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Profil
| Derzeitige Stellung | Professor W-1 und Äquivalente |
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| Fachgebiet | Werkstofftechnik,Theoretische Physik |
| Keywords | Adaptive learning, Statistical learning, Functional materials, Materials informatics, Bandgap prediction |
Aktuelle Kontaktadresse
| Land | USA |
|---|---|
| Ort | Los Alamos |
| Universität/Institution | Los Alamos National Laboratory |
| Institut/Abteilung | Materials Science and Technology Division (MST-7) |
Gastgeber*innen während der Förderung
| Prof. Dr. Matthias Scheffler | Fritz-Haber-Institut der Max-Planck-Gesellschaft, Berlin |
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| Beginn der ersten Förderung | 01.05.2017 |
Programm(e)
| 2016 | Humboldt-Forschungsstipendien-Programm für Postdocs |
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Publikationen (Auswahl)
| 2020 | Ghanshyam Pilania, Prasanna V Balachandran, James E Gubernatis, Turab Lookman: Data-Based Methods for Materials Design and Discovery: Basic Ideas and General Methods. Morgan & Claypool Publishers, 2020 |
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| 2018 | ArunMannodi-Kanakkithodi, Anand Chandrasekaran, Chiho Kim, Tran Doan Huan, Ghanshyam Pilania, Venkatesh Botu, Rampi Ramprasad: Scoping the polymer genome: A roadmap for rational polymer dielectrics design and beyond. In: Materials Today, 2018, 785-796 |
| 2017 | Rampi Ramprasad, Rohit Batra, Ghanshyam Pilania, Arun Mannodi-Kanakkithodi, Chiho Kim: Machine learning in materials informatics: recent applications and prospects. In: NPJ Computational Materials, 2017, 1-13 |