Hi, I am a PhD candidate in Machine Learning at ETH Zurich and the Max Planck Institute for Intelligent Systems. I am advised by Andreas Krause and Bernhard Schölkopf.
My interests in machine learning span across various fields. My current research explores how to build machine learning models for scientific and medical applications that enable novel discoveries. Broadly, I work on two areas:
- Using large language models and reinforcement learning to develop clinical prediction models that perform reliably under real-world conditions;
- Combining foundation models and causal inference to understand and predict the effects of interventions, with a focus on applications in single-cell biology.
I hold a Master's degree in Statistics from ETH Zurich. For my Master's thesis, I worked with Charlotte Bunne and David Alvarez-Melis at Harvard on optimal transport for modeling single-cell dynamics. Before my PhD, I was a Data Scientist at QuantCo and interned at IBM.
Reach out if you want to chat!
Email: frederike.luebeck@inf.ethz.ch
Publications
Master Thesis Projects
I am happy to supervise Master students. You can find current available projects on the LAS Group Student Projects page. If you're interested, please reach out with your research interests, along with your up-to-date CV and academic transcript.