I am a science enthusiast. I like research and challenges it offers. I also enjoy the challenge of science dissemination in simple terms.
My interests have been evolving from THEORETICAL PHYSICS through COMPUTATIONAL MATERIALS SCIENCE to DATA-DRIVEN computing.
In my research, I exploit DATA [ which I generate via high-throughput quantum-mechanical computations or find online in available data bases ] and develop MODELS.
The latter e.g. NEURAL NETWORK, can help us to learn essential features of INORGANIC MATTER:
patterns, structural stability and multi-variate functional dependencies.
Specific applications of my models include
- Interatomic Force Fields (trained from first principles calculations and then extrapolated in time / scale)
- Crystal Structure prediction, where first principles calculations is a basis reference
- Phase fields detection with high likelihood of finding novel compounds.
In my free time I like photography, walks with a dog, talking to children about nature.