ELIXIR Bioinformatics Industry Forum: Enabling Ecosystems for Machine Learning in the Life Sciences

Tue 11 October 2022, 09:00 to 18:00
Henry Wellcome Auditorium, Wellcome Collection, 183 Euston Road, London, NW1 2BE, United Kingdom

The ELIXIR Bioinformatics Industry Forum (EBIF) is a one-day event and aims to bring together the community of bioinformaticians to discuss visionary ideas, bottlenecks and solutions to some of the major challenges in the data-driven life science sector.ELIXIR logo

This year’s EBIF focus is on making Machine Learning robust and reproducible for the Life Sciences. The programme includes a mixture of presentations from industry and academia that will lead to panel discussions on the following themes:

  • Interoperable data and workflows to enable reproducible Machine Learning in the life sciences and the role of Open Science in the value chain;
  • Challenges and solutions in Machine Learning for the life sciences - Federated Learning and Synthetic Data;
  • Innovation, collaboration and security in the Machine Learning Ecosystem.

Format: hybrid event

We encourage physical attendance for participating in roundtable discussions and networking activities, and for engaging with the speakers.
Virtual participants will only access live stream and ask questions via SliDo.

Target audience

Bioinformaticians and technical specialists with an interest in the industry perspective of the topic.


  • Give companies the chance to present technological advances in the field of Machine Learning in life sciences;
  • Provide a forum for knowledge exchange and collaboration in the pre-competitive space;
  • Create networking opportunities with bioinformatics opinion leaders, academic experts in ELIXIR and other industry members.


  • Two Sessions of presentations from academia and industry
  • Flash talk session and round table discussions (only for physical attendees)
  • Panel discussions
  • Keynote speech



Tue 4 October 2022



Programme: Despoina Sousoni (despoina.sousoni@elixir-europe.org)
Event administration: Dana Cernoskova (dana@scientifka.eu)