Yassine Souilmi

With a background in physics, electronics and automated systems, I received extensive training in bioinformatics, computer science and statistics. This diversely rich training opened the opportunity for me to work with the laboratory for personalized medicine (LPM), that I joined in 2013 through a Fulbright joint supervision doctoral grant, and where Dr. Peter Tonellato (PI), my PhD thesis co-advisor gave me the opportunity to work on cutting edge technologies and research questions. Throughout this year of exchange I developed thorough scientific research skills, excellent computational biology methods mastering and became a more independent researcher.

My research focuses on the development of high-throughput genomic data analysis workflows as well as developing breast cancer risk models for the Moroccan population. To resolve the increasing need of clinics in analyzing an increasing number of genomic data, especially data issued from next-generation sequencing, this data requires heavy computational skills and resources. To solve such issues, we developed COSMOS, a python library for massively parallel workflows, and leveraged the power of the cloud computing infrastructures using the best practices. This approach allowed us to provide a very cost effective solution.