جستجوی استاد راهنمای دانشگاهی

Stergios Tampekisمشاهده پروفایل

استادیار

• Forest Operations Engineering
• Sustainable Forest Management
• Geographic Information Systems (GIS)
• +۴ مورد دیگر

Stergios Tampekis is an Assistant Professor at the Department of Forestry and Natural Environment Management within the Faculty of Plant Sciences at the Agricultural University of Athens . His research focuses on forest operations engineering, emphasizing the optimization of human-environment interactions through Nature-Based Solutions. Based in Karpenisi, Greece, he contributes to sustainable forest infrastructure and wildfire prevention strategies. Contact: stampeki@aua.gr Phone: +30-22370-23282 Research Interests Tampekis specializes in: Environmental impact assessment of forest operations GIS-based spatial planning for fire management Development of Decision Support Systems (DSS) for forestry Resilient infrastructure planning in Mediterranean islands Integration of wildfire prevention with sustainable land use Recent Research Trends His recent publications highlight GIS-driven approaches for wildfire risk management, economic evaluation of forest infrastructure, and climate change adaptation through complex systems science. Key themes include multi-criteria analysis, spatial optimization, and sustainable resource deployment. Scientific Awards No awards listed in the provided text

Kalogeraki Vanaمشاهده پروفایل

استاد

• Distributed Systems
• Real-Time Systems
• Big Data Systems
• +۸ مورد دیگر

Prof. Vana Kalogeraki is a Faculty Member at the Department of Informatics , Athens University of Economics and Business (AUEB) , and serves as the Dean of the School of Information Sciences and Technology and Director of the Computer Systems and Communications Laboratory . She has held academic positions at the University of California, Riverside and was a Research Scientist at Hewlett-Packard Labs . PhD: University of California, Santa Barbara M.S. & B.S.: University of Crete, Greece Her research focuses on Distributed and Real-Time Systems , Big Data Systems , Cloud Computing , Human-Centered Systems , and Crowdsourcing . She has published over 200 papers at top journals (IEEE TPDS, ACM TOS, etc.) and conferences (RTSS, DSN, ICDCS, VLDB, MDM), including co-authoring the OMG CORBA Dynamic Scheduling Standard . Her 2023-2025 publications address AI pipelines in serverless environments, edge computing for trauma detection via eye-tracking, and fairness in resource scheduling. She has received prestigious awards including an ERC Starting Grant , Best Paper Awards (DEBS 2017, IPDPS 2009), a Best Poster Award (EuroSys 2024), and multiple UC Research Awards . Her research is funded by the European Union (ARISTEIA, THALIS), NSF, and industry partners like SUN and Nokia. Advising Legacy : Supervised 10 PhD graduates (now at Google, Amazon, IBM, Apple) and over 60 MS/PhD committees Labs & Teams : Leads the Computer Systems and Communications Laboratory at AUEB, focusing on mobile human-centered systems and urban data analytics

Ioannis Vlahavasمشاهده پروفایل

استاد

• Logic Programming
• Knowledge representation and Reasoning
• Automated Planning
• +۳ مورد دیگر

Ioannis Vlahavas is a Professor in the School of Informatics at Aristotle University of Thessaloniki since 2003, where he directs the Intelligent Systems Lab. He has held significant leadership roles including Chair of the School of Informatics (2003-2005, 2013-2017) and Dean of the School of Science and Technology at the International Hellenic University (2007-2016). His career spans over three decades with continuous contributions to artificial intelligence research and education. Education: Ph.D. in Computer Science, Aristotle University of Thessaloniki (1988) B.Sc. in Physics, Aristotle University of Thessaloniki (1982) Professor Vlahavas's research focuses on foundational AI areas including Logic Programming, Knowledge Representation and Reasoning, Automated Planning, and Machine Learning. His work bridges theoretical frameworks with practical applications in autonomous systems, healthcare diagnostics, and financial modeling. He has pioneered methodologies in reinforcement learning and multi-agent systems, with particular emphasis on personality emulation in gamified environments and transformer-based architectures for complex real-world problems. His recent publications reveal a strong trajectory toward deep reinforcement learning, transformer optimization, and low-resource language processing. Key application domains include autonomous driving (5 of 15 recent papers), biomedical text mining (particularly drug-drug interaction extraction), and personality modeling in gaming environments. There is notable cross-pollination between finance (portfolio theory applications, cryptocurrency trading) and AI methodology development. Scientific Awards: EurAI Fellow (2017) Professor Vlahavas has mentored numerous graduate students through PhD candidate programs and research projects. His leadership extends to organizing major international conferences including the 24th IEEE International Conference on Tools with AI (2012) and the 9th Hellenic Conference on Artificial Intelligence (2016). He serves on editorial boards and has guest-edited special journal issues on AI applications. He directs the Intelligent Systems Lab at Aristotle University, which operates as a multidisciplinary research hub focusing on machine learning, natural language processing, and intelligent system applications across healthcare, transportation, and finance sectors. The lab maintains strong industry connections including RealMINT, the university spin-off where he serves as CEO.

• Cyber Security
• Critical Infrastructure Protection
• Machine Learning
• +۷ مورد دیگر

Konstantinos Demertzis is a Postdoctoral Researcher in Cyber Security of Critical Infrastructures at the School of Civil Engineering, Democritus University of Thrace. He also serves as Chief Information Security Officer at the Research & Informatics Directorate of the Greek Army and maintains research affiliations with National and Kapodistrian University of Athens. His academic journey includes PhD studies in Advanced Machine Learning and multiple Master's degrees spanning Mathematics, Cyber Security, Big Data, and Networking Technologies. PhD in Advanced Machine Learning (2017) - Democritus University of Thrace MSc in Mathematics (2020) - University of Crete MSc in Cyber Security and Big Data (2020) - University of Thessaly MSc in Networking Technologies (2012) - University of the Aegean BSc in Military Science (1996) - Academy of Non-Commissioned Officers Demertzis's research spans the intersection of machine learning, cybersecurity, and critical infrastructure protection. His work focuses particularly on developing intelligent systems for cyber defense of urban critical infrastructure, with applications in smart grids, environmental monitoring, and disaster response. His methodology often combines biologically inspired computational intelligence approaches with blockchain technology and federated learning frameworks. He has published extensively in high-impact journals with particular emphasis on anomaly detection, adaptive learning systems, and privacy-preserving architectures. His recent publications demonstrate a clear trend toward increasingly sophisticated integration of machine learning with critical infrastructure security. The 15 most recent papers show progression from foundational machine learning applications to complex, multi-layered security architectures incorporating blockchain, explainable AI, and cross-modal neural networks. His work consistently addresses real-world security challenges in industrial control systems, smart cities, and military applications. Windows Azure for Research Award Winner (2015-2016) Multiple Postgraduate Academic Excellence Scholarships Google Scholarship (2017-2018) Cisco CCNA Cyber Ops Scholarship (2017-2018) Best Research Paper Award at ISCRAM-med 2017 IBM Cloud Award (2017) Demertzis has advised multiple research projects including the Operational Programme 'Digital Convergence' and the Electoral Observatory Internet Research Programme. His technical expertise spans a wide range of cybersecurity domains including network security, blockchain applications, and AI-powered threat detection systems. He maintains active collaborations across academic and military institutions, with particular focus on protecting critical national infrastructure. His laboratory work primarily centers on the Lab of Forest-Environmental Informatics and Computational Intelligence, where he has developed intelligent models for environmental risk assessment and critical infrastructure protection. Current research directions include blockchained adaptive federated auto meta-learning architectures for cybersecurity and privacy in Industry 4.0 environments.

• Biomedical Engineering
• Entropy Analysis
• Bubble Entropy
• +۱۳ مورد دیگر

George Manis is an Associate Professor in the Department of Computer Science and Engineering at the School of Engineering, University of Ioannina, Greece. He is a member of the IPAN lab and serves as a Guest Editor for a special issue on 'Entropy in Biomedical Engineering' in the journal Entropy . His research bridges biomedical engineering and computational systems, with a strong focus on entropy-based methods and machine learning for physiological signal analysis. PhD in Computer Science, National Technical University of Athens (1993–1997) MSc in Advanced Methods in Computer Science, Queen Mary, University of London (1992–1993) Diploma in Electrical and Computer Engineering, National Technical University of Athens (1987–1992) His primary research interests include Biomedical Engineering , Entropy Analysis (especially Bubble Entropy), Fast Computation Algorithms , Biomedical Data Classification , Heart Rate Analysis , and Computing Systems with emphasis on parallelization. He teaches postgraduate courses in data analysis and biomedical data processing, and undergraduate courses in compilers. The analysis of his recent publications reveals a consistent trend in developing computationally efficient and robust methods for entropy estimation and classification in biomedical contexts. His work on Bubble Entropy eliminates the need for scale parameters and enhances stability, while his improvements to Random Forests and Support Vector Machines target enhanced diagnostic accuracy in diseases like Alzheimer’s and heart conditions. In computing systems, he has pioneered compiler technologies for parallelizing recursive functions and optimizing runtime scheduling. No scientific awards are explicitly mentioned in the provided text. George Manis has advised or collaborated with several researchers, including Evanthia Tripoliti, Dimitrios Fotiadis, Petros Arsenos, Argyro Kampouraki, and others, indicating active supervision and research leadership. He is currently involved in funded projects such as Palimpsest , an interactive museum system, and Homore , a smart monitoring system for elderly individuals. These projects reflect his interest in applying advanced computing to real-world biomedical and societal challenges. He is affiliated with the IPAN lab and contributes to the development of innovative algorithms for entropy computation and parallel processing. His work on the C2μTC/SL compiler and Ariadne system demonstrates deep expertise in compiler design for specialized architectures like the SVP processor.

• Parallel Computing
• Distributed Systems
• Multiprocessor Operating Systems
• +۵ مورد دیگر

Vasilios Mamalis is a Professor at the Department of Informatics and Computer Engineering, University of West Attica, and a member of the Collaborating Scientific Staff at the Hellenic Open University's Informatics program. His academic career spans decades with significant contributions to parallel and distributed computing, wireless sensor networks, and cloud technologies. Education: Diploma in Computer Engineering and Informatics, University of Patras (1993) PhD in Computer Engineering and Informatics, University of Patras (1998) Research Interests focus on parallel algorithms, distributed systems, wireless sensor networks, cloud computing, and information retrieval. His work addresses energy efficiency in ad-hoc networks, optimization techniques, and educational technology applications. Publication Trends show extensive work on WSN clustering, cloud task scheduling, parallel simplex methods, and fog computing applications in education and urban systems. He combines metaheuristics with infrastructure optimization in large-scale networks. Scientific Contributions include editorial roles in the Journal of Balkan Libraries Union and program committee memberships in international conferences. He actively reviews for journals and conferences in computing. Teaching Expertise covers operating systems, parallel computing, distributed systems, and cloud technologies at both undergraduate and postgraduate levels. His Research Leadership involves EU/Greek-funded projects on communication protocols, parallel content-based retrieval, and wireless sensor networks.