ΑΙhub.org
 

CLAIRE COVID-19 Initiative Video Series: Meet the Team Leaders – Marco Aldinucci

Marco Aldinucci

In this penultimate interview in the series of Meet the Team Leaders from the CLAIRE COVID-19 Initiative, we hear from Marco Aldinucci, Computer Science Department, University of Torino.

AIhub focus issue on good health and well-being

Marco Aldinucci is the leader of the Image analysis (CT scans, X-ray) topic group in the CLAIRE COVID-19 Initiative. In this interview you can find out about the group he leads, how AI methods can be used to help analyse medical images, and the challenges the team faced.

To find out more about this series, read our recent post and watch the first video with Emanuela Girardi. You can also watch interviews with Davide Bacciu, Ann Nowé, Jose Sousa, Marco Maratea and Manlio De Domenico.

You may also be interested in the article Marco wrote for AIhub which details the work of the topic group and describes how high-performance computing and AI can combine to good effect.

You can watch the series on the CLAIRE YouTube channel.

Find out more about the CLAIRE COVID-19 task force here.
You can contact the taskforce by email here.



tags: , ,


CLAIRE (Confederation of Laboratories for AI Research in Europe)

            AUAI is supported by:



Subscribe to AIhub newsletter on substack



Related posts :

#ICML2026 social media round-up

  17 Jul 2026
We take a look at what the participants got up to in Seoul.

François Pachet on music generation with AI

  16 Jul 2026
“The day I hear a song of the quality of the Beatles, I will say: ‘Okay, we are done’. And I’ve never heard anything like that. Never.”

AI for science – talk recordings now available to watch

  15 Jul 2026
Watch the invited talks from the day on YouTube.

AAAI presidential panel – factuality and trustworthiness

  14 Jul 2026
Watch the latest panel discussion in the series based on the Future of AI research report from AAAI.

The secret to human ‘brilliance’ that AI just can’t match

  13 Jul 2026
New research reveals how people learn social conventions with minimal data – and why that sets us apart from LLMs.

Pre-training isn’t bitter enough

  10 Jul 2026
Given an unlabeled data stream, and a small set of verifiable downstream examples, can we use those examples during continued pre-training?

Interview with Thi Kieu Khanh Ho: Time-series anomaly detection

  09 Jul 2026
How can we teach AI systems to recognize when something unusual or abnormal is happening in complex, real-world data streams, without relying on large amounts of labeled examples?

#RoboCup2026 social media round-up

  08 Jul 2026
Find out what the teams got up to at this year's RoboCup extravaganza in Incheon.



AUAI is supported by:







Subscribe to AIhub newsletter on substack




 















©2026.05 - Association for the Understanding of Artificial Intelligence