnosis (urgent endoscopy prediction), and foundational machine learning (Least-Squares Policy Iteration, RCPI algorithm). Scientific Recognition : Recipient of Duke University's Outstanding Dissertation Award (2002-2003) and two Outstanding Teaching Assistant Awards. Professional Affiliations : Member of AAAI, IEEE, and ACM. Collaborations include industrial applications in disassembly planning, dynamic packet routing, and medical imaging. He advocates for computational biology and interdisciplinary research, aiming to integrate tools from mathematics and control theory into machine learning.