Subject: [T2TRG] Call for participation to the Summer School on AI Technologies for Trust, Interoperability and Autonomy in Industry 4.0

From: "Charpenay, Victor" <[email-masked]>
Date: Wed, 10 Jun 2020 16:29:41 +0000

Dear all,

we might have already met during one of the WISHI workshops: I am a member of the W3C Web of Things (WoT) group. I am especially looking at semantic interoperability aspects on WoT and this is what this call for participation is mostly about. We will hold a summer school on AI for Industry 4.0 where we will show how to use semantically annotated Thing Descriptions to control a production line. We are also pleased to have Matthias Kovatsch as a keynote speaker.

Because of the Covid pandemic, remote participation will be favored but if local policies allow, facilities in France (Saint-Étienne) and Germany (Nuremberg) will also be available. Participants may attend lectures only or participate in hands-on sessions and a hackathon.

We are looking forward to your registration!

Best,

Victor Charpenay

========================== CALL FOR PARTICIPATION =================

Call for participation to the Summer School on

AI Technologies for Trust, Interoperability and Autonomy in Industry 4.0

27th to 31st of July 2020

Saint-Étienne, France

http://ci.mines-stetienne.fr/ai4industry

We invite PhD students and early stage researchers from academia or industry to apply to the summer school we organise 27th to 31st of July 2020 on the topic of AI Technologies for Trust, Interoperability and Autonomy in Industry 4.0, in a collaboration between French and German institutions.

This summer school will have a unique format where participants will be intensively working on concrete industry use cases: we plan to dedicate most of the summer school to hands-on sessions while providing an overview of the theoretical foundations underlying the practical work.

Topics

=====

The summer school will address various aspects of AI in Industry 4.0 (or Industry of the future) with a particular focus on:

* knowledge graphs

* the web of things

* decentralised AI

* responsible AI

Each of these topics will be covered in lectures and practical sessions, then applied to the industry use cases to devise potential solutions.

Expected candidates and benefits

========================

We welcome applications from PhD students and early stage researchers that have already some knowledge in at least one of the topics above, but want to broaden their perspective and have a chance to apply their skills on real problems. The benefits for the participants are:

* learn or improve knowledge in several areas of Artificial Intelligence

* get in touch with high profile researchers and professors

* build a network with other talented young researchers

* hack together plausible solutions to stimulating real-life problems

* have the opportunity to further develop your approach in collaboration with industry partners

How to apply

=========

We will limit the number of participants to 30 people. Therefore, in case we receive too many applications, we will select attendees based on their résumés and cover letter. Please use the form at https://easychair.org/conferences/?conf=ai4industry to submit them in a single file.

The registration fees are 300 € including meals, coffee breaks, lunches and special event dinner and accommodation at the student residence of Mines Saint-Étienne, for those participating on site. Reduced fees for remote participants will be 150 €. Thanks to our sponsorships, some fees may be waived. If you need a fee waiver, please send us a motivation letter, and we will consider your request in the limit of our budget.

Dates

====

* Opening of application for participation: 27 February 2020
* End of application: 15 May 2020
* Notification of acceptance: 20 May 2020
* Deadline for registration: 15 June 2020
* Summer school: 27-31 July 2020

Contact and organising institutions

==========================

Main contact: [email-masked]

Mines de Saint-Étienne

Université Jean Monnet Saint-Étienne

Friedrich-Alexander-Universität Erlangen-Nürnberg

Fraunhofer IIS-SCS