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7th INTERNATIONAL SCHOOL ON DEEP LEARNING
DeepLearn 2022 Autumn
Luleå, Sweden
October 17-21, 2022
https://irdta.eu/deeplearn/2022au/
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Co-organized by:
Luleå University of Technology
EISLAB Machine Learning
Institute for Research Development, Training and Advice – IRDTA
Brussels/London
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Regular registration: October 14, 2022
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SCOPE:
DeepLearn 2022 Autumn 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. Previous events were held in Bilbao,
Genova, Warsaw, Las Palmas de Gran Canaria, Guimarães and Las Palmas de Gran
Canaria.
Deep learning is a branch of artificial intelligence covering a spectrum of
current frontier research and industrial innovation that provides more
efficient algorithms to deal with large-scale data in a huge variety of
environments: computer vision, neurosciences, speech recognition, language
processing, human-computer interaction, drug discovery, health informatics,
medical image analysis, recommender systems, advertising, fraud detection,
robotics, games, finance, biotechnology, physics experiments, biometrics,
communications, climate sciences, bioinformatics, etc. etc. Renowned academics
and industry pioneers will lecture and share their views with the audience.
Most deep learning subareas will be displayed, and main challenges identified
through 18 four-hour and a half courses and 2 keynote lectures, which will
tackle the most active and promising topics. The organizers are convinced that
outstanding speakers will attract the brightest and most motivated students.
Face to face interaction and networking will be main ingredients of the event.
It will be also possible to fully participate in vivo remotely.
An open session will give participants the opportunity to present their own
work in progress in 5 minutes. Moreover, there will be two special sessions
with industrial and recruitment profiles.
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. Since there will be a variety of levels,
specific knowledge background may be assumed for some of the courses. Overall,
DeepLearn 2022 Autumn is addressed to students, researchers and practitioners
who want to keep themselves updated about recent developments and future
trends. All will surely find it fruitful to listen to and discuss with major
researchers, industry leaders and innovators.
VENUE:
DeepLearn 2022 Autumn will take place in Luleå, on the coast of northern
Sweden, hosting a large steel industry and the northernmost university in the
country.
The venue will be:
Luleå University of Technology
https://www.ltu.se/?l=en
STRUCTURE:
2-3 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.
Full live online participation will be possible. However, the organizers
highlight the importance of face to face interaction and networking in this
kind of research training event.
KEYNOTE SPEAKERS:
Tommaso Dorigo (Italian National Institute for Nuclear Physics),
Deep-Learning-Optimized Design of Experiments: Challenges and Opportunities
Elaine O. Nsoesie (Boston University), AI and Health Equity
PROFESSORS AND COURSES:
Sean Benson (Netherlands Cancer Institute), [intermediate] Deep Learning for a
Better Understanding of Cancer
Thomas Breuel (Nvidia), [intermediate/advanced] Large Scale Deep Learning and
Self-Supervision in Vision and NLP
Hao Chen (Hong Kong University of Science and Technology),
[introductory/intermediate] Label-Efficient Deep Learning for Medical Image
Analysis [virtual]
Jianlin Cheng (University of Missouri), [introductory/intermediate] Deep
Learning for Bioinformatics
Nadya Chernyavskaya (European Organization for Nuclear Research),
[intermediate] Graph Networks for Scientific Applications with Examples from
Particle Physics [virtual]
Efstratios Gavves (University of Amsterdam), [advanced] Advanced Deep Learning
[virtual]
Quanquan Gu (University of California Los Angeles), [intermediate/advanced]
Benign Overfitting in Machine Learning: From Linear Models to Neural Networks
Jiawei Han (University of Illinois Urbana-Champaign), [advanced] Text Mining
and Deep Learning: Exploring the Power of Pretrained Language Models
Awni Hannun (Zoom), [intermediate] An Introduction to Speech Recognition and
Weighted Finite-State Automata [virtual]
Tin Kam Ho (IBM Thomas J. Watson Research Center), [introductory/intermediate]
Deep Learning Applications in Natural Language Understanding
Timothy Hospedales (University of Edinburgh), [intermediate/advanced] Deep
Meta-Learning
Shih-Chieh Hsu (University of Washington), [intermediate/advanced] Real-Time
Artificial Intelligence for Science and Engineering
Tatiana Likhomanenko (Apple), [intermediate/advanced] Self-, Weakly-,
Semi-Supervised Learning in Speech Recognition [virtual]
Othmane Rifki (Spectrum Labs), [introductory/advanced] Speech and Language
Processing in Modern Applications
Mayank Vatsa (Indian Institute of Technology Jodhpur),
[introductory/intermediate] Small Sample Size Deep Learning [virtual]
Yao Wang (New York University), [introductory/intermediate] Deep Learning for
Computer Vision
Zichen Wang (Amazon Web Services), [introductory/intermediate] Graph Machine
Learning for Healthcare and Life Sciences
Alper Yilmaz (Ohio State University), [introductory/intermediate] Deep Learning
and Deep Reinforcement Learning for Geospatial Localization
OPEN SESSION:
An open session will collect 5-minute voluntary presentations of work in
progress by participants. They should submit a half-page abstract containing
the title, authors, and summary of the research to da...@irdta.eu by October 9,
2022.
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 da...@irdta.eu by
October 9, 2022.
EMPLOYER SESSION:
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 da...@irdta.eu by October 9, 2022.
ORGANIZING COMMITTEE:
Nosheen Abid (Luleå)
Sana Sabah Al-Azzawi (Luleå)
Lama Alkhaled (Luleå)
Prakash Chandra Chhipa (Luleå)
Saleha Javed (Luleå)
Marcus Liwicki (Luleå, local chair)
Carlos Martín-Vide (Tarragona, program chair)
Hamam Mokayed (Luleå)
Sara Morales (Brussels)
Mia Oldenburg (Luleå)
Maryam Pahlavan (Luleå)
David Silva (London, organization chair)
Richa Upadhyay (Luleå)
REGISTRATION:
It has to be done at
https://irdta.eu/deeplearn/2022au/registration/
The selection of 8 courses requested in the registration template is only
tentative and non-binding. For logistical reasons, it will be helpful to have
an estimation of the respective demand for each course. During the event,
participants will be free to attend the courses they wish.
Since the capacity of the venue is limited, registration requests will be
processed on a first come first served basis. The registration period will be
closed and the on-line registration tool disabled when the capacity of the
venue will have got exhausted. It is highly recommended to register prior to
the event.
FEES:
Fees comprise access to all courses and lunches. There are several early
registration deadlines. Fees depend on the registration deadline. The fees for
on site and for online participants are the same.
ACCOMMODATION:
Accommodation suggestions are available at
https://irdta.eu/deeplearn/2022au/accommodation/
CERTIFICATE:
A certificate of successful participation in the event will be delivered
indicating the number of hours of lectures.
QUESTIONS AND FURTHER INFORMATION:
da...@irdta.eu
ACKNOWLEDGMENTS:
Luleå University of Technology, EISLAB Machine Learning
Rovira i Virgili University
Institute for Research Development, Training and Advice – IRDTA, Brussels/London
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