Marijn van der Meer
@meer_marijn
Passionate data scientist, doctoral student @ETH researching the cryosphere and feminist activist @polyquity - she/her.
ID: 1387824635874615303
29-04-2021 17:42:43
19 Tweet
103 Followers
95 Following
Welcome to Marijn van der Meer, who joins us as a scientific assistant! ๐ Marijn will be working with Harry Zekollari and focusing on emulating #glacier dynamics using machine learning. ๐ป Happy to have you with us, Marijn!
New article by Sophie de Roda Husman where she intercompares different satellites for assessing surface melt ๐ over the entire Antarctic Ice Sheet ๐ฆ๐ถ. ieeexplore.ieee.org/document/99283โฆ
Group member Marijn van der Meer just returned from the 'Machine Learning in Glaciology' workshop in Norway, where she was able to collaborate with other machine learning experts and enjoy these gorgeous views! ๐คฉโ๏ธโ๏ธ Universitetet i Oslo Universitetet i Bergen Utrecht University TU Delft UC Berkeley University of Twente (inactive)
![[1/4] Weโve been brainstorming in response to the lack of #diversity in the #EGU23 Division Awards. We see potential for #action at both the top #EGU level and the level of individual Divisions.](https://pbs.twimg.com/media/FvCIU-HWcAAmy77.jpg "VAW Glaciology (@vaw_glaciology) on Twitter photo [1/4] Weโve been brainstorming in response to the lack of #diversity in the #EGU23 Division Awards. We see potential for #action at both the top #EGU level and the level of individual Divisions.")
๐คนโโ๏ธOur true polymath, Marijn van der Meer, wrote a fabulous paper on her MSc thesis work๐ฉโ๐. Together with Stef Lhermitte and me, she developed an emulator to reproduce regional high-resolution ๐ surface mass balance predictions over the Antarctic Peninsula ๐ฆ๐ถfrom a GCM.
๐ข Impressive work by team member Marijn van der Meer! In her first published paper in AGU (American Geophysical Union)'s #JAMES, she demonstrates the power of fast machine learning emulators ๐ค to downscale global climate models to regional resolution. Congratulations! ๐ Link below โฌ๏ธ agupubs.onlinelibrary.wiley.com/doi/full/10.10โฆ
๐จ New RSE paper by Sophie de Roda Husman where we present UMelt: an Antarctic-wide ๐ฆ๐ถ, high-resolution surface melt record by merging multi-source remote sensing data ๐ฐ๏ธ using deep learning ๐ค. doi.org/10.1016/j.rse.โฆ
Discover UMelt๐ต๏ธโโ๏ธ, an Antarctic-wide surface melt product with impressive high resolution (500 meters, 12 hours). Dive into the data, exploring both daily and seasonal melt patterns on this Google Earth Engine app: โฆsophiederoda.projects.earthengine.app/view/umelt-insโฆ. (1/6)
Group member Marijn van der Meer was a co-author on this paper from Sophie de Roda Husman looking at surface melt in Antarctica using deep-learning! ๐ฆ๐ถ๐ป They made an instructive and easy-to-use product to examine daily and seasonal melt. Check it out! ๐ค
Last week, PhD student Marijn van der Meer spoke about her research at this seminar on data science in glaciology! She presented her current work modeling glacier mass balance using machine learning. A great opportunity to get in touch with other interdisciplinary scientists ๐
We are excited to announce the 3rd edition of the โMachine Learning in Glaciologyโ workshop, in the Finse alpine research station (Norway) ๐ณ๐ด The workshop will take place on 6-12 September 2024, and the deadline to apply is April 8! โ๏ธ โฆning-in-glaciology-workshop.github.io
Preprint alert! #VAW PhD student Marijn van der Meer introduces miniML-MB, a machine-learning model for glacier mass balance. ๐๏ธ It outperforms simple PDD models in most casesโexciting news for future ML applications in glacier modeling! ๐ป Check it out: egusphere.copernicus.org/preprints/2024โฆ
