Eastern European Machine Learning summer school (in-person), Novi Sad, Serbia, 15-20 July 2024 -- DEADLINE March 29
Viorica Patraucean
Call for Applications (apologies for crossposting)
Eastern European Machine Learning summer school (in-person)
July 15-20, 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
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.
Travel grants
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, 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.
Organizers
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
contact at eeml.eu
Follow us on X/Twitter https://twitter.com/EEMLcommunity