[visionlist] Eastern European Machine Learning summer school (in-person), Novi Sad, Serbia, 10-15 July 2024 -- APPLICATIONS OPEN

[Viorica Patraucean]

Call for Participation (apologies for crossposting)

Eastern European Machine Learning summer school (in-person)
July 10-15, 2024, Novi Sad, Serbia
Web: https://www.eeml.eu
Email: contact at eeml.eu

Applications are open! Details about the application process
https://www.eeml.eu/application.
Application period closes: March 29, 2024
Notification of acceptance: Early May, 2024


Registration fees and travel grants

Students (PhD, master, undergrad, high school): 100 EUR
Postdoc / faculty: 150 EUR
Industry: 400 EUR
The registration fees include catering for the entire week (except 2
dinners). The fees do not include travel and accommodation.
A number of need-based travel grants are available for accepted
participants who cannot afford to attend the school. They cover fully or
partially the costs of attending the school (registration fee, travel
costs, accommodation).


Motivation and description

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

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
world.

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 Basics of Machine Learning,
Multimodal learning, Natural Language Processing, Computer Vision, Advanced
Deep Learning architectures, Generative models, AI for Science, and more.


List of confirmed speakers

Aleksandra Faust, Google DeepMind
Alfredo Canziani, New York University
Chris Dyer, Google DeepMind
Doina Precup, McGill University & Google DeepMind
Jovana Mitrović, Google DeepMind
Kyunghyun Cho, New York University & Genentech
Martin Vechev, ETH Zürich & INSAIT
Michael Bronstein, University of Oxford
Mihaela van der Schaar, University of Cambridge
Nenad Tomašev, Google DeepMind
Razvan Pascanu, Google DeepMind
Sander Dieleman, Google DeepMind
Velibor Ilić, Institute for AI Research and Development of Serbia
Vladimir Gligorijević, Genentech
Yee Whye Teh, University of Oxford & Google DeepMind
Anastasija Ilić, Google DeepMind
Andreea Deac, Mila & Université de Montréal
Cristian Bodnar, Microsoft Research
Ioana Bica, Google DeepMind
Iulia Duță, University of Cambridge
Matko Bošnjak, Google DeepMind
Ognjen Milinković, University of Belgrade
Petar Veličković, Google DeepMind & University of Cambridge


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.


Organisers

Doina Precup, McGill University & Google DeepMind
Razvan Pascanu, Google DeepMind
Viorica Patraucean, Google DeepMind
Branislav Kisačanin, NVIDIA & Institute for AI Research and Development of
Serbia
Dubravko Ćulibrk, Institute for AI Research and Development of Serbia
Matko Bošnjak, Google DeepMind
Nemanja Rakićević, Google DeepMind
Petar Veličković, Google DeepMind & University of Cambridge
Gabriel Marchidan, IasiAI & Feel IT Services


Main partner

The Institute for Artificial Intelligence Research and Development of Serbia


More info

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