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.
Ioannis Theodoridis is a Professor at the Department of Informatics, University of Piraeus, and Director of the Data Science Laboratory under the School of Information and Communication Technologies. His research focuses on data science, particularly large-scale data management and analysis, with applications in maritime informatics, spatiotemporal data, and mobility patterns. He holds editorial roles at ACM Computing Surveys and has contributed to numerous international conferences and journals. As a project leader in Horizon 2020 initiatives, he has coordinated research on data-driven solutions for maritime safety and urban mobility. He earned his Diploma (1990) and PhD (1996) in Electrical and Computer Engineering from the National Technical University of Athens (NTUA). His work includes developing scalable systems for maritime route forecasting (e.g., GMSA), frameworks for vessel trajectory prediction (e.g., VesselVision), and platforms like i4sea for fisheries monitoring. Contact: ytheod@unipi.gr .
Professor Gregoris Mentzas is a faculty member at the National Technical University of Athens, School of Electrical and Computer Engineering, where he directs the Division of Industrial Electric Devices and Decision Systems. His research focuses on AI-enabled decision systems, knowledge management, and semantic technologies applied to digital enterprises and e-government. With over 350 publications, he ranks among the top 2% most cited scientists globally. Research Interests: Artificial intelligence for decision augmentation, big data analytics in personalized health and smart mobility, semantic web technologies, and industrial internet of things. Current projects investigate trustworthy AI frameworks and hybrid intelligence systems for Industry 5.0. Teaching: Leads courses in Digital Enterprise Management, Strategic Information Systems, and Project Management at undergraduate and postgraduate levels, incorporating industry case studies and experiential learning approaches. Awards & Leadership: Top 2% Highly Cited Scientist (PLOS Biology 2021) 5 Best Paper Awards in international conferences Director of Information Management Unit (1997-present) Board Member of Institute of Communication and Computer Systems (2006-2009) Projects & Funding: Secured over €18 million in research grants through 60+ European projects with industry partners including SAP, IBM, and Siemens. Research outcomes led to three technology spin-offs.
Kostas Magoutis is Professor and Chair of the Computer Science Department at the University of Crete , and a collaborating researcher at FORTH-ICS . His research focuses on scalable distributed systems, cloud computing, IoT, and quantum-enhanced control. Education and Career: Ph.D. in Computer Science, Harvard University (2003) Research Staff Member, IBM T. J. Watson Research Center (2003-2009) Assistant Professor (2014-2019, tenured 2017) and Associate Professor (2020-2024), University of Crete Professor and Chair, University of Crete (2024-present) Research Interests: His work spans distributed computer systems , cloud computing , scalable data stores and stream-processing engines , Internet of Things , and the emerging area of quantum-enhanced control . Representative projects include the H.F.R.I.-funded QUADS (2025-2028) on quantum-enhanced adaptive systems, STREAMSTORE (2020-2023) on elastic stream processing, SmartCityBus on IoT-driven public transport, and the EU FP7 PaaSage project on model-based cloud lifecycle management. Awards and Honors: Best Paper Awards: USENIX ATC 2002, USENIX BSDCon 2002, IEEE SRDS 2014 (Best Student Paper), IoT 2024 (Runner-up) Grand Challenge Audience Award, ACM DEBS 2022 Best Poster Award, ACM EuroSys 2022 EU Marie Curie IEF Fellow (2009-2011) Alexander S. Onassis Fellow (1994-1995) and J. William Fulbright Scholar (1993-1994) Students and Mentoring: He has supervised or co-supervised more than 30 Ph.D., M.Sc. and undergraduate students, including Antonis Papaioannou (Ph.D. 2021), Efthimios Papageorgiou (current Ph.D.), and numerous M.Sc. graduates now in industry and academia. Labs and Teams: At FORTH-ICS he leads activities within the Distributed Systems and Storage Laboratory, coordinating research on scalable storage, stream processing, and IoT data management. The lab collaborates closely with European and national initiatives, hosting visiting researchers and industry partners.
Ioannis Iglezakis is an Associate Professor at the School of Law, Aristotle University of Thessaloniki (AUTH), specializing in the intersection of law and technology. His academic career spans over three decades with continuous contributions to informatics law, cyber law, data protection, and privacy law. At AUTH, he teaches courses including Law of Informatics, Computers and Law I (Cyberlaw I), Computers and Law II (Privacy and Security in the Information Society), Legal Aspects of Cybercrime, Internet-Law, and Law and Information Technology. Dr. Iglezakis earned his undergraduate degree in Law from AUTH in 1987, followed by a Magister Legum Europae from Hannover University in 1993. He completed his postgraduate studies in History, Philosophy and Sociology of Law at AUTH in 1990 and earned his PhD in Law from AUTH in 1999. His educational background combines Greek legal training with European legal perspectives. His research interests focus on the legal challenges posed by digital technologies, with particular emphasis on data protection, privacy law, cybercrime regulation, digital rights, and the application of GDPR in various contexts. He has published extensively on topics including the right to be forgotten, digital identity management, workplace surveillance in the digital age, hate speech online, and the legal implications of emerging technologies like blockchain and artificial intelligence. His work bridges theoretical legal analysis with practical applications in the rapidly evolving digital landscape. The trends in his publications reveal a consistent focus on the evolving relationship between law and technology, with increasing attention to GDPR implementation, health data protection, and the challenges of algorithmic decision-making. His work spans multiple disciplines including legal theory, privacy studies, cyber security, and digital governance, reflecting the interdisciplinary nature of modern informatics law. Dr. Iglezakis has supervised over 50 master's theses at AUTH, mentoring the next generation of legal scholars in areas including cloud computing contracts, personal data protection, social media law, intellectual property in digital environments, and cybercrime. His administrative roles have included membership on the European Educational Programs Committee (2011-2012) and the Legal Committee of AUTH (2013-2014). His research projects include the 2018-2019 study on 'Legal Issues of Mobile Applications Development, Distribution and Use,' the 2014 '6th International Conference on Informatics Law,' and the 2013-2015 Center of Excellence for Cybercrime for Education, Research and Training in Greece. These projects highlight his commitment to addressing practical legal challenges in the digital domain while contributing to academic discourse.
Jovan Stojkovic is an incoming Assistant Professor at the Department of Computer Science at the University of Texas at Austin, set to join in Fall 2026. Prior to his appointment at UT Austin, he will spend a year at Meta working with the AI and Systems Co-design group. His research focuses on cloud computing and datacenters, with particular emphasis on cloud-native workloads and machine learning inference. Education: PhD in Computer Science from the University of Illinois at Urbana-Champaign, advised by Professor Josep Torrellas Undergraduate studies at the School of Electrical Engineering, University of Belgrade, Serbia, where he was recognized as the best student of the Computer Engineering and Information Theory Department every year from 2017-2020 Research Interests: Jovan's research focuses on cloud computing and datacenters , with two primary domains: Cloud-native workloads , such as microservices and serverless computing. He investigates how to co-design novel hardware platforms and software systems that deliver orders-of-magnitude improvements in performance, energy efficiency, and resource utilization for these emerging workloads. Machine Learning (ML) inference , particularly large language models (LLMs). His work addresses the challenges of ML inference through smart scheduling, workload placement, and system-level configuration tuning to reduce energy, power, and thermal overheads while maintaining performance and accuracy guarantees. Publication Trends: Jovan's publications demonstrate a strong focus on optimizing cloud infrastructure for emerging workloads. His research spans across serverless computing, microservices, and large language model inference. A clear trend emerges in his work: addressing the performance, energy efficiency, and resource utilization challenges of modern cloud workloads through innovative hardware-software co-design approaches. His most recent work shows increasing focus on LLM inference optimization, particularly in the areas of thermal management, power efficiency, and scheduling for many-adapter environments. Awards and Honors: HPCA Best Paper Award (2025) IEEE MICRO Top Picks Honorable Mention (2024) 6 patents with IBM and Microsoft on: Serverless systems, Processor overclocking in the cloud, and Energy-efficient LLM inference W. J. Poppelbaum Memorial Award (2025) for hardware and architecture innovation Mavis Future Faculty Fellowship (2024–2025) Invited to present at 11th Heidelberg Laureate Forum (2024) Kenichi Miura Award (2022) for excellence in High Performance Computing Multiple student travel grants to ISCA, MICRO, ASPLOS, and HPCA Advising and Grants: Jovan is actively seeking prospective PhD students for his research group at UT Austin. His research has been supported through collaborations with major tech companies including IBM, Microsoft, and Meta. His six patents with IBM and Microsoft demonstrate the practical impact of his research in serverless systems, processor overclocking, and energy-efficient LLM inference. His work on serverless computing (MXFaaS, EcoFaaS) and LLM inference optimization has received significant recognition in top-tier computer architecture conferences. Research Groups: During his PhD at UIUC, Jovan worked with Professor Josep Torrellas on cloud infrastructure research. He has collaborated extensively with researchers at IBM Research (particularly Hubertus Franke) and Microsoft (particularly Íñigo Goiri and Ricardo Bianchini). His upcoming position at UT Austin will establish his independent research group focused on cloud computing and datacenter systems. His year at Meta working with the AI and Systems Co-design group will further strengthen his expertise in AI infrastructure.
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)
Dr. Aris Dimeas is a Researcher at the National Technical University of Athens in the Department of Electric Power and Industrial Applications . He holds a diploma and PhD in Electrical and Computer Engineering from NTUA and has extensive experience in power systems operations, renewable energy integration, and smart grid technologies. Specialized in AI applications for power systems Developed control software for demand side management Consultant for PPC (2007-2012) Research Focus : Smart grids and digital twin implementations Renewable energy market dynamics Microgrid optimization and control algorithms Collaborations : Active participant in EU research projects, collaborating with HEDNO and other energy grid operators on electronic meters and intelligent network deployments. Teaching : Instructs courses on electric energy systems, power system analysis, and energy management.
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.
Labros Bisdounis is a Professor at the Department of Electrical and Computer Engineering, University of the Peloponnese, Greece. He previously held positions at the Technological Educational Institute of Western Greece, including Associate Professor, Full Professor, and Dean of the School of Technological Applications (2016–2018). He has extensive industry experience as a senior research engineer and project manager at Intracom S.A. (2000–2008), focusing on VLSI circuits and telecom applications. His research interests include CMOS circuit timing/power modeling, low-power/high-speed design, MOSFET modeling, and sensor applications. He has authored over 30 papers with 740+ citations and is an IEEE member. Education: Diploma in Electrical Engineering (1992), University of Patras Ph.D. in Electrical Engineering (1999), University of Patras Research Interests: CMOS circuit timing and power dissipation modeling Deep-submicron/nano-CMOS circuit design MOSFET device modeling Low-power embedded systems and SoC Sensor applications and organic electronics Leadership Roles: Dean of the School of Engineering, University of the Peloponnese (2023–present) Director of Training & Lifelong Learning Centre (2019–2019) Board Member, Hellenic NARIC (2016–2019) Collaborations: Active at the Hellenic Open University as a tutor in Computer Architecture and Digital Systems modules. Co-developed the AETHER framework for pervasive computing and contributed to energy-aware SoC designs for 5 GHz WLANs.
Stavrakakis Ioannis is a Professor at the Department of Informatics and Telecommunications, School of Science, University of Athens, where he has served since 2002. He previously held academic positions at Northeastern University (1994-1999) and University of Vermont (1988-1994). Ph.D., Electrical Engineering (1988), University of Virginia Diploma, Electrical Engineering (1983), Aristotle University of Thessaloniki His research focuses on network resource allocation algorithms , cooperative content dissemination , mobile ad hoc networks , and privacy-aware protocols . He leads the Advanced Networking Research (ANR) Group. Recent publications highlight trends in AI-driven network optimization , edge computing for VR , drone-assisted sensor networks , and privacy in vehicular systems . Key themes include game theory applications, energy-efficient protocols, and distributed learning frameworks. Contact: ioannis@di.uoa.gr
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).
Dimitris Karlis is a Professor in the Department of Statistics at the Athens University of Economics and Business (AUEB), within the School of Information Sciences and Technology. He has been a key academic figure since earning his BSc and PhD in Statistics from AUEB in 1992 and 1999, respectively, and was promoted to Associate Professor in 2012 before advancing to full Professor. Education: BSc in Statistics, AUEB (1992) PhD in Applied Statistics, AUEB (1999) His research spans computational statistics, mixture models, EM algorithms, copulas, multivariate discrete data, and applications in sports, insurance, and seismicity. He has published extensively in top-tier statistical journals such as the Journal of the Royal Statistical Society and Statistics in Medicine . The 15 most recent publications reveal a strong focus on multivariate count data, integer-valued time series, model-based clustering using copulas, and applications in actuarial science and health. His work frequently involves mixture models, Bayesian inference, and innovative extensions of Poisson-based frameworks. Scientific Service and Recognition: Associate Editor: Metron, Communications in Statistics, IMA Journal of Management Mathematics, Stochastic Environmental Research and Risk Assessment Editor: Biometrics Bulletin of IBS Member: American Statistical Society, International Statistical Institute, International Association of Statistical Computing, Hellenic Statistical Institute Publicity Officer: Eastern Mediterranean Region, International Biometric Society Advising and Grants: He has supervised 4 completed PhDs and 18 Master’s theses, with several more in progress. He has led and participated in research projects funded by the European Union and EUROSTAT, particularly in official statistics. His advising spans methodological and applied topics in statistics. Labs and Teams: While no formal lab is named, he collaborates extensively with researchers in actuarial science, transportation, biostatistics, and environmental risk, often through joint projects and publications.
Professor Dollas Apostolos serves as a Professor in the School of Electrical and Computer Engineering at the Technical University of Crete (TUC), where he has held leadership roles such as Department Chairman. He directs the Microprocessor and Hardware Laboratory, focusing on reconfigurable computing, embedded systems, and high-performance digital systems. His work emphasizes rapid prototyping and real-world implementation of computational solutions. Education: Ph.D., Computer Science, University of Illinois at Urbana-Champaign (1987) M.Sc., Computer Science, University of Illinois at Urbana-Champaign (1984) B.Sc., Computer Science, University of Illinois at Urbana-Champaign (1982) Research Interests: Reconfigurable computing architectures FPGA-based acceleration for bioinformatics and genomics Embedded systems and real-time processing Hardware-software co-design for high-performance computing His research bridges theoretical innovation with practical applications, such as FPGA implementations for genome assembly and aquaculture monitoring systems. Publications: Recent work highlights FPGA-based solutions for bioinformatics (e.g., genome assembly acceleration), real-time embedded systems (e.g., fish cage net monitoring), and scalable data processing frameworks. His articles often explore the intersection of FPGA technology with computational biology, embedded vision, and distributed systems. Awards and Affiliations: Senior Member, IEEE and IEEE Computer Society Recipient of IEEE Computer Society Golden Core and Meritorious Service Awards Twice honored with the University of Illinois Teaching Excellence Award He is a co-founder of IEEE conferences like FCCM and RSP, reflecting his leadership in the reconfigurable computing community. Teaching and Labs: Teaches courses on computer architecture, logic design, and VLSI design. The Microprocessor and Hardware Lab under his direction drives advancements in FPGA-based systems, with projects ranging from bioinformatics hardware accelerators to embedded vision systems.
Kostas Magoutis is Professor and Chair of the Computer Science Department at the University of Crete and collaborating researcher with FORTH-ICS. His research focuses on distributed systems, scalable data processing, IoT, and cloud computing, with projects including GreenInCities for urban regeneration and STREAMSTORE for stateful stream processing systems. Research interests include: Distributed computer systems architecture Elastic stream processing platforms Quantum-enhanced computing applications Multi-cloud application lifecycle management Recent publications demonstrate strong focus on federated data systems, quantum computing applications, and IoT-enhanced infrastructure, with consistent output in high-impact conferences and journals. Awards and distinctions: Multiple best paper awards from USENIX conferences Grand Challenge Audience Award at DEBS 2022 Marie Curie Fellowship and IBM Research awards Advises over 20 PhD and MSc students in distributed systems research. Leads multiple EU-funded projects and serves on program committees for top conferences including SOSP, EuroSys, and IEEE BigData. Directs research groups in distributed systems and cloud computing at FORTH-ICS.
