archimedes-Artificial Intelligence, Data Science, Algorithms-greece

 
Artificial Intelligence
 
Data Science
 
Algorithms

[Archimedes Talks Series]Advanced Data Mining and Search Techniques for Natural Spatio- Temporal Systems - Dr. Matthias Renz

Dates
2025-01-17 13:00 - 15:00
Venue
Artemidos 1 - Amphitheater

Title: Advanced Data Mining and Search Techniques for Natural Spatio-Temporal Systems


Speaker: Professor Matthias Renz (Christian-Albrechts-Universität zu Kiel (CAU, University of Kiel))



Abstract: The study of natural spatio-temporal systems—such as climate patterns, environmental phenomena, and dynamic processes in the ocean—presents unique challenges due to the complexity and dynamic nature of data. Advanced data mining and search techniques play a critical role in analyzing and interpreting these systems, enabling the extraction of meaningful patterns and knowledge from large, complex datasets. In this talk, I will highlight some of our recent studies in data mining and query processing we have conducted in a number of interdisciplinary collaborative projects. This includes water-mass connectivity pattern mining, spatio-temporal correlation clustering and predictive modeling, tailored to address the complexities of spatio-temporal data to understand complex systems in ocean dynamics. We also delve into the development of search algorithms for CO2 minimizing ship routing in large-scale, dynamic, multi-attribute ocean data, focusing on optimizing performance and scalability. This talk underpins the importance of interdisciplinary strategies in advancing the field and fostering deeper insights into the behavior of natural systems over time and space.

 

 

Short bio: Dr. Matthias Renz is Professor at the Department of Computer Science at Christian-Albrechts-Universität zu Kiel (CAU, University of Kiel). Before he joined CAU in summer 2018, Dr. Renz was Associate Professor in the Computational and Data Science Department at George Mason University (GMU), Fairfax, VA, USA. He received his Ph.D. in Computer Science at Ludwig-Maximilians-Universität München in 2006, where he served as lecturer after finishing his habilitation (venia legendi) 2011. Dr. Renz’s main research interest is Data Science with focus on scalable methods for searching and mining in very large, heterogeneous, dynamic and potentially uncertain data. He is substantially involved in a number of interdisciplinary collaborative research projects including the Gaia-X initiative Marispace-X, NFDI4Objects, MarData Helmholtz Information & Data Science Academy, Data Campus, ArcWorlds among others and is head of the CAU Center for Interdisciplinary Data Science. He gave several invited tutorials, seminars, and keynotes on international conferences and in 2016 his work received the 10-Year Best Paper Award at the International Conference on Database Systems for Advanced Applications. He has been program committee member for several international conferences and workshops, including SIGMOD, VLDB, ICDE, and KDD. Furthermore, Dr. Renz co-organized and chaired several international conferences and workshops, including SSTD, ACM SIGSPATIAL, DASFAA, ACM SIGSPATIAL QUeST, ACM SIGMOD GeoRich, and ACM SIGSPATIAL LocalRec.

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Vision

To position Greece as a leading player in AI and Data Science

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Mission

To build an AI Excellence Hub in Greece where the international research community can connect, groundbreaking ideas can thrive, and the next generation of scientists emerges, shaping a brighter future for Greece and the world

 

Welcome to ARCHIMEDES, a vibrant research hub connecting the global AI and Data Science research community fostering groundbreaking research in Greece and beyond. Its dedicated core team, comprising lead researchers, affiliated researchers, Post-Docs, PhDs and interns, is committed to advancing basic and applied research in Artificial Intelligence and its supporting disciplines, including Algorithms, Statistics, Learning Theory, and Game Theory organized around 8 core research areas. By collaborating with Greek and Foreign Universities and Research Institutes, ARCHIMEDES disseminates its research findings fostering knowledge exchange and providing enriching opportunities for students. Leveraging AI to address real-world challenges, ARCHIMEDES promotes innovation within the Greek ecosystem and extends its societal impact. Established in January 2022, as a research unit of the Athena Research Center with support from the Committee Greece 2021, ARCHIMEDES is funded for its first four years by the EU Recovery and Resilience Facility (RRF).

 
 

NEWS

 
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Archimedes and the Biomedical Research Foundation Share Latest Findings in AI and Medicine

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Archimedes Reaches Milestone of 200 Publications

Archimedes Reaches Milestone of 200 Publications

Archimedes is proud to announce that its researchers have published over 200 scientific publications in top-tier conferences (NeurIPS, ICLR, ICML) and journals.Archimedes maintains a vibrant scientific community of over 130 researchers, including more than 60 senior researchers (faculty members from Greece and abroad), 12 postdoctoral fellows, and 55 PhD students, along with over 20 undergraduate interns from various disciplines.

Happy International Greek Language Day!

Happy International Greek Language Day!

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

Two Research Positions in Data Stream Management Systems & Big Data Management

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.

 
 

The project “ARCHIMEDES Unit: Research in Artificial Intelligence, Data Science and Algorithms” with code OPS 5154714 is implemented by the National Recovery and Resilience Plan “Greece 2.0” and is funded by the European Union – NextGenerationEU.

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