Call for Proposals

Proposal Deadline: Sunday March 31, 2019 - 23:59:00

Dates: Fri May 10: tutorials; Sat+Sun May 11-12: main conference.

Venue: Fri - GoDataDriven, Wibautstraat 202, 1091 GS Amsterdam; Sat+Sun - Booking.com, Herengracht 597, 1017 CE Amsterdam

Important dates:

  • Proposal submission deadline on March 31.
  • Acceptance notices will go out by April 11.
  • The program will be published by April 12. 


Submit a new proposal

Accepted speakers receive a free ticket to attend the conference. Please note that speaker expenses for travel and lodging are not covered. Any questions can be directed to [email protected]

Would you be traveling internationally? Submit your proposal now to have it reviewed on a rolling submission to allow enough time for travel arrangements. Travel and lodging expenses will not be paid. *Please make a note in the proposal that you would be traveling internationally*

PyData brings together analysts, scientists, developers, engineers, enthusiasts and others from the data science community to discuss applications of new tools and techniques within data science. Our talks often include data management, analytics, visualization as well as new machine learning approaches including statistical and neural network approaches.

Topics: PyData welcomes presentations focusing on a variety of languages from Python to R, Julia and Scala. In particular, PyData introduces talks that concentrate on either data science or Python, or both.

To see the type of topics presented at previous PyData events, please look at our past conference sites at pydata.org or check out the videos on https://www.youtube.com/user/PyDataTV.

Format:

  • Presentation content can be at a novice, intermediate or advanced level.
  • Talks will run 35 minutes (including questions)
  • Hands-on tutorials will run 90 minutes.

Non-profit: PyData is a volunteer-run conference. It supports open source development by donating all proceeds to NumFOCUS, a non-profit organization that supports the development of open-source tools, such as Numpy, IPython, Jupyter, and many others.

Open Source: As a reminder, PyData presentations are intended to share knowledge and experience. To this end, we encourage the code and/or data that your talk relies on to be open-source. Ideally, the audience would have access to the necessary tools to reproduce the results of the talk. Also, we welcome talks focused on your own practical application of tools and concepts either at work or in your free time, but discourage sales oriented proposals whose sole aim is to sell a product.

Your Submission: In our experience, attendees pay close attention to proposal abstracts when deciding which talks to attend during the conference. The submitted abstract will be published as is in the conference program (you can edit the submission later).

We encourage you to include details about the theory and/or practice that you will discuss. Specifically, if the system you've built uses open source tools, please mention the libraries in the proposal and make it clear whether you will be presenting a case-study of their use or if you will discuss details of their design.

In general conference attendees, as well as the review committee, should be able to answer these questions based on your submission:

  • What problem is your talk addressing (are you talking about a well known problem or have you found something new during a project)
  • Why is the problem relevant to the audience
  • What is(are) your solution(s) to the problem, or are you simply pointing out the fact there is an issue we should be aware of (this is also extremely useful)
  • What are the main takeaways from your talk. For tutorial submission this is extremely important, please specify what people will have learned at the end of the tutorial session.
  • For tutorial submission, please be explicit in how you plan to do the interactive part of the tutorial.

You can check out the following submissions from last year’s conference as a reference for some good examples.

Tom Bocklisch: https://pydata.org/amsterdam2018/schedule/presentation/31/

Jane Stewart Adams: https://pydata.org/amsterdam2018/schedule/presentation/26/

Tobias Sterbak: https://pydata.org/amsterdam2018/schedule/presentation/7/

Diversity & First-Time Speakers: If you are interested in presenting a talk or tutorial, we encourage your submission(s). We especially encourage first-time speakers and submissions by underrepresented members of the community.

Submission Process: After you submit a proposal, the PyData committee will review the proposals and communicate any needed feedback or improvements. We aim to include many first-time speakers, and therefore will attempt to communicate and iteratively help you improve the abstracts.

Keywords:

  • Interesting Datasets
  • Data Visualization
  • New libraries
  • Existing Libraries
  • Simulations
  • Algorithms
  • Python fundamentals
  • Data Mining / Scraping
  • Massive data
  • Devops: Pipelines, Deployment, Scalability, Packaging
  • Jupyter / Notebooks
  • Databases and ETL
  • GIS / Geo-Analytics
  • Natural Language Processing
  • Computer Vision
  • Blockchain
  • Predictive Modelling
  • Python in Social Sciences
  • Neural Networks / Deep Learning
  • Unsupervised ML
  • Theory of machine learning
  • Statistics in ML
  • Ethics of Machine Learning (Privacy, Fairness, …)
  • Transparency in ML / Interpretable Models
  • Spark/Hadoop
  • R
  • Julia
  • Reproducible Science
  • Functional Programming
  • Theory
  • Use Cases
  • Philosophy
  • Best Practice
  • Tutorial
  • Survey

The CFP is currently open until March 31.

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