About ML4Cryo

ML4Cryo is a place where the cryosphere community and the machine learning community come together. We are here to bridge gaps, support each other, and do science together.

To melt our communities together, we do the following:

  • Maintain a Community Platform (Slack Space)
  • Offer Announcement Options (Mailinglist & Re-tweeting)
  • Organize Scientific Exchange (Workshops / Winter Schools)

The website you are on, is supposed to be the entry point, where you can choose how exactly you want to interact with the broader community :)

How can I interact with the ML-Cryo community?

We offer some facilitation to get in touch, with folks working on either side and anywhere in between.

Slack Space

This is the right place for you, if you want to regularly interact with ML4Cryo people.

You might be actively doing research at the intersection, or you are an ML person or Cryo person who needs ML support / domain expertise. If you are a professor or senior scientist and want to be up-to-date who is doing what in the community, this is also the right place. If you are not a researcher/scientists, but another stakeholder (e.g. users, applied folks, indigenous community, and more), and you want regular interactions, this is also the right place for you.

Forms of interactions: Learning from each other, teach, inspire, support, exchange, share your work, joke around, find collaborators or co-workers, and more.

Mailing List & Twitter

This is the right place for you, if you do not want to miss the most important developments.

Twitter might be the more regular, less filtered, and less consistent option.

The Mailing List is a form of community-lead newsletter. Once a month you will receive a collection of the most important news. Everyone who is part of the community can send requests of news items to be included.

This is the right place to hear about conference-sessions, workshops, and other events, as well as job announcements, highlighted papers and datasets and funding opportunities.

Form of interactions: Listening, observing, receiving announcements. (Submitting announcements)

Events

You can also participate in events to share your work and learn actively with others. Right now, we have a list of conference sessions, workshops, and summer schools collected on this website (“Events”). In the future, we want to offer a regular winter school where everyone can get together.

Form of interactions: Actively learning, presenting your work, networking, having fun together.

Become Part of our Team!

If you want to get more actively involved, we are happy to share tasks and responsibilities for the ML4Cryo platforms!

Currently open positions (volunteering):

  • Moderation committee
  • Public Relations committee
  • Finance committee
  • EDI committee

If you are interested, please reach out to us at ml4cryo@gmail.com with a short description of who you are, and how you would like to contribute!

Form of interactions: Community engagement, sharing responsibility in community building, organizing, supporting, working together with fantastic human-beings ;D

Team

ML4Cryo is a research community initiated by Julia Kaltenborn, Andrew McDonald, and Kim Bente.

Picture of Andrew

Andrew McDonald

he/him

University of Cambridge & British Antarctic Survey

Andrew is a PhD Student in the AI4ER CDT at the University of Cambridge and British Antarctic Survey working alongside Scott Hosking and Rich Turner to advance the intersection of machine learning and climate science. His research is focused on improving sea ice forecasing with diffusion models.

arm99@cam.ac.uk Website LinkedIn Twitter
Julia has white skin, blue eyes, long fair hair that looks slightly tousled in that pic.

Julia Kaltenborn

she/her

McGill University & Mila - Quebec AI Institute

Julia is a PhD student at Mila - Quebec AI Institute and McGill University, supervised by David Rolnick. She is particularly interested in advancing DL-based emulators for snow modeling. And Julia is always down for a ski-tour :)

julia.kaltenborn@mila.quebec Website LinkedIn Twitter
Picture of Kim Bente smiling at the camera in the Sydney sun.

Kim Bente

she/her

University of Sydney

Kim is a final-year PhD student at the School of Computer Science, at The University of Sydney, Australia. She is supervised by Prof Fabio Ramos (NVIDIA and University of Sydney) and A/Prof Roman Marchant (The University of Technology Sydney) and part of the ARC Industrial Transformation Training Centre for Data Analytics for Resources and Environments (DARE). Her research focuses on developing probabilistic machine learning models for environmental monitoring and forecasting for the Antarctic ice sheet. Her research interests span geospatial modelling, kernel methods, Bayesian Optimisation, sensor placement, remote sensing, climate science, super-resolution, and uncertainty quantification.

kim.bente@sydney.edu.au Website LinkedIn Twitter