Sasan AmariAmir is a PhD candidate in the fields of machine learning and cheminformatics. He received his a bachelor’s degree in ‘chemistry’ from Eötvös Loránd University (ELTE), Budapest. He also holds a master’s degree in ‘materials science and simulation’ from The Interdisciplinary Centre for Advanced Materials Simulation (ICAMS), Ruhr University Bochum, in 2020. In ICAMS he worked on sensitivity analysis for materials simulation inputs as well as applying active learning and transfer learning for material discovery. In the beginning of 2021, he joined the eScience group where he pursues his interest in tackling physico-chemical problems using data science. In his PhD project he investigates the synthesizability of materials by developing machine learning models which learn from materials structures. Inspired by the Pauling Rules for crystal stability, he is searching for chemical heuristics which might govern synthesizability of crystals.
- Sasan AmariAmir. “Master's Thesis: Combining Active and Transfer Learning for Data-guided Search of New Materials”. Ruhr University Bochum, 2020. DOI: http://dx.doi.org/10.13140/RG.2.2.17311.48803
- Gergely T ́oth and Sasan AmariAmir. “Seriation, the method out of a chemist’s mind”. Journal of Chemo-metrics32 (2018).ISSN: 1099128X.DOI: http://dx.doi.org/10.1002/cem.2995