I did my bachelors and masters in Physics in Iran. In my master's project, I worked on optimizing graphene oxide as an antibacterial agent. After that, I started working as a data scientist where I was involved in creating models to analyse social media.
I am interested in combining my physics background with what I have learned while working as a data-scientist by solving problems in physics with computational and machine learning tools.
For my PhD, I will be studying the frictional properties of surfaces by coupling physics-based simulations and machine-learning models to predict surface structures.
Research interests and hobbies
My research interests are statistical mechanics, machine learning, simulation of materials, and complex systems. As for hobbies I enjoy reading, working out, music, and origami.
Frictional properties of surface structures generated by machine-learning
Friction as the force between surfaces in contact, resisting relative motion, is crucial both in applications like object grasping robots, and in scientific problems like understanding earthquakes in the earth’s crust. Frictional properties are generally sensitive to changes in surface structures, which leads to the idea of controlling friction by choosing particular surface structures.
Neural networks can be used to map physical structures to their properties. In this project I will integrate physics-based simulations and machine learning methods, to create optimized surface structures with prescribed frictional behaviour.
- Astani, N.A., Najafi, F., et al. (2021) ‘Molecular machinery responsible for graphene oxide’s distinct inhibitory effects toward Pseudomonas aeruginosa and Staphylococcus aureus pathogens’, ACS Applied Bio Materials, pp. 660–668. doi:10.1021/acsabm.0c01203.