جستجوی استاد راهنمای دانشگاهی

• Optical Metrology
• Coherent Metrology
• Holography
• +۷ مورد دیگر

Dr. Vivi Tornari is a Research Fellow and head of the Holography laboratory at IESL/FORTH, specializing in optical metrology and cultural heritage preservation. She has held this position since 1996 and has coordinated major EU projects such as E-RIHS and CHARISMA . Her work focuses on developing holographic interferometry techniques for structural diagnosis of artworks, fraud detection, and environmental impact assessment. She holds a PhD in Applied Science from the University of Sunderland and has authored over 70 scientific publications. Education: Postdoctoral Fellow in Optical Holography, Royal College of Art (RCA), London (1990) PhD in Applied Science, University of Sunderland, UK (2009) MSc in Chemical Engineering/Material Science, National Technical University of Athens (1996) Research interests include laser-based structural analysis, speckle interferometry, and the integration of optical methods for heritage preservation. She has pioneered non-invasive diagnostic tools such as the Applied Holography Metrology Laboratory and has advised on EC projects as an evaluator. Funding highlights include: Leadership in EU projects totaling over €20M Coordinator of SYDDARTA (FP7) and CLIMATE FOR CULTURE (FP7) PI for HOLOAUTHENTIC (FP5) and LASERACT (FP6) Her publications emphasize interdisciplinary collaboration, combining optical engineering with conservation science. Key innovations include: Development of DHSPI (Digital Holographic Speckle Pattern Interferometry) Integration of thermography with interferometry for defect analysis Laser ablation studies on polymer substrates Labs/Teams: Lead the Holography Lab at IESL, collaborating with international institutions like the V&A Museum and Imperial College London. Current projects focus on European research infrastructures (E-RIHS) and climate change impacts on heritage materials.

Ioannis Pitasمشاهده پروفایل

استاد

• Computer Vision
• Machine Learning
• Autonomous Systems
• +۵ مورد دیگر

Ioannis Pitas is a Professor at the Department of Informatics, Aristotle University of Thessaloniki (AUTH), and serves as the Director of the Artificial Intelligence and Information Analysis (AIIA) Lab. He has held visiting roles at multiple international universities and is actively engaged in research and R&D projects funded by the European Union. Education : 1980 - Degree in Electrical Engineering, AUTH; 1985 - PhD in Electrical Engineering, AUTH Research interests encompass computer vision, machine learning, autonomous systems, biomedical imaging, affective computing, and cultural heritage conservation. His work has resulted in over 920 publications, 11 books, and 35,200+ citations. Scientific awards : IEEE Fellow IEEE Distinguished Lecturer EURASIP Fellow Prof. Pitas has coordinated 47 competitive R&D projects, including Horizon Europe initiatives like TEMA , AI4EUROPE , and SIMAR . He leads the International AI Doctoral Academy (IAIDA) under the AI4Media project and has organized major conferences such as IEEE ICIP2001 and EUSIPCO98.

• Design and Implementation of Electronic Systems
• Intelligent Systems
• Machine Vision
• +۳ مورد دیگر

Ioannis Andreadis is a Professor in the Department of Electrical and Computer Engineering at the School of Engineering, Democritus University of Thrace. He has been a faculty member since 1993, following his appointment as a Visiting Professor at the School of Technological Applications of TEI Kavala (1991-1992). His academic journey began with a Diploma in Electrical Engineering from Democritus University of Thrace (1983), followed by an M.Sc. in Electrical Engineering & Electronics (1985) and a Ph.D. in Instrumentation & Analytical Science (1989), both from the University of Manchester. Professor Andreadis's research spans the Design and Implementation of Electronic Systems with particular emphasis on Intelligent Systems and Machine Vision . His work has resulted in over 230 publications in international journals, book chapters, and conference proceedings. He has made significant contributions to image processing, particularly in mathematical morphology, color image processing, and real-time implementation of image processing algorithms. His research has practical applications in seismic signal processing, crowd management systems, and 3D reconstruction technologies. The analysis of his recent publications reveals a strong focus on advanced image processing techniques, with increasing integration of deep learning approaches. His work spans both theoretical foundations (such as entropy estimation and moment calculations) and practical applications (including image stabilization, multi-focus image fusion, and crowd management systems). The interdisciplinary nature of his research connects electrical engineering, computer vision, and signal processing with applications in safety engineering, structural analysis, and robotics. Among his notable achievements are the IET Image Processing Premium Award (2009) , Best Paper Award at PSVIT 2007 , and Best Paper Award at EUREKA 2009 . He was elected Fellow of the Institute of Engineering & Technology (IET) in 2006 and Fellow of the Institute of Measurement & Control (InstMC) in 2021. He has also served as Subject Editor of the IET Electronics Letters and as Guest Editor for special issues of Pattern Recognition journal. Professor Andreadis has supervised 14 PhD theses , 21 Master's theses , and 88 Diploma works , demonstrating his commitment to academic mentoring. His research has been supported by significant grants including the EDUnet project (€280,000), wireless network implementation (€37,000), laboratory infrastructure development (€120,000), school information systems support (€478,000), the RESCUER project (€350,000 as Deputy P.I.), and the EDUSAFE project (Marie Curie Actions). He leads the Electronics Laboratory at Democritus University of Thrace, which has undergone significant infrastructure development through multiple funding sources. His work on the RESCUER project demonstrates collaboration with European partners on emergency risk management systems, while his EDUSAFE involvement shows commitment to advanced AR/VR safety systems development. His research group applies computational intelligence techniques to diverse challenges from seismic analysis to pedestrian evacuation modeling.

Konstantinos G. Arvanitisمشاهده پروفایل

استاد

• Electrification
• Automation
• Digitalization in Agriculture
• +۲۳ مورد دیگر

Konstantinos G. Arvanitis is a Professor in the Department of Natural Resources Management & Agricultural Engineering at the Agricultural University of Athens, affiliated with the Agricultural Engineering Laboratory. He holds a PhD in Electrical and Computer Engineering from the National Technical University of Athens and has held diverse research and teaching roles across Greek institutions. Teaches courses on electrical engineering, sensors, automation, and AI in agriculture Supervised 2 PhD, 9 MSc theses, and guides 6 ongoing PhD projects Member of FEANI, EurAgEng, and IFAC Technical Committee (2000-2017) His research integrates IoT, machine learning, and cyber-physical systems into agricultural practices, focusing on precision agriculture and sustainability. He contributes to editorial boards of journals like Sensors and Energy , and has published over 342 technical works with significant citation metrics. His recent work explores quantum technologies, edge computing, and 3D printing in agricultural systems, emphasizing energy efficiency and educational innovation. He actively reviews for 130+ journals and conferences.

Chrysanthos Maraveasمشاهده پروفایل

استادیار

• Agricultural Engineering
• Sustainable Materials
• Artificial Intelligence Applications
• +۵ مورد دیگر

Chrysanthos Maraveas is an Assistant Professor at the Department of Technology and Natural Resources Management & Agricultural Engineering in the School of Environment and Agricultural Engineering at the Agricultural University of Athens since 2022. He earned his PhD in Structural Engineering from the University of Manchester and has held postdoctoral research positions at the University of Liège (EU-funded) and the University of Patras (Greek Ministry of Development-funded). Research Interests : Applications of AI and quantum computing in agriculture Sustainable materials and biodegradable polymers from agricultural waste Internet of Things (IoT) for greenhouse optimization Structural durability and corrosion resistance in agricultural environments Plastic waste management in agrifood systems 4D printing for sustainable agricultural plastics Scientific Recognition : Ranked in the top 2% of scientists worldwide by Stanford University (based on citations and h-index) Publications focus on: Cybersecurity in Agriculture 4.0/5.0 Smart sensors and edge computing for resource management Biopolymer innovations and nanotechnology Structural analysis of agricultural systems Sustainable construction materials from agro-waste Fire resistance in steel and composite structures

Christos Diouمشاهده پروفایل

دانشیار

• Machine Learning
• Artificial Intelligence
• Healthcare Applications
• +۳ مورد دیگر

Christos Diou is an Associate Professor of Artificial Intelligence and Machine Learning at the Department of Informatics and Telematics, Harokopio University of Athens, Greece. His academic career spans over 15 years of participation in national and international research projects, with a focus on machine learning algorithms, domain generalization, causal inference, and bias mitigation. He earned a BSc and Ph.D. in Electrical and Computer Engineering from Aristotle University of Thessaloniki. His research emphasizes the application of machine learning to healthcare, addressing challenges such as visual bias mitigation, causal effect estimation from observational data, and fairness-aware representation learning. Notable projects include REBECCA and RELEVIUM , both EU-funded, and MELIORA , targeting lifestyle interventions for breast cancer risk reduction. He has published extensively in top-tier venues like IEEE TPAMI, CVPR, and ICCV. Christos is a leading voice in AI ethics and healthcare innovation, with over 150 publications and best paper awards at IEEE Big Data Service 2023 and AIAI 2022. His work includes developing platforms like Effector for feature effects and Beam for behavior studies. He collaborates with institutions such as Karolinska Institutet and CERTH/ITI, and his students include PhD candidates Ioannis Sarridis and Aristotelis Ballas.

George Papadopoulosمشاهده پروفایل

استادیار

• Computer Graphics
• Computational Vision
• Computer Vision
• +۷ مورد دیگر

George Papadopoulos is an Assistant Professor in the Department of Informatics and Telematics at Harokopio University of Athens, Greece. His research focuses on computer graphics, computational vision, artificial intelligence, and machine/deep learning, with emphasis on self-supervised learning, visual captioning, and X-ray image analysis. He holds a Diploma and Ph.D. in electrical and computer engineering from Aristotle University of Thessaloniki (AUTH). Education: Diploma in Electrical and Computer Engineering (AUTH) Ph.D. in Electrical and Computer Engineering (AUTH) He has over 20 years of experience in EU-funded research projects, currently serving as Principal Investigator (PI) for projects such as Ceasefire (Technical Manager), ONELAB, KLEPTOTRACE, TRIFFID (Coordinator), GANNDALF, ARMADILLO, and TORNADO (Deputy Coordinator). No scientific awards explicitly mentioned in the text. His advisory roles and grants are tied to his EU project leadership and coordination roles. His work is centered around interdisciplinary teams collaborating on ICT, security, and robotics initiatives.

• Service-Oriented Architectures
• Cloud Computing
• Data Management
• +۷ مورد دیگر

Professor Kyriazis Dimosthenis holds a faculty position at the Department of Digital Systems, University of Piraeus. He earned his diploma in Electrical & Computer Engineering from the National Technical University of Athens (2001) and a cross-disciplinary MSc in Techno-Economic Systems (2004). His academic rank is Professor specializing in service-oriented architectures with a focus on quality of service and workflow management. He has led European projects like BigDataStack, CrowdHEALTH, and CYBELE, addressing challenges in cloud computing, edge computing, and AI-driven solutions for healthcare, finance, and industrial sectors. His research emphasizes resilient service-oriented systems, AI explainability, and human-centric digital transformation. Notable contributions include frameworks for dynamic resource allocation in hybrid cloud/edge environments, AI applications for maritime safety, and data governance solutions for cross-sector integration. He coordinates initiatives such as the Future Internet Architecture Board and Cloud QoS&SLAs, driving advancements in federated data marketplaces and sustainable computing practices. His recent work explores Large Language Model (LLM) applications in financial decision-making, conversational AI for MLOps, and neurosymbolic systems for defect detection. He also investigates XAI methodologies, including VirtualXAI, which leverages GPT-generated personas for explainability assessment. His projects often bridge technical innovation with societal impact, such as the iHELP platform for holistic health records and SmartCHANGE for behavioral change strategies in youth health. Key themes in his publications include bias mitigation in machine learning, dynamic deployment prediction in hybrid cloud settings, and energy-efficient data spaces for mobility. He has contributed to standards like the H2020-funded IRMOS and 5GTANGO, emphasizing interoperability and fault-tolerant architectures. His work frequently intersects with EU policy frameworks, particularly in data governance and ethical AI implementation.

Christos Antonopoulosمشاهده پروفایل

دانشیار

• Wireless Networks
• Network Communication Protocols
• Embedded Software
• +۶ مورد دیگر

Dr. Christos Antonopoulos is an Associate Professor at the Department of Electrical and Computer Engineering, University of Patras. He holds a Diploma and PhD in Electrical Engineering from the University of Patras (2002, 2008) and has participated in over 16 European research projects (FP5, FP6, FP7, Horizon 2020) and 6 national projects. Research Interests: Wireless Networks Cyberphysical Systems Embedded Software Architecture Internet of Things Cross-Layer Protocols Sensor Networks Technical Expertise: His work involves network simulation, power optimization, and reconfigurable computing. He has published >100 journal/conference papers and 13 book chapters with over 1000 citations.

Andy D. Pimentelمشاهده پروفایل

استاد

• Multi-core embedded systems
• System-level design, modeling and simulation
• Design space exploration
• +۷ مورد دیگر

Andy D. Pimentel is a Full Professor at the University of Amsterdam, where he chairs the Parallel Computing Systems (PCS) group within the Systems and Networking Lab at the Informatics Institute. His work focuses on the design, programming, and run-time management of multi-core and multi-processor computer systems, with particular attention to performance, power/energy consumption, system dependability, and design productivity. His academic background includes: PhD in Computer Science, 1998, University of Amsterdam MSc in Computer Science, 1993, University of Amsterdam Professor Pimentel's research spans multiple critical areas in modern computing systems. His primary interests include multi-core embedded systems, system-level design and simulation, design space exploration, performance and power analysis, system dependability, hardware/software co-design, run-time resource management, and Edge AI. His work addresses the growing challenges of making computer systems faster, more sustainable, energy efficient, reliable, and secure in an era of increasing computational demands and climate concerns. The PCS group he leads performs research on the modeling, analysis and optimization of extra-functional aspects of computing systems, which play a pivotal role in their work. An analysis of Professor Pimentel's recent publications reveals a strong focus on edge computing, distributed AI, and energy-efficient system design. His work bridges theoretical computer architecture with practical implementation challenges, particularly in the context of resource-constrained environments. Key trends include the adaptation of AI models for edge devices, thermal management in advanced architectures, and optimization of multi-core systems for both performance and energy efficiency. His research increasingly addresses sustainability concerns in computing, reflecting broader industry and academic priorities. His notable scientific achievements include: IEEE CEDA Outstanding Service Recognition Award DATE Fellow Award Professor Pimentel has served in numerous leadership roles in the academic community, including as General Chair of Design Automation and Test in Europe (DATE) 2024, Vice General Chair of IEEE/ACM Embedded Systems Week 2025, and General Chair of IEEE/ACM Embedded Systems Week 2026. He has secured significant research funding for projects related to sustainable computing, edge AI, and multi-core system design. His professional service includes board membership with the ICT Research Platform Nederland (IPN) since 2020 and leadership roles in major conferences such as DATE, Embedded Systems Week, and SAMOS. The Parallel Computing Systems group he chairs is a vibrant research team within the Systems and Networking Lab at the Informatics Institute. The PCS group focuses on the challenges of modern computing systems, particularly addressing the extra-functional aspects like performance, power consumption, and system dependability. Their work is highly relevant to current technological challenges in edge computing, sustainable systems design, and the integration of AI into resource-constrained environments.

Michael Carbinمشاهده پروفایل

دانشیار

• Programming Systems
• Probabilistic Programming
• Quantum Computing
• +۳ مورد دیگر

Michael Carbin is an Associate Professor at MIT in the Department of Electrical Engineering and Computer Science (EECS), where he leads the Programming Systems Group at the Computer Science and Artificial Intelligence Laboratory (CSAIL). His research centers on developing programming systems that handle uncertainty through probabilistic programming, quantum computing, and neural networks. Carbin's work spans programming languages, systems, and machine learning, with themes including uncertainty management, efficiency optimization, and formal verification. His publications demonstrate a strong focus on probabilistic inference methods, neural network optimization, and quantum programming frameworks. Awards and Honors: Sloan Research Fellowship (2020) Multiple Best Paper Awards (OOPSLA 2013, 2014; ICLR 2019) NSF CAREER Award (2018) Google Faculty Research Award (2018) As the head of the Programming Systems Group, he advises 10+ graduate students and postdocs, focusing on cutting-edge systems research. He has secured grants including Facebook Research Awards and NSF funding.

Doitsidis Eleftheriosمشاهده پروفایل

دانشیار

• Multirobot Systems
• Autonomous Vehicles
• Control Systems
• +۵ مورد دیگر

Dr. Eleftherios Doitsidis is an Associate Professor at the School of Production Engineering & Management of the Technical University of Crete (TUC) and a member of the Intelligent Systems & Robotics Laboratory. Previously, he served as faculty at the Department of Electronic Engineering at Hellenic Mediterranean University. His expertise spans multirobot systems, autonomous vehicle control, and computational intelligence. He holds a robust record of EU and national research project involvement. Research Interests: Specializes in multirobot team coordination, autonomous navigation systems for UAVs/AUVs, control systems design, and computational intelligence applications. Recent work focuses on energy-efficient path-planning for swarms, educational robotics frameworks like HYDRA, and digital twin integration in autonomous systems. Publications Trends: His 150+ publications address cutting-edge topics including: Autonomous vehicle control architectures Modular robotics for STEM education Optimization algorithms for multirobot systems Energy efficiency in manufacturing systems Advising & Projects: Lead researcher on numerous funded projects involving UAV/AUV missions, swarm robotics, and educational technology. Active in collaborative research with institutions like the University of South Florida. Labs & Groups: Leads the Intelligent Systems & Robotics Lab at TUC, developing advanced robotic platforms and educational tools. Maintains an open-access research portal at doitsidis.tuc.gr .

• Robotic Vehicles
• Computational Intelligence
• Cooperative Control and Optimization
• +۳ مورد دیگر

Lefteris Doitsidis is an Associate Professor at the School of Production Engineering and Management, Technical University of Crete. He holds a PhD in Production and Management Engineering from the same institution (2008), with prior academic positions at the Department of Electronics, Hellenic Mediterranean University. His professional journey includes visiting scholar roles at the University of South Florida, USA. Research focuses on robotic systems, including autonomous navigation of UAVs/AUVs, multirobot teams, computational intelligence, and educational robotics. He leads the Intelligent Systems and Robotics Laboratory, developing tools like HYDRA for STEM education and frameworks for industry 4.0 applications such as bin-picking and precision agriculture. His work integrates control systems optimization, energy efficiency in manufacturing, and digital twin technologies. Over 65 publications span journals, conferences, and books, emphasizing practical implementations like ROS-based autonomous vehicle testbeds and energy management systems for electric vehicles. Key contributions include UAV path planning algorithms, swarm robotics coordination, and sensor fusion techniques. Current research trends emphasize sustainability in manufacturing, educational robotics platforms, and autonomous systems validation through advanced algorithms like Deep Deterministic Policy Gradient.

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

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

Georgios Siolasمشاهده پروفایل

پژوهشگر

• machine learning
• text mining
• information retrieval
• +۶ مورد دیگر

Georgios Siolas is a Senior Researcher at the Artificial Intelligence and Learning Systems Laboratory (NTUA-ISLab), part of the School of Electrical & Computer Engineering at the National Technical University of Athens (NTUA). He holds a BSc in Electrical & Computer Engineering from NTUA (1998), an MSc in Cognitive Science from Sorbonne Université (1999), and a PhD in Computer Science (2003). His research focuses on machine learning, text mining, information retrieval, and semantic web technologies, with applications in computer vision, recommender systems, and social network analysis. He develops intelligent systems for cultural heritage management, smart tourism platforms, and sign language recognition. Key contributions include innovations in neural architecture search, deep learning for hyperspectral imagery, and plagiarism detection in imbalanced datasets. His work integrates semantic technologies with pervasive computing for smart home environments.