NEWS
Happy International Greek Language Day!
9 February 2025
Today, we celebrate the historical, cultural, and linguistic significance of the Greek language. While Standard Modern Greek often takes center stage, we at Archimedes - AI and Data Science Research Hub recognize the impressive diversity and great cultural significance of its numerous dialects. These dialects present both exciting opportunities and complex challenges for AI and Large Language Models (LLMs) because each one of them presents unique linguistic features and all of them are low resourced. That’s why we’re using cutting-edge AI to document, digitize, and analyze these invaluable linguistic treasures, ensuring their preservation and accessibility for generations to come.
Two Research Positions in Data Stream Management Systems & Big Data Management
7 February 2025
We are pleased to announce the availability of two research positions in data stream management systems and big data management, to be co-supervised by Assistant Professor Odysseas Papapetrou from the Eindhoven University of Technology (TU/e) in the Netherlands and Professor Minos Garofalakis from the Technical University of Crete in Greece.
Archimedes Shines Bright at NeurIPS 2024
3 January 2025
The NeurIPS 2024 conference featured a strong presence from the Archimedes Research Unit at Athena Research Center, showcasing 38 groundbreaking contributions across machine learning and optimization. Our researchers presented research ranging from game theory to graph meta networks, cementing their role as leaders in the AI research community. Below an overview of their impressive contributions:
Archimedes AI Researcher receives Best Paper Runner-Up at Discovery Science 2024
17 December 2024
Archimedes is proud to announce that John Pavlopoulos (Assistant Professor at Athens University of Economics and Business and Lead Researcher at Archimedes) latest research, "Revisiting Silhouette Aggregation", was recognized as Best Paper Runner Up at Discovery Science 2024 in Pisa. Prof. Pavlopoulos, in collaboration with A. Likas and G. Vardakas from the Department of Computer Science & Engineering of the University of Ioannina, uncovered a powerful yet overlooked method of evaluating clustering solutions using the Silhouette Coefficient—particularly advantageous for datasets with cluster imbalance.
