Keivan Amini

Research Fellow under the supervision of Prof. Daniel Remondini, he performs data analysis to contribute to the GenoMed4All project by implementing supervised and unsupervised machine learning algorithms for the analysis and integration of multi-omics data (mainly dimensionality reduction, clustering and classification).

He graduated in Applied Physics with a thesis on robotics and reinforcement learning written during an internship at the Institute of Intelligent Systems and Robotics at the Sorbonne University, Paris.

In the past, he taught coding, electronics and robotics at the Open Laboratories of Emilia-Romagna, aimed at high school, middle school and primary schools children.

In general, he is passionate about problem solving, programming, and machine learning.