Stefan Canzar

Dr. Stefan Canzar leads the Algorithmic Bioinformatics research group at Ludwig-Maximilians-Universität München's Gene Center since 2016, where he develops computational methods for genomic data analysis. His lab focuses on reconstructing biological patterns from fragmented sequencing data using combinatorial optimization and machine learning techniques.

Research interests span:

• Transcriptome reconstruction through methods like CIDANE and Ladder-seq that improve RNA-seq accuracy
• Single-cell genomics including Sphetcher for cellular heterogeneity analysis and multimodal integration
• Algorithm engineering for high-dimensional biological data processing
• Combinatorial optimization applied to omics data integration and network analysis

Canzar's publications demonstrate consistent focus on developing scalable algorithms for genomic data challenges, particularly in RNA reconstruction, single-cell analysis, and multimodal integration. His recent work emphasizes dimensionality reduction techniques and transcriptome quantification improvements.

Currently funded projects include BAYHOST and DFG collaborative research center LETSIMMUN. As group leader, he mentors doctoral researchers including Alice Descoeudres and Shuang Li.

The Canzar Lab develops open-source software tools that have contributed to discoveries in neural development, leukemia research, and immune system regulation through collaborations with medical institutions.