PhD candidate
Research group | Deep Earth (CEED)
Main supervisor | Razvan Caracas
Co-supervisor | -
Affiliation | Department of Geosciences, UiO
Contact | anaanz@uio.no
Short bio
2022 - Present: Ph.D. Research Fellow, CEED, University of Oslo
- By combining geosciences background and computational skills, I apply machine learning to problems in geochemistry.
2019 - 2022: Master’s degree in Geosciences, University of Zagreb
- In my master thesis I sampled metamorphic rocks in East Serbia and analyzed them to write a petrological and geochemical study with implications for tectonic setting of the area.
Research interests and hobbies
My research interests revolve around applying computational mineral physics to better understand the functioning of planetary interiors. I will employ machine learning to build a deep learning based model of interatomic potential energy and force fields which will allow to simulate larger systems in a computationally more efficient way.
In my leisure time I like to read, play volleyball, and enjoy all sorts of outdoor activities, most notably cycling and hiking.
CompSci project
Modelling impact of melts on mantle diffusion and viscosity with geodynamic implications
In this project both the first principles and the reactive force fields molecular dynamics will be used to simulate silicate melts and analyze their structural and dynamical properties. The focus of the project is on kimberlites, ultramafic magmas rich in volatiles, associated with the large igneous provinces and the breakup of supercontinents. The deep-seated mantle source of kimberlites makes them a valuable source of information about the mantle. We will analyze their chemical speciation, and the buoyancy relations to the surrounding mantle. After determining their transport properties, i.e. diffusion and viscosity, this information will be used to understand their geological setup. We will integrate the computed physical properties of the melts into large-scale modeling of tectonic processes, correlate their eruptions with continental cycles, and interpret gravimetric isostasy data.
Publications
CompSci publications
None yet.
Previous publications
None.
