Professor Alexiou Aggeliki is a faculty member at the Department of Digital Systems, University of Piraeus, specializing in 'Wireless Communication Systems.' She holds a Diploma in Electrical & Computer Engineering from the National Technical University of Athens (1994) and a PhD in Electrical Engineering from Imperial College, University of London (2000). Previously, she worked at Bell Laboratories (now Nokia Bell Labs) from 1999 to 2009, first as a Researcher and later as Technical Manager. Her research focuses on advanced wireless systems, including smart antennas, MIMO, 5G/6G networks, and machine learning applications. She leads the H2020 projects TERRANOVA (Coordinator) and ARIADNE (Technical Coordinator), and chairs the Wireless World Research Forum's Radio Communication Technologies and High Frequencies Radio Communication Technologies working groups. She is a member of IEEE, IET, and the Greek Engineers Association.
Constantine Dovrolis is a Professor at the School of Computer Science, Georgia Institute of Technology, and Director of the Center for Computational Science and Technology (CaSToRC) at The Cyprus Institute. He holds a BEng from the Technical University of Crete (1995), M.S. from the University of Rochester (1996), and Ph.D. from the University of Wisconsin-Madison (2000). His research bridges Network Theory, Machine Learning, and Neuroscience, focusing on neuro-inspired architectures and structural adaptation in AI systems. His work includes pioneering contributions to sparse neural networks, continual learning through structural adaptation, and hierarchical modularity in neural networks. His research has been supported by NSF, NIH, DOE, DARPA, Google, Microsoft, and Cisco, resulting in over 15,000 citations and an h-index of 56. Affiliations: Georgia Tech (Primary), Cyprus Institute (Director of CaSToRC) Research Themes: Neuro-inspired AI, Network Science, Machine Learning Theory, Computational Neuroscience Grants: Over $10M in funding from U.S. agencies and industry partners
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 .
George Vouros is a Professor in the Department of Digital Systems at the University of Piraeus, Greece. He is the head of the AI Lab (http://ai-group.ds.unipi.gr/ai-group/) and director of the MSc in Artificial Intelligence program in collaboration with the Institute of Informatics and Telecommunications at NCSR Demokritos. He completed his BSc in Mathematics (1986) and PhD in Artificial Intelligence (1992) at the University of Athens. His research focuses on Expert Systems, Knowledge Management, Multi-Agent Systems, Reinforcement Learning, and Mobility Analytics. He has served as program chair and committee member for major conferences (AAMAS, AAAI, IJCAI) and editorial roles in journals like Discover Artificial Intelligence (Springer Nature) and Information (MDPI). He has supervised 13 PhD students and currently oversees 4. His work spans EU-funded projects and national initiatives, emphasizing scalable mobility analytics, air traffic management automation, and ontology engineering. He is also President of the Hellenic A.I. Society and actively promotes interdisciplinary applications of AI in healthcare, transportation, and environmental monitoring. Recent research highlights include deep reinforcement learning for tactical air traffic conflict resolution, LLM-integrated ontology engineering, and multimodal generative adversarial imitation learning for flight trajectory modeling. His work bridges theoretical advancements with real-world applications in critical infrastructure systems.
Stavros Demetriadis is a Full Professor at the School of Informatics, Aristotle University of Thessaloniki, Greece. His research focuses on Learning Technologies, including Conversational Agents in Education, Learning Analytics, Computer-Supported Collaborative Learning (CSCL), Computational Thinking, and Massive Open Online Courses (MOOCs). He has led EU-funded projects like colMOOC and developed educational tools such as 'pytolearn' for Python instruction and 'Cubes Coding' (winner of Open Education Challenge 2014 and NUMA Competition 2014). He has supervised 5 completed PhD theses, 4 ongoing PhDs, and over 60 Master’s theses. Academic Appointments: Full Professor (2020–present), Associate Professor (2015–2020), Assistant Professor (2012–2015), Lecturer (2002–2008), Informatics Teacher (1989–2002) Education: PhD in Multimedia Technology in Education (2000), MSc in Electronic Physics (1986), BSc in Physics (1983) His work bridges AI and education, with over 161 publications and an h-index of 27. Recent research explores ChatGPT integration, ethics in Learning Analytics, and AI-driven assessment tools. He has delivered invited talks at institutions like the University of Valladolid (2024) and coordinates the 'Teachers' Fast-paced Distance Training on Tele-education' project. Awards include three international best paper awards and recognition for his 'Cubes Coding' project. Key Research Contributions: Developed frameworks for Conversational Agents in CSCL Innovated Computational Thinking pedagogy through robotics Explored ethics and culture in Learning Analytics adoption Created Python-based MOOCs for non-programmers He has taught courses like Human-Computer Interaction and Learning Analytics, and led short programs on Conversational AI. His collaborations span institutions in Spain, Denmark, and Greece. ORCID: 0000-0002-1561-6372; Google Scholar, Semantic Scholar, and Scopus profiles list his extensive output.
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.
Vlahogianni Eleni is a Professor and Dean of the Department of Transportation Planning and Engineering at the National Technical University of Athens (NTUA). Her research focuses on integrating machine learning , quantum computing , and reinforcement learning with urban mobility and traffic engineering , addressing challenges in eco-routing , congestion pricing , and autonomous vehicle interactions . Her work emphasizes data-driven approaches to traffic forecasting, including quantum neural networks and theory-aware unsupervised learning . Recent publications explore mixed traffic environments , shared space modeling , and parking occupancy prediction , highlighting her commitment to advancing intelligent transportation systems . Professor Vlahogianni leads the Traffic Engineering Laboratory at NTUA and contributes to policy frameworks for connected and automated transport , wildfire resilience , and dynamic mobility solutions . She is actively involved in the LEVITATE project and advocates for explainable AI in transportation applications.
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.
Brandon Lucia is a Full Professor in the Department of Electrical and Computer Engineering at Carnegie Mellon University's College of Engineering. He leads the abstract research group focusing on the intersection of computer architecture, systems, and programming languages. His work bridges theoretical foundations with practical implementations in energy-constrained environments. Lucia's research centers on intermittent computing systems and edge computing in extreme environments. His work on energy-harvesting systems has established fundamental principles for batteryless computing, while his orbital edge computing research pioneers computational intelligence for nanosatellite constellations. These research thrusts address critical challenges in reliability, efficiency, and programmability for systems operating under severe power constraints. His publication record shows a clear evolution from foundational work on intermittent computing models to sophisticated applications in space computing and edge intelligence. Recent publications demonstrate increasing integration of dataflow architectures with energy-harvesting constraints, particularly in satellite constellations where computational resources must be managed across distributed, power-constrained platforms operating in extreme environments. NSF CAREER Award (2017) IEEE TCCA Young Computer Architect Award (2019) Sloan Foundation Fellowship (2021) ASPLOS Best Paper Awards (2018, 2020) OOPSLA Distinguished Paper and Artifact Awards (2015) Lucia actively mentors numerous PhD students including Brad Denby, Zhuo Cheng, and Emily Ruppel, many of whom contribute significantly to his research program. His abstract research group maintains strong industry connections while pursuing fundamental advances in computing systems. The group has developed multiple open-source tools including Legerdemain for program analysis and MultiCacheSim for cache coherence simulation. His laboratory work spans from theoretical foundations of intermittent computing to practical implementations in space systems. Current projects include computational nanosatellite constellations, energy-minimal dataflow architectures, and secure edge computing systems that operate reliably despite frequent power failures.
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.
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).
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.
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.
Sotirios K. Goudos is a Professor at the Department of Physics, Aristotle University of Thessaloniki (AUTH), Greece, and Director of the ELEDIA@AUTH lab within the ELEDIA Research Center Network. His research focuses on antenna design, evolutionary algorithms, wireless communications, machine learning, and IoT applications. He holds a B.Sc. in Physics (1991), M.Sc. in Electronics (1994), Ph.D. in Physics (2001), and additional qualifications in Information Systems and Electrical Engineering. Prof. Goudos is a Senior Member of IEEE and serves as Editor-in-Chief of the Telecom open access journal (MDPI) and Associate Editor for IEEE Transactions on Antennas and Propagation, IEEE Access, and IEEE Open Journal of the Communication Society. He has organized multiple special issues in journals like EURASIP Journal on Wireless Communications and Networking and has authored/edited books on antennas and AI in networks. His awards include multiple IEEE Access Outstanding Associate Editor recognitions (2019–2023) and inclusion in Stanford University's top 2% scientists list (2020–2024). He teaches courses on telecommunications, Java programming, and microwave systems, and has supervised over two dozen master's students since 2009. His work spans antenna optimization, AI-driven communications, and IoT security, with contributions to 5G/6G, RIS systems, and smart agriculture. Prof. Goudos actively contributes to IEEE Greece Section leadership roles, including Secretary (2022) and Vice-Chair (2023–2024). His labs and teams focus on ELEDIA's research in electromagnetics, optimization, and AI applications.
