RESEARCH
Dr. Lehmann’s research brings together genomics, transcriptomics, and single-cell biology with advanced machine learning. At KAUST, he led the long-read genome sequencing of anemone fish species and has worked on both non-spatial and spatial single-cell transcriptomics and multiomics. He uses machine learning to study differences between individual cells, trace how cells develop over time, and understand how genetic changes affect cell behavior.
His team won the NeurIPS 2021 Challenge for their work on combining different types of biological data using machine learning. In 2025, they presented a study on uncovering cause-effect relationships in gene editing experiments at ICLR. His interdisciplinary work not only deepens our understanding of how genomes and cells function but also creates new tools for analyzing complex biological systems.

BIOGRAPHY
Dr. Lehmann received his Ph.D. in Bioinformatics in 2015 from the Institute for Theoretical Biology and Freie Universität Berlin, where he began combining genomic data with computational models.
After his Ph.D., he co-founded celldeg, a sustainable biotech startup focused on developing innovative photobioreactors.
He joined KAUST in 2016 as a Postdoctoral Fellow and became a Research Scientist in 2018. His work at KAUST focuses on developing deep learning tools for single-cell genomics and integrating different types of biological data. Earlier, he built tools for genome assembly, gene annotation, and population studies of coral reef fish.
Dr. Lehmann is also a dedicated teacher. He has created and led workshops and courses that help students from different academic backgrounds learn advanced data analysis techniques in life sciences. He co-developed the Coursera course Fundamental Skills in Bioinformatics, which has been used by over 10,000 learners at KAUST.