Call for Presentations and Posters
January 27-29, 2020

Want to speak and present your work during one of the largest machine learning and AI events in Europe? This is your chance!

As last year, AMLD2020 features different domain-specific tracks from Monday to Wednesday, January 27-29, 2020. More than twenty “AI & your domain” tracks will be featured during the event.

If you have some interesting research, a practical project, an awesome product, a promising startup, a sharp expertise, a strong opinion or anything worth sharing and discussing with other researchers, practitioners, fields experts or machine learning and AI enthusiasts, we encourage you to submit a proposal for one of the tracks in development. You can propose a presentation and/or a poster.

Presentation Format:

  • Language: all presentations are in English
  • Presentation duration: we would like to keep the sessions interesting, full of energy and fast-paced. We’re looking for talks of a length between 5 and 30 minutes, most being on the shorter end. We will be on a tight schedule and will enforce the time limits rigorously. We suggest that you time your presentation accordingly in advance.
  • Brevity: keep the proposal concise and focused. If you need more than two paragraphs to get to the point, we ask you to put more time into focussing your application. With the amount of submissions we get, the quicker you can make a good first impression, the better.
  • Originality: one of the things we want to do at AMLD is to push the community forward. Thus, we favor original content. If you want to present a topic that you have talked about elsewhere, try to add a twist, new research or development to it - something to make it unique.

Poster Format:

  • Language: all posters are in English
  • Poster format: Poster size should be standard A0 (841 × 1189mm), preferably in portrait orientation.
    Note that you will need to print, bring and hang your poster yourself. Poster contributors need a Conference Ticket to attend the Conference and the Poster Sessions.
  • Originality: same here, we favor original and novel work.

Selection process:
Here’s how presentations and posters will be selected:

  • All submissions are anonymized, so that there is no bias towards the submitter.
  • All submissions are reviewed and voted for by the conference and track organizers. Each presentation and poster is rated on a scale from 1 to 5, taking into account the following criteria:
    • 1. relevance of the topic to the ML community and for the track
    • 2. coherence and clarity of the proposal
    • 3. novelty/originality of the topic
    • 4. if presentation: can the topic be reasonably covered in the allocated time
  • The top submissions are then de-anonymized so we can take speaker details into account.

Video recording for presentations: We plan to record and publish all talks online for free, along with a recording of the slide deck, live demo, and any on-presenter-screen activity. We do this for the benefit of the larger ML community and those who couldn’t make it to the conference. Since you retain full ownership of your slides and recording, we’d like to ask you to make your materials and recording available under a Creative Commons (we default to non-commercial reuse) or other open source licenses.
We hope you agree with us, but if you are uncomfortable with this in any way, let us know.

If in doubt, reach out! If you have an idea for a talk, but are unsure, please talk to us! Reach out to info@appliedmldays.org.

Timeline

Submission deadline

Friday November 1st, 2019 23:59 UTC

Notification

November 22, 2019

Conference, Presentations and Poster Sessions

January 27-29, 2020 at EPFL, Switzerland

Presentation and poster proposal

To apply and submit your presentation and or poster application, please fill out the form below.

First Name and Last Name
displayed on your profile if selected. If you do not want us to show a picture of you, link to another image we can use.
a few sentences, to be displayed on your profile

--- All data above will be hidden from the reviewing team during the initial selection phase to avoid bias. ---

more tracks TBA soon
to be used in the program