Kalin Nonchev, MSc
Committed to advancing machine learning research in biomedicine to improve clinical decision-making.
My research focuses on understanding the gap between genotype and phenotype in human diseases. Machine learning algorithms are key tools for uncovering biological patterns and interpreting medical datasets. I believe this is the key to more accurate disease diagnoses for patients, and, more importantly, the well-proven rationale for their therapies.
I studied bioinformatics at the Technical University of Munich and Ludwig-Maximilian University of Munich, followed by a Master's at ETH Zurich. During my Bachelor's, I worked with Prof. Julien Gagneur on rare disease genomics. In my Master's, I contributed to transcriptomics projects at the Functional Genomics Center Zurich and Roche Diagnostics. Currently, I am a doctoral candidate under Prof. Gunnar Rätsch's supervision. Meanwhile, I'm grateful to work with exceptional people who continually push the boundaries in biomedical informatics.