Sebastian is a Physics PhD student at Stony Brook University. While originally active in the field of strongly correlated systems with a focus on mathematical topics such a group cohomology, his area of research has shifted towards computational methods in condensed matter physics. In particular, his work investigates how deep learning can be used to advance simulations based on first principals in both chemical sciences as well as material science. Sebastian's research has been recognized through multiple awards and fellowships. He is a two-times recipient of the Young Researcher Award, granted by the Institute for Avanced Computational Science and is currently supported by a Software Fellowship awarded by the Molecular Science Software Institute (MolSSI). He has received training in sustainable software development from MolSSI, which he draws upon for the creation of his machine learning package and thesis project: NeuralXC. Apart from being an avid guitarist, Sebastian enjoys hiking and mountain biking as well as working on machine learning and data science projects outside his research field.

Links

  • Stony Brook Group
  • MolSSI
  • IACS
  • Princeton CSI
  • NeuralXC
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