Kiarash gained a BSc in mathematics and statistics from the University of Toronto, St George in 2016 and also studied at the Vector Institute as a machine learning researcher being supervised by Frank Rudzicz.  

In the summer of 2019, as part of UofT's PEY programme, he worked as a machine learning researcher at RBC Capital Markets on the Aiden project. After graduating in the winter of 2020, he worked for Semantic Health as a machine learning scientist using NLP to help hospitals maximize the use of their data.

In 2025 Kiarash was awarded a PhD at the MRC Laboratory of Molecular Biology under the supervision of Sjors Scheres. This focussed on applying deep learning to cryogenic electron microscopy (cryo-EM) to create automated atomic model building in cryo-EM maps. He also works on heterogeneous reconstruction algorithms using VAEs, machine learning for protein design (ADFLIP).

At GBI Kiarash is developing deep learning algorithms to generate novel proteins with atomic-level accuracy, targeting functions not found in nature.