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Alexandros NtoulasView profile

Assistant Professor

• Big Data Systems
• Web Search
• Social Network Analysis
• +5 more

Alexandros Ntoulas is an Assistant Professor at the National and Kapodistrian University of Athens, Department of Informatics and Telecommunications. He holds a Ph.D. and M.Sc. from UCLA, and prior industry experience at Microsoft Research, Zynga, Samsung Research, and LinkedIn, focusing on scalable Machine Learning for Big Data applications. He co-founded Infocious (now Piksel) and has served as Program Co-Chair for PAKDD 2020 and Track Chair for IEEE Big Data Congress 2017. Education: Ph.D. and M.Sc. in Computer Science, University of California Los Angeles (UCLA) MSc and Engineering Diploma, Computer Engineering and Informatics Department, University of Patras Research interests span Big Data systems for Web search, social networks, and scalable Machine Learning applications. Notable achievements include 15 patents and awards such as the Best Paper Award at ICDE 2005 and KDD 2017's Best Applied Data Science Reviewer Award. Teaching includes courses like Web Information Systems, Systems Programming, and Big Data Management at the University of Athens. He has also held invited lectureships at UC Berkeley, University of Patras, and the University of Patras' Mathematics Department. Awards highlight contributions to data science and search engine innovation, including recognition from academic foundations and industry peers.

Dimitris AchlioptasView profile

Professor

• Theoretical Computer Science
• Algorithms
• Randomized Algorithms
• +5 more

Dimitris Achlioptas is a Professor at the Department of Informatics and Telecommunications, National and Kapodistrian University of Athens. His research focuses on theoretical computer science, algorithms, and probabilistic methods. He has contributed extensively to areas such as satisfiability problems, random constraint satisfaction, combinatorial optimization, and phase transitions in random structures. His work bridges algorithm design with probabilistic analysis, often leveraging tools from discrete mathematics and statistical physics. Key research themes include the Lovász Local Lemma, random k-SAT, and the interplay between computational complexity and statistical properties of problems. Notable contributions address algorithmic barriers from phase transitions, solution space geometry of random CSPs, and efficient sampling techniques for combinatorial structures. His recent work explores applications of probabilistic methods in machine learning and optimization, including scalable algorithms for high-dimensional problems.

• Algorithmic Game Theory
• Approximation Algorithms
• Facility Location Problems
• +2 more

Dimitris Fotakis is Professor of Computer Science at the National Technical University of Athens (NTUA) and Collaborating Senior Researcher at the Archimedes Unit/ATHENA RC. His research in theoretical computer science focuses on algorithmic game theory, approximation algorithms, and facility location problems. He leads research projects including BALSAM (Beyond Worst-Case Analysis in Approximation Algorithms) funded by HFRI. With publications in ICALP, NeurIPS, and STOC, his work develops efficient algorithms for optimization under uncertainty. Fotakis serves on program committees of major conferences including ICALP and SAGT.

• Causal Inference
• Machine Learning
• Data Science
• +2 more

Sofia Triantafillou is an active Assistant Professor at the University of Crete specializing in causal inference and machine learning, with research applications spanning healthcare, telecommunications, and environmental health. Her work bridges theoretical advances in causal discovery with real-world problem solving across diverse domains. Her educational background includes a PhD from the University of Crete completed in 2015. Dr. Triantafillou's research focuses on developing robust methods for causal discovery, treatment effect estimation, and data integration. Key contributions include foundational work on causal Markov boundaries, identifiability frameworks, and automated causal pipelines. She addresses critical challenges in heterogeneous data settings, particularly in healthcare applications like sepsis treatment optimization and environmental health impact analysis. Her interdisciplinary approach combines computer science, statistics, and domain-specific knowledge to advance both methodological rigor and practical utility. Analysis of her 2021-2025 publications reveals a sustained emphasis on automating causal discovery processes and handling complex real-world data scenarios. She has pioneered techniques for integrating observational and experimental data, with growing applications in biomedical informatics (e.g., sepsis heterogeneity analysis) and industrial domains (e.g., 5G network optimization). Her work demonstrates consistent innovation in making causal methods more accessible, reliable, and applicable across disciplines.

• Artificial Intelligence
• Automated Planning
• Machine Learning
• +7 more

Dimitris Vrakas is an Assistant Professor at the Department of Informatics, School of Informatics, Aristotle University of Thessaloniki (AUTh). He holds a PhD in Intelligent Planning Systems and has conducted post-doctoral research focusing on Planning for the Semantic Web. His professional experience includes roles as a Lecturer (per Greek law 407/80), Informatics Instructor in multiple educational institutions, and IT consultant for medium-sized enterprises through the Go-online Project. Education: Bachelor of Science (1995–1999): Informatics, Aristotle University of Thessaloniki PhD (2000–2004): Intelligent Planning Systems, Dept. of Informatics, AUTh Postdoctoral Research (2005–2007): Planning for the Semantic Web, AUTh Research Interests: Automated Planning, Heuristic Functions, Intelligent Autonomous Systems, Machine Learning Applications (Energy Management, NILM), Semantic Web Services, and Smart Environment Technologies. His work bridges theoretical AI advancements with practical implementations in energy systems and emergency response. Publications: Over 45 papers (including 15 journal articles) and 5 book chapters, with a focus on energy disaggregation, evacuation algorithms, and semantic web composition. His work demonstrates expertise in applying advanced techniques like GANs for data generation and reinforcement learning for adaptive planning. Awards: 2025 ACM SIGMOD Test-of-Time Award for contributions to time-series clustering Advising & Grants: Active in guiding PhD candidates (as per recent calls) and coordinating projects like the IRIS RISK PARADIGM for industrial safety. His work involves developing smart university platforms for energy monitoring and collaborating on EU-funded initiatives. Labs & Teams: Member of the Intelligent Systems Lab at AUTh, contributing to projects like the BOnSAI ontology for smart buildings and the IRISPortal for risk management. He also coordinates the Hellenic Artificial Intelligence Society and chairs conferences like SETN 2016.

• Biostatistics
• Experimental Designs
• Combinatorics
• +4 more

Karagiannis Vasilis is a researcher and educator at the Department of Mathematics, Aristotle University of Thessaloniki. He holds a PhD in Mathematics (2006) and a Mathematics degree (1998), both from Aristotle University of Thessaloniki. His current position is EDIP at the Department of Mathematics, a role he has held since 2017. He maintains extensive teaching activities across multiple university departments including Mathematics, Dentistry, and Physical Education & Sports. His educational background includes: PhD in Mathematics, Aristotle University of Thessaloniki (2006) Mathematics Degree, Aristotle University of Thessaloniki (1998) Karagiannis specializes in the application of mathematical and statistical methods to diverse fields. His research spans theoretical work in experimental design and graph theory to applied biostatistics in medical and dental contexts. His expertise in R and SPSS programming enables sophisticated data analysis across multiple disciplines. The interdisciplinary nature of his work is evident in collaborations with researchers in dentistry, cardiology, and aquaculture, demonstrating how statistical theory can solve practical problems in various scientific domains. His publication record shows a clear evolution from theoretical statistical design (2005-2008) toward increasingly applied medical and dental research (2010-2019). The most recent publications focus on dental applications, including periodontal surgery outcomes, dental fear assessment in children, and material science for dental prosthetics. This trajectory illustrates the practical implementation of his statistical expertise in clinical settings. Karagiannis has been involved in numerous research projects funded by ELKE (Aristotle University Research Committee), including the Master's Program in Networks and Complexity, the project "Applications of Mathematics in Industry and Business," and various dental and medical research initiatives. His work demonstrates consistent grant funding and collaborative research across disciplinary boundaries.

• Fair Allocation
• Mechanism Design
• Graph Sampling
• +3 more

George Amanatidis is an Assistant Professor in the Department of Informatics at the Athens University of Economics and Business (AUEB) since December 2024 and a Research Associate at the Archimedes Unit of the Athena Research Center since February 2023. His academic career spans multiple international institutions with progressive roles in theoretical computer science and algorithmic economics. His educational qualifications include: PhD in Computer Science (2017) from Athens University of Economics and Business with thesis "Design of algorithms and mechanisms for problems with limited—or no—payoffs" Diploma in Applied Mathematics from National Technical University of Athens Master of Science in Mathematics from Georgia Institute of Technology Dr. Amanatidis specializes in algorithmic problems at the intersection of Discrete Mathematics, Computer Science, and Economics. His research critically examines fair allocation of goods, mechanism design frameworks, and graph sampling methodologies, contributing to foundational advancements in computational social choice and resource distribution theory. His work bridges theoretical computer science with economic modeling to solve complex optimization problems under constraints. No scientific awards are documented in the provided information. While no student advisement details or research grants are specified in the source material, his career trajectory demonstrates sustained engagement with high-impact academic institutions including the University of Essex, University of Amsterdam, Sapienza University of Rome, and CWI Netherlands. His current research activities at the Archimedes Unit focus on algorithmic design and computational theory, leveraging interdisciplinary approaches to address challenges in economic modeling and discrete systems.

Panagiotis PapadimitriouView profile

Associate Professor

• Software-Defined Networking
• Network Function Virtualization
• Cloud Networking
• +6 more

Panagiotis Papadimitriou serves as an Associate Professor at the Department of Applied Informatics, University of Macedonia in Thessaloniki, where he leads the NetCloud research group. Previously, he held positions as Assistant Professor at Leibniz University Hanover's Institute of Communications Technology and as a Post-Doctoral Researcher at Lancaster University (UK) and Telecom SudParis (France), with additional research experience at the University of Cambridge. His research spans Internet architectures and technologies with emphasis on Network Function Virtualization (NFV), Software-Defined Networking (SDN), Time-Sensitive Networking (TSN), Internet-of-Things (IoT), and Edge Computing. His work includes ML-assisted NFV orchestration (SFC-graph embedding, transformation, and multi-domain partitioning), network slicing orchestration, programmable dataplanes with P4, deterministic networks, datacenter network fabrics, and edge computing. Notable research outcomes include distributed network processing architectures (MIDAS, DistNSE), multi-provider service mapping mechanisms (Nestor), open-source NFV orchestration platforms (TeNOR), and orchestration platforms for cross-slice communication (MESON). His recent publications show a strong focus on In-Band Network Telemetry, Service Function Chain optimization, Time-Sensitive Networking implementations, and cross-slice communication systems, demonstrating his leadership in network virtualization and edge computing research areas. His work consistently addresses practical implementation challenges while advancing theoretical foundations in network management. Scientific Recognition: Senior Member of IEEE Associate Editor of IEEE Transactions on Network and Service Management Counselor of the IEEE Student Branch at University of Macedonia As Principal Investigator of the Horizon Europe NEPHELE project and previous EU-funded projects (NECOS, T-NOVA, CONFINE), he has secured over 1M euro in research funding. He actively contributes to the academic community through conference organization roles including IEEE ICC NGNI 2025, IEEE ICIN 2024, and IFIP/IEEE CNSM 2022 as General Co-Chair. The NetCloud research group he leads maintains a dedicated edge computing facility used for both research and teaching, and is known for its commitment to open-source software and community service through academic network resources. His educational background includes a Ph.D. in Electrical and Computer Engineering from Democritus University of Thrace (2008), an M.Sc. in Information Technology from University of Nottingham (2001), and a B.Sc. in Computer Science from University of Crete (2000).