Kirsten Troestrup Winther

Bio

The main goal of my research is to combine density functional theory simulations and data science approaches to accelerate the discovery of novel materials for catalysis. My research interests include:

- The development of machine learning models for the prediction of material stability and adsorption energetics
- Accelerated high-throughput frameworks for materials discovery, using machine-learning aided (active-learning) algorithms for materials exploration.
- Developing scientific software and the open database catalysis-hub.org.

Education & Certifications

Master of Science, Technical University of Denmark, Physics (2011)

Bachelor of Science, Aarhus University, Denmark, Nanoscience (2009)