Kirsten Winther

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