I was born and raised in Germany, where I received my joint BSc. degree in Bioinformatics from the Ludwig-Maximilians-Universität München (LMU) and the Technical University of Munich (TUM) in 2020. My Bachelor's Thesis was on linking gene expression data to transcription factor binding information, to find transcription factors which are active during lactation by predicting gene expression from ChIP-seq signals.
During my undergraduates, I gained further practical experience while working as a student research assistant at the Chair of Experimental Bioinformatics at the TUM. Throughout the two years I worked on projects in the field of systems biology and systems medicine where I wrote tools and co-authored papers on (1) exploring the SARS-CoV-2 virus-host-drug interactome for drug repurposing, (2) analyzing the functional role of alternative splicing in protein interactions, and (3) network-constrained biclustering of patients and omics data.
My current research interests lie in the application of machine learning on health data and range from the fields of genomics to sensor data for medical applications - but I am always eager to explore new research areas.
In my free time I like to meet-up with friends, cook and build stuff; projects that I am currently working on can be found on my GitHub page: github.com/kevihiiin