Dr. Michael Steininger, M.Sc.

I joined the DMIR group for my PhD studies after receiving my master's degree in Computer Science at the university of Würzburg in early 2018. As a member of the BigData@Geo project, I am working on climate and air pollution modeling using Deep Learning techniques. I am also interested in methods for tackling data imbalance in regression tasks.

Summer Term 2021:

• Information Retrieval

Summer Term 2020:

• Information Retrieval

Summer Term 2019:

• Information Retrieval

Winter Term 2018/19:

• Databases

Summer Term 2018:

• Information Retrieval

• Best ML Innovation Award: "Deep Learning for Climate Model Output Statistics", Michael Steininger, Daniel Abel, Katrin Ziegler, Anna Krause, Heiko Paeth, Andreas Hotho at Tackling Climate Change with Machine Learning Workshop at NeurIPS 2020 (link)
• Best Student Paper Award: "Evaluating the multi-task learning approach for land use regression modelling of air pollution", Andrzej Dulny, Michael Steininger, Florian Lautenschlager, Anna Krause, Andreas Hotho at FAIML 2020 (link)

• Reviewer for Nature Energy
• Reviewer for Atmospheric Pollution Research
• PC Member for Tackling Climate Change with Machine Learning Workshop at ICML 2021 and NeurIPS 2021
• Subreviewer for several conferences and journals