Helmholtz-Zentrum Dresden-Rossendorf
Machine Learning for Materials Design
Dr. Attila Cangi
Head of Department Machine Learning for Materials Design
Phone
+49 3581 37523 52
a.cangi
hzdr.de
Links
CV / Lebenslauf
Department Website
Research Group Website (Personal)
ORCID: 0000-0001-9162-262X
Address
Building/Office
Conrad-Schiedt-Straße 20 - 02826 Görlitz
GRWerk1/228
Area of responsibility
- Application of machine learning in materials science and chemistry
- Scalable machine learning for electronic structure calculations of material properties
- Simulation of magneto-structural phase transitions in materials
- First-principles simulations of electronic transport properties
- Method development for describing electronic structure and dynamics using density functional methods
Career (education, degrees, important stations)
- 2024 – now: Helmholtz-Zentrum Dresden-Rossendorf, Germany: Head of department, Staff scientist (permanent)
- 2022 – 2024: Helmholtz-Zentrum Dresden-Rossendorf, Germany: Head of department (acting), Staff scientist (permanent)
- 2020 – 2022: Helmholtz-Zentrum Dresden-Rossendorf, Germany: Staff scientist
- 2019 – 2020: Sandia National Laboratories, Albuquerque, USA: Staff Scientist (permanent)
- 2017 – 2019: Sandia National Laboratories, Albuquerque, USA: Staff Scientist (LTE)
- 2011 – 2017: Max Planck Institute of Microstructure Physics, Halle (Saale), Germany: Postdoctoral Researcher with E. K. U. Gross
- 2006 – 2011: University of California, Irvine, USA: Ph.D., Chemistry (Chemical and Materials Physics) with K. Burke
- 2005 – 2006: Rutgers, The State University of New Jersey, USA: M.Sc., Physics
The Machine Learning for Materials Design research group accelerates materials innovation through machine learning and computational modeling, with a focus on developing sustainable materials for a greener future. Our applications span energy storage devices, thermoelectrics, spintronics, neuromorphic devices, and advanced semiconductor modeling.
