Both my Bachelor and Master degrees were both obtained at the Ecole Polytechnique Fédérale de Lausanne in Switzerland. Over the course of my studies, I was able to learn from various fields ranging from oncology, medical engineering to advanced data analysis and machine learning methods. Over the course of my Master’s studies I focused on the latter in a variety of fields such as brain-computer interfaces, image analysis and more importantly genomics and transcriptomics.
The aim of my Master thesis at the Computational Biology & Cancer Genomic group (UNIL) was to predict the efficacy of the off-label use of targeted cancer therapies for individual patients by using open source gene essentiality screens (both CRISPR and RNAi).
I joined the Saez lab as a PhD candidate in the fall of 2021 and will be working on single-cell transcriptomics data from neuronal tissues in collaboration with the lab of Prof. Rohini Kuner and the Heidelberg Pain Consortium.
I am interested in how experimental data and prior biological evidence can be used to generate and address new hypotheses by using computational techniques. In particular, I find it fascinating how data analysis techniques from various fields (such as image analysis and machine learning) can be applied to biological data in order to gain valuable insight into the mechanistic background of biological processes or pathogenesis of various diseases.
My current research project is investigating the transcriptomic changes that occur in cortical regions of the brain under chronic pain.
|2021 - Present
|PhD Candidate, Institute for Computational Biomedicine, Heidelberg University, Faculty of Medicine & Heidelberg University Hospital
|Internship at the Science and Technology office at the Swiss Embassy in Tokyo
|Research Internship at the AIDS Vaccine Research Laboratory, University of Wisconsin
|MSc in Life Sciences Engineering, Ecole Polytechnique Fédérale de Lausanne, Switzerland
|BSc in Life Sciences and Technologies, Ecole Polytechnique Fédérale de Lausanne, Switzerland