Aarhus Universitets segl

Andreas Hedegaard Slavensky completes his PhD

On 8th October Andreas successfully defended his PhD thesis

Andreas holding thesis

Andreas has successfully defended his PhD thesis "Improvements to Machine Learning-enhanced Atomistic Global Optimization Algorithms", marking the end of his years as a PhD in InterCat under supervision of Bjørk Hammer and Mie Andersen.

Andreas started his PhD studies in 2020, during the pandemic, which meant that supervision, meetings and getting to know his colleagues was carried out behind a screen.

During his studies, Andreas examined how atomistic global optimization algorithms could be improved. These algorithms are essential for predicting the properties of materials, as they help model materials at the atomic level. As nature tends to maximize stability of various materials, atomistic global optimization algorithms are used to determine the most stable configuration from a given number of atoms. He studied how different machine learning methods could be used to increase the performance of such algorithms, reducing the computational resources required to solve such optimization problems.

Well done Andreas and thank you for being a part of InterCat - we wish you all the best in your new job.