archimedes-Artificial Intelligence, Data Science, Algorithms-greece

 
Artificial Intelligence
 
Data Science
 
Algorithms

[Archimedes Seminar Series] Towards next-generation AI with neuro-inspired computing by Angeliki Pantazi (IBM)

Dates
2024-07-04 16:00 - 17:00
Venue
Artemidos 1 - Amphitheater

 

 
 
ArchimedesSeminar Series - Towards next-generation AI with neuro-inspired computing
Dr. Angeliki Pantazi (IBM Research – Zurich)
Seminar 04 07 24
 
Abstract
The recent advances in AI show that models only remotely inspired by biology can achieve impressive results on human-like tasks. These AI capabilities are achieved using the latest generations of Large Language Models (LLMs), enabled by their powerful transformer architecture. However, the operational principles of these systems have little similarity to the substantially more evolved network designs that the brain employs. Contrary to humans, the AI models operate with enormous energy and area consumption and their learning mechanism requires a large amount of data for training. A computational model inspired by the principles and mechanisms of biological systems is likely to provide more efficient innovative AI solutions due to its inherent conception idea. For example, the sparse neural activity, the neural coding strategies, the efficient neuronal dynamics, and the local plasticity mechanisms are potential key enablers for the astounding energy efficiency of the brain that can be integrated in AI systems. In this talk, I will provide an overview of our research on neuro-inspired models and learning algorithms that aim to address the sustainability concerns of current AI models. I will also showcase the efficiency of neuro-inspired computing concepts in several AI applications. Finally, I will present how neuro-inspired models could further leverage the acceleration provided by analog AI hardware.

Short Bio
Angeliki Pantazi is a Principal Research Staff Member and a Research Manager at the IBM Research – Zurich. She received her Diploma and Ph.D. degrees in Electrical Engineering and Computer Technology from the University of Patras, Greece. Since 2006, she is a Research Staff Member in IBM Research – Zurich, where she has contributed to several projects in the area of data storage systems. Currently, she leads the research on neuro-inspired computing in the Emerging Computing and Circuits group. She was named IBM Master Inventor in 2014 and became a senior member of the IEEE in 2015 and a Fellow of IFAC in 2019. She was a co-recipient of the 2009 IEEE Control Systems Technology Award, the 2009 IEEE Transactions on Control Systems Technology Outstanding Paper Award and the 2014 IFAC Industrial Achievement Award. In 2017, she received an IBM Corporate Award and the IEEE Control Systems Society Transition to Practice Award. She has published over 100 refereed articles and holds over 50 granted patents.


________________________________________________________________________________
Microsoft Teams Need help?
Meeting ID: 362 849 199 025
Passcode: 6piKyG
For organizers: Meeting options
 
 
________________________________________________________________________________
 
 

Vision

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

image
image

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

 

ARCHIMEDES IMPACT

Research

Education

HIGHLIGHTS

Academy of Athens
Greek National AI Team selected through PDTN, the Panhellenic AI Competition, co-organized by Archimedes, Athena Research Center
ERC Grant: Christos Papadimitriou will lead the NEAGT project (starting 2026) on strategic interactions and computational decision-making, opening new directions for algorithmic game theory
Archimedes Talks: Michael I. Jordan (Inria Paris; UC Berkeley) on “Nonnegative Supermartingales, Sequential Testing, and Statistical Contract Theory”, 10 February 2026
Archimedes Talks: Paul Goldberg (University of Oxford) on “Complexity of Unambiguous Problems in Σ₂ᴾ”, 4 February 2026
ERC Grant: Christos Tzamos leads the COMFORMAL project (launched 2025) on rigorous foundations for robust and efficient machine learning algorithms
Archimedes Talks: Mark Girolami (The Alan Turing Institute; University of Cambridge) on “Statistical Finite Element Methods”, 7 November 2025
Archimedes Talks: Mihalis Yannakakis (Columbia University) on “Computing a Fixed Point of Contraction Maps in Polynomial Queries”, 25 June 2025

Highlights will be added soon.

 

NEWS

 
Διαδικτυακά Μαθήματα ΠΔΤΝ 2026–2027 (GR/EN)

Διαδικτυακά Μαθήματα ΠΔΤΝ 2026–2027 (GR/EN)

9 November 2026

Τα Διαδικτυακά Μαθήματα του Πανελλήνιου Διαγωνισμού Τεχνητής Νοημοσύνης (ΠΔΤΝ) για το 2026–2027 ξεκινούν την Πέμπτη 12 Νοεμβρίου 2026, στις 15:00 (ώρα Αθήνας). Γνωρίστε τα Νευρωνικά Δίκτυα, την Επεξεργασία Φυσικής Γλώσσας και την Όραση Υπολογιστών μέσα από δωρεάν μαθήματα μέσω Zoom. Το κείμενο είναι διαθέσιμο στα ελληνικά και στα αγγλικά (English version below).

Archimedes at EMNLP 2026

Archimedes at EMNLP 2026

15 October 2026

Archimedes members will present seven papers at the Conference on Empirical Methods in Natural Language Processing (EMNLP 2026), one of the leading international conferences in natural language processing, taking place in Budapest, Hungary, from 24 to 29 October 2026: three papers in the Findings of EMNLP, one paper in the EMNLP Industry Track, and three papers at EMNLP workshops.

More news items here
 
 

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.

Greece 2.0 – Funded by the European Union – NextGenerationEU