archimedes-Artificial Intelligence, Data Science, Algorithms-greece

 
Artificial Intelligence
 
Data Science
 
Algorithms

[Archimedes Seminar Series] Sparsity, modularity, and structural plasticity in deep neural networks

Dates
2024-06-10 11:00 - 12:00
Venue
Microsoft Teams Meeting; Artemidos 1 - Amphitheater

Archimedes Seminar Series: Sparsity, modularity, and structural plasticity in deep neural networks

Prof. Constantine Dovrolis

Professor at the School of Computer Science at the Georgia Institute of Technology (Georgia Tech) and Director of the center for Computational Science and Technology(CaSToRC) at The Cyprus Institute(Cyl)

 
Seminar 10062411am
 
Abstract: There is a growing overlap between Machine Learning, Neuroscience, and Network Theory. These three disciplines create a fertile inter-disciplinary cycle: a) inspiration from neuroscience leads to novel machine learning models and deep neural networks in particular, b) these networks can be better understood and designed using network theory, and c) machine learning and network theory provide new modeling tools to understand the brain’s structure and function, closing the cycle. In this talk, we will “tour” this cross-disciplinary research agenda by focusing on three recent works: a) the design of sparse neural networks that can learn fast and generalize well (PHEW, ICML 2021), b) the use of structural adaptation for continual learning (NISPA, ICML 2022), and c) the emergence of hierarchically modularity in neural networks (Neural Sculpting, NeurIPS 2023).
 
Bio: Dr. Constantine Dovrolis is the Director of the center for Computational Science and Technology (CaSToRC) at The Cyprus Institute (CyI) as of 1/1/2023. He is also a Professor at the School of Computer Science at the Georgia Institute of Technology (Georgia Tech). He is a graduate of the Technical University of Crete (Engr.Dipl. 1995), University of Rochester (M.S. 1996), and University of Wisconsin-Madison (Ph.D. 2000).

His research is highly inter-disciplinary, combining Network Theory, Data Mining and Machine Learning. Together with his collaborators and students, they have published in a wide range of scientific disciplines, including climate science, biology, and neuroscience. More recently, his group has been focusing on neuro-inspired architectures for machine learning based on what is currently known about the structure and function of brain networks.

According to Google Scholar, his publications have received more than 15,000 citations with an h-index of 56. His research has been sponsored by US agencies such as NSF, NIH, DOE, DARPA, and by companies such as Google, Microsoft and Cisco. He has published at diverse peer-reviewed conference and journals such as the International Conference on Machine Learning (ICML), the ACM SIGKDD conference, PLOS Computational Biology, Network Neuroscience, Climate Dynamics, the Journal of Computational Social Networks, and others. 

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Meeting ID: 336 122 410 964

Passcode: KDhgMB
 
 
 
 

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

 
Archimedes Workshop on Dialect NLP

Archimedes Workshop on Dialect NLP

Upcoming workshop on Dialect NLP on “Standardization and Variation for Dialect Varieties with Universal Dependencies as an Application Framework” coming up. We are excited to announce that the Dialect NLP team at Archimedes, Athena Research Center, Greece, is organizing a workshop in collaboration with the MaiNLP Research Lab at Ludwig Maximilian University (LMU) of Munich. Workshop details:Workshop info: UniDive WG1 Workshop on Dialect Varieties Dates: September 5–6, 2025 Location: LMU Munich Funded by: UniDive – Universality, Diversity and Idiosyncrasy in Language Technology Archimedes: Dialect NLP and Linguistic Diversity At Archimedes, our Dialect NLP team focuses on the intersection of AI and linguistic diversity, with an emphasis on under-resourced and endangered language varieties, both Greek and non-Greek. Our research includes:   • Dialectal speech-to-text and morphosyntactic modeling  • Dialect-to-standard normalization for Greek varieties   • Intra-dialectal variation analysis   • A critical perspective on annotation frameworks like Universal Dependencies (UD), especially when applied to non-standard or endangered varieties Our resources cover:   • Standard Modern Greek: GUD Treebank   • Greek dialects: Cretan, Messinian, Lesbian, Cypriot, Griko/Greko, Aperathitika   • Non-Greek varieties spoken in Greece: Pomak, Arvanitika All datasets, models, and tools we develop are freely available to the research community. About Our Collaborators at MaiNLP (LMU Munich) The MaiNLP Research Lab at Ludwig-Maximilians-Universität Munich conducts research in Natural Language Processing, combining computer science, linguistics, and cognitive science. Their focus is on human-facing NLP: developing models that are robust to variation, fair, and reflective of human annotation diversity. MaiNLP is also leading the ERC Consolidator Grant project DIALECT, which explores natural language understanding for non-standard languages and dialects—making them an ideal partner in our shared mission to design NLP systems that work for all language varieties. Workshop Goals This workshop will:   • Document current practices in dialectal UD treebanks (e.g., orthographic/phonological variation, lemmatization, interference)   • Identify gaps in annotation and processing across dialects   • Develop shared methodologies for handling variation, improving consistency, and enabling knowledge transfer   • Foster community engagement with researchers working on under-resourced dialects and less-studied language families   • Ground discussions in theoretical insights from Plank (2016): What to do about non-standard language in NLP It is an opportunity to reflect on how annotation frameworks and tools serve—or fall short of serving— dialectal and endangered varieties, and how AI can support documentation, analysis, and preservation of linguistic diversity. We look forward to sharing our findings and engaging with colleagues working on inclusive, culturally informed, and variation-aware NLP. Stay tuned for more updates!

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

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

Archimedes and the Biomedical Research Foundation of the Academy of Athens successfully hosted a special collaborative session at the Panhellenic Working Group Seminars of the Hellenic Society of Cardiology. This session focused on innovative applications of artificial intelligence in medicine, with a particular emphasis on advancements in cardiology. Held on Friday, February 7, 2025, in Room MC2 of the Megaron Athens International Conference Centre, the event brought together leading experts to explore how artificial intelligence is transforming cardiovascular medicine.

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.

 
 

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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