[visionlist] Eastern European Machine Learning summer school (in-person) -- Application deadline March 31

Viorica Patraucean vpatrauc at gmail.com
Fri Mar 10 12:17:07 -04 2023

Call for Participation (apologies for crossposting)

Eastern European Machine Learning summer school (in-person)
July 9-16, 2023, Kosice, Slovakia
Web: https://www.eeml.eu
Email: contact at eeml.eu

Applications are open! Details about the application process
Application closes: March 31, 2023
Notification of acceptance: End of April 2023

Registration fees

Students (PhD, master, undergrad, high school): 100 EUR
Postdoc / faculty: 150 EUR
Industry: 400 EUR

Motivation and description

EEML is a machine learning summer school that aims to democratise access to
education and research in AI, and improve diversity in the field. The
summer school is held yearly in Eastern Europe – this year it will be held
in person in Kosice, Slovakia.

By bringing together high quality lecturers and participants from all over
the world, we strive to enable communication and networking among the
Eastern European AI communities as well as with researchers from around the

The school is open to participants from all over the world. The selection
process has equal opportunities and diversity at heart, and will assess
interest and knowledge in machine learning.

We encourage applications from candidates at all levels of expertise in
Machine Learning (beginner, intermediate, advanced). Details about the
application process are available online at https://www.eeml.eu/application.

The programme consists of lectures, hands-on practical sessions, panel
discussions, and more. Topics covered include Reinforcement Learning,
Natural Language Processing, Computer Vision, Theory of Deep Learning,
Ethics, Robotics, and more.

List of confirmed speakers (more coming soon)

Ankur Handa, Nvidia
Doina Precup, McGill University & DeepMind
El Mahdi El Mhamdi, École Polytechnique Paris
Michal Valko, DeepMind & Inria
Peter Richtárik, KAUST
Razvan Pascanu, DeepMind

Poster session

Participants will have the opportunity to present their research work and
interests during poster sessions. The work described does not have to be
novel. For example, participants can present their experience of
reproducing published work.


Doina Precup, McGill University & DeepMind
Razvan Pascanu, DeepMind
Viorica Patraucean, DeepMind
Andrea Lee, ESET
Katarina Mayer, ESET
Michal Valko, DeepMind & Inria

Main partner




Local partners

Technical University of Kosice

More info

contact at eeml.eu
Follow us on Twitter https://twitter.com/EEMLcommunity
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