Philine Lou Bommer
Department: Data Science in Bioeconomy
Research programs
Research areas
Philine is interested in Deep Learning, Explainable AI, scientific data evaluation and environmental science. She is working towards developing explainable AI solutions, which are targeted towards the application in scientific data analysis. Her work focusses on specifically on environemental and climate science. In these fields she assesses the application of XAI solutions to gain new scientific insight in climate and hwo to develope XAI methods to enable the transparent application of AI.
Committees and boards
Recent Projects:
https://proceedings.mlr.press/v162/kramer22a.html
https://meetingorganizer.copernicus.org/EGU22/EGU22-8130.html
Projects
Publications
- Bommer, P.; Kretschmer, M.; Hedström, A.; Bareeva, D.; Höhne, M. (2024): Finding the right XAI Method - A Guide for the Evaluation and Ranking of Explainable AI Methods in Climate Science. Artificial Intelligence for the Earth Systems (AIES). : p. 1-55. Online: https://doi.org/10.1175/AIES-D-23-0074.1
- Hedström, A.; Bommer, P.; Wickstrøm, K.; Samek, W.; Lapuschkin, S.; Höhne, M. (2023): The Meta-Evaluation Problem in Explainable AI: Identifying Reliable Estimators with MetaQuantus. Transactions on Machine Learning Research. (06): p. 1-35. Online: https://openreview.net/forum?id=j3FK00HyfU
Curriculum Vitae
Philine Bommer received her Master's degree in Physics at University of Heidelberg in 2020 and in the following worked as a research assistant at ZI Mannheim. Previously, Philine earned her Bachelor's degree in Physics at University of Heidelberg. She started pursuing her PhD at the Department of Machine Learning at TU Berlin in October 2022 and is a part of the UMI Lab research group. Currently, she is continuing her PhD in the departement of Data Science in Bioeconomy at ATB Potsdam.
A tabular CV can be found here.