Dr. Malte D. Lücken

Malte Lücken completed his foundational studies in Physics at the University of Warwick before he transitioned to working in computational biology, completing a PhD in network biology with Prof. Charlotte Deane and Prof. Gesine Reinert at the University of Oxford in the Department of Statistics in 2017. After a stint in industry, working at UCB Pharma in Belgium, he moved to Helmholtz Munich in 2018, where he first glimpsed the transformative potential of single-cell genomics during his postdoctoral research with Prof. Fabian Theis. This keen interest led him to establish his independent research group in 2022. The Luecken lab bridges the Computational Health and Environmental Health Centers, working at the interface of machine learning and single-cell genomics, with a focus on lung health.

Malte Lücken’s research focuses on three related areas of single-cell data science: systematic evaluation of tools, building cellular views of human tissues in single-cell atlases, and modelling inter-individual differences. He started in single-cell genomics by establishing the first best practice workflow for analysing single-cell data, identifying patterns in published tool benchmarks. He has since performed numerous benchmarking studies, and co-founded the Open Problems in Single-cell Analysis project, a living benchmarking framework for single-cell genomics, which he uses to run competitions to engage machine learning scientists to address unsolved challenges in single-cell data science. Leveraging these best practice pipelines, Malte Lücken integrates datasets to build cellular reference atlases of human tissues and organs, generating the first reference atlas of a human tissue in the human lung cell atlas. In this capacity, he leads the integration team of the Human Cell Atlas since 2022, a global organization of over 4000 researchers aiming to characterize the cellular landscape of healthy human tissues and organs. He combines benchmarking and atlasing expertise in developing tools to model differences between individuals. He applies these tools to identify biomarkers and build prognostic models in consortia on lung cancer, asthma, COPD, and lung transplantation.