Area of research
Materials Chemistry · Software
Research interest
Research interests include Machine Learning in Materials Science, Model-Driven Software Engineering Techniques, Scientific Computing and Data Management, and Advanced Materials Characterization Techniques.
Towards a new era for open and FAIR data in catalysis research – A catalysis plugin for NOMAD
FAIR-MOFs:A Comprehensive Database for Accelerating the Discovery and Synthesis of Metal-Organic Frameworks
Developments and applications of the OPTIMADE API for materials discovery, design, and data exchange
Roadmap on data-centric materials science
Shared metadata for data-centric materials science
FAIR data enabling new horizons for materials research
Roadmap on Machine learning in electronic structure
Density-of-states similarity descriptor for unsupervised learning from materials data
OPTIMADE, an API for exchanging materials data
optimade-python-tools: a Python library for serving and consuming materials data via OPTIMADE APIs
An open-source, end-to-end workflow for multidimensional photoemission spectroscopy
The OPTIMADE Specification
Metamodeling vs Metaprogramming: A Case Study on Developing Client Libraries for REST APIs
Generation of Large Random Models for Benchmarking.
2015cited by 6position: first
Model-Based Mining of Source Code Repositories
Reference representation techniques for large models
Type-Safe Model Transformation Languages as Internal DSLs in Scala
ClickWatch — An experimentation framework for communication network test-beds
HWL — A high performance wireless sensor research network