[agents] First Inria-DFKI European Summer School on AI (IDAI 2021), Trustworthy AI and AI for Medicine, July 20-23, 2021- Saclay, France

[angelica BIARD]

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*First Inria-DFKI European Summer School on AI (IDAI 2021)*

*                Trustworthy AI* and *AI for Medicine*
*                              Saclay, France*
*                               July 20-23, 2021*
*                         https://idessai.inria.fr/
<https://idessai.inria.fr/>*

*               Registration deadline: April 19, 2021*
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IDAI 2021 inaugurates a series of yearly Summer Schools organized by the
two renowned German and French AI institutes, DFKI and Inria. It stands out
from the crowd of offerings for AI students in several respects:

   - We ensure a good balance in the number of participants and
   instructors: participants will have the opportunity to join a community of
   like-minded people and, at the same time, they will be in close contact
   with the experts.
   - Our program features a line-up of courses focused on two themes,
   Trustworthy AI and AI for Medicine, which are at the forefront of
   socio-economic issues related to AI.
   - On top of the latest methodological advances and the shared vision of
   the future that both organizing institutes have to offer, IDAI 2021 will be
   practically oriented. We will achieve this through hands-on courses and the
   involvement of industry practitioners and innovators.
   - Participants will be offered to the opportunity to present their work
   to each other in dedicated poster/demo sessions.

Trustworthy AI and AI for Medicine will take place in two parallel tracks.
There will be plenty of opportunities to exchange between these two tracks
at coffee breaks, meals and social events, as well as through joint
cross-track sessions.

*TARGETED AUDIENCE*

IDAI 2021 was designed for PhD students in all areas of AI, including
machine learning, knowledge representation and reasoning, search and
optimisation, planning and scheduling, multi-agent systems, natural
language processing, robotics, computer vision, and other areas. PhD
students in other fields, MSc students, postdocs, and researchers in
industry are also welcome.

*VENUE*

IDAI 2021 is currently planned as a fully in-person event, which will take
place at the Inria Saclay Île-de-France research center, close to Paris.
Remote attendance will not be possible.

In case the sanitary conditions do not allow an in-person event, IDAI 2021
will take place as a fully virtual event at the same dates instead. We are
closely monitoring the situation and will strive to make this decision as
early as possible.

*CONFIRMED KEYNOTES AND SPEAKERS*

Cross-track keynotes:


   - Mihaela van der Schaar (University of Cambridge) - Why medicine is
   creating exciting new frontiers for machine learning and AI
   - Joanna Bryson (Hertie School) - AI ethics

Trustworthy AI track (to be completed):

   - Serge Abiteboul (Inria) - Responsible data analysis algorithms: a
   realistic goal?
   - Simon Burton (Fraunhofer IKS) - Safety, complexity, AI and automated
   driving - holistic perspectives on safety assurance
   - Michèle Sebag (CNRS - LISN) - Why and how learning causal models
   - Patrick Gallinari (Sorbonne University and Criteo AI Lab) - Deep
   learning meets numerical modeling
   - Christian Müller (DFKI) - Explaining AI with narratives
   - Catuscia Palamidessi (Inria) and Miguel Couceiro (University of
   Lorraine) - Addressing algorithmic fairness through metrics and explanations
   - Guillaume Charpiat (Inria), Zakaria Chihani (CEA), and Julien
   Girard-Satabin (CEA) - Formal verification of deep neural networks: theory
   and practice
   - Hatem Hajri (IRT SystemX) - Adversarial examples and robustness of
   neural networks

AI for Medicine track (to be completed):

   - Gerd Reis (DFKI) - AI in Medicine - An engineering perspective
   - Marco Lorenzi (Inria) - Federated learning methods and frameworks for
   collaborative data analysis
   - Gaël Varoquaux (Inria) - Dirty data science: machine learning on
   non-curated data
   - Thomas Moreau and Demian Wassermann (Inria) - Introduction to
   neuroimaging with Python
   - Francesca Galassi (Inria) and Rutger Fick (TRIBVN Healthcare) - Domain
   adaptation for the segmentation of multiple sclerosis lesions in brain MRI.
   - Tim Dahmen (DFKI) - Bio-mechanical simulation for individualized
   implants and prosthetics
   - Elmar Nöth (Friedrich-Alexander-University Erlangen-Nuremberg) -
   Automatic analysis of pathologic speech – from diagnosis to therapy
   - Pierre Zweigenbaum (CNRS - LIMSI) - NLP for medical applications

Open discussion with industry (to be completed):

   - Juliette Mattioli (Thales) and Frédéric Jurie (Safran) - Industry use
   cases involving trusted AI
   - Boris Dimitrov (Check Point Cardio) - Real-time online patient
   tele-monitoring


*FEES AND REGISTRATION*

Our fees are all-inclusive and may optionally include accomodation.

For more details and to register, see https://idessai.inria.fr/registration/
(deadline: April 19).

To ensure a good balance in the number of participants and instructors and
maximize the chances of interaction, the number of attendees is limited to
50 per track. Applicants will be selected on the grounds of diversity and
benefit gained from attending the selected track.

*ORGANIZERS*

Co-organized by: Inria, DFKI, Dataia, IRT SystemX
Contact us: idessai-contact at inria.fr.
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