On-site registration
SCOPE
DeepLearn 2024 will be a research training event with a global scope aiming at updating participants on the most recent advances in the critical and fast developing area of deep learning.
ADDRESSED TO
Graduate students, postgraduate students and industry practitioners will be typical profiles of participants. However, there are no formal pre-requisites for attendance in terms of academic degrees, so people less or more advanced in their career will be welcome as well.
VENUE
DeepLearn 2024 will take place in Porto, the second largest city in Portugal, recognized by UNESCO in 1996 as a World Heritage Site.
STRUCTURE
- 3 courses will run in parallel during the whole event.
- Participants will be able to freely choose the courses they wish to attend as well as to move from one to another.
- All lectures will be videorecorded. Participants will be able to watch them again for 45 days after the event.
- An open session will give participants the opportunity to present their own work in progress in 5 minutes. Also companies will be able to present their technical developments for 10 minutes.
- This year’s edition of the school will schedule hackathons, where participants will work in teams to tackle several machine learning challenges.
Full live online participation will be possible. The organizers highlight, however, the importance of face to face interaction and networking in this kind of research training event.
Special Sessions
OPEN SESSION
An open session will collect 5-minute voluntary oral presentations of work in progress by participants.
They should submit a half-page abstract containing the title, authors, and summary of the research to david@irdta.eu by July 7, 2024.
INDUSTRIAL SESSION
A session will be devoted to 10-minute demonstrations of practical applications of deep learning in industry.
Companies interested in contributing are welcome to submit a 1-page abstract containing the program of the demonstration and the logistics needed. People in charge of the demonstration must register for the event.
Expressions of interest have to be submitted to david@irdta.eu by July 7, 2024.
HACKATHONS
Hackathons will take place, where participants will work in teams to tackle several machine learning challenges. They will be coordinated by Professor Sergei V. Gleyzer. The challenges will be released 2 weeks before the beginning of the school. A jury will judge the submissions and the winners of each challenge will be announced. The winning teams will receive a monetary prize and the runners-up will get a certificate.
The facilitators who will help during the development of the work include: Emanuele Usai, Axel Newton Buchot Perraguin (general), Marco Knipfer, Eric Reinhardt (Higgs, particle images, NMR), Pranath Reddy (gravitational lensing), Jason Patrick Terry (exoplanets), Tom Magorsch, Gopal Dahale (QML), Xabier Granja, Shashank Shekhar Singh, Harrison Meadows, Utsav Rai, Yukinori Yamamoto, Arsh Khan (RenAIssance), Krishna Chaitanya Rao Kathala (assessment).
More details here.
List of winners and runners-up here.
EMPLOYERS
Organizations searching for personnel well skilled in deep learning will have a space reserved for one-to-one contacts.
It is recommended to produce a 1-page .pdf leaflet with a brief description of the organization and the profiles looked for to be circulated among the participants prior to the event. People in charge of the search must register for the event.
Expressions of interest have to be submitted to david@irdta.eu by July 7, 2024.
Sponsors
Companies/institutions/organizations willing to be sponsors of the event can download the sponsorship leaflet from sponsoring page
ORGANIZING COMMITTEE
- José Paulo Marques dos Santos (Maia, local chair)
- Carlos Martín-Vide (Tarragona, program chair)
- Sara Morales (Brussels)
- José Luís Reis (Maia)
- Luís Paulo Reis (Porto)
- David Silva (London, organization chair)
CERTIFICATE
- A certificate of successful participation in the event will be delivered indicating the number of hours of lectures. This should be sufficient for those participants who plan to request ECTS recognition from their home university.
Acknowledgments
