Josef Spidlen
BD Biosciences, Ashland, OR, USA


Josef Spidlen received his MSc in Computer Science and his PhD in Biomedical Informatics from the Charles University in Prague. His career includes commercial software engineering work, 5 years as a researcher at the Institute of Computer Science, Academy of Sciences of the Czech Republic, and over a decade as a scientist at the Terry Fox Laboratory, BC Cancer Agency in Vancouver, Canada. Josef developed many R packages and dozens of GenePattern modules for computational flow cytometry data analysis. He also led the development of FlowRepository for over 5 years; he is an active member of ISAC, a 2016-2019 ISAC Marylou Ingram Scholar, and the first author of several cytometry standards including FCS, Gating-ML and MIFlowCyt. In 2016, Josef joined FlowJo to help bring the advancements of computational biology to benchtop scientists by implementing computational algorithms in FlowJo, and later by leading a team to drive innovation in FlowJo products. In late 2017, FlowJo was acquired by BD, and integrated as the Research Informatics Platform of BD Biosciences. Josef became the R&D leader of the Research Informatics platform driving engineering, bioinformatics, quality assurance, and design teams to deliver science-first informatics solutions in flow cytometry and single-cell genomics. In 2019, Josef extended his role by joining the BDB R&D leadership team, and in 2022, BD acquired Cytognos, and Josef further expanded his role by also taking on leadership of the Cytognos software R&D team. Currently, Josef is accountable for setting the technical vision and direction for BDB’s Informatics portfolio (including BD Research Cloud, FlowJo, Infinicyt and other products), execution on the Informatics strategy, delivering BDB’s suite of cloud and desktop applications, as well as driving development activities for new technology, strategy, computational approaches in Informatics and improvements in BDB’s overall software ecosystem.

Selected publications:

Please select the 5 most interesting publications.
  • Hahne F et al., flowCore: a Bioconductor package for high throughput flow cytometry. BMC Bioinformatics (2009)
  • Spidlen J et al., FlowRepository: A resource of annotated flow cytometry datasets associated with peer‐reviewed publications. Cytometry A (2012)
  • Spidlen J et al., Data file standard for flow cytometry, Version FCS 3.2. Cytometry A (2021)
  • Belkina AC et al., Automated optimized parameters for T-distributed stochastic neighbor embedding improve visualization and analysis of large datasets. Nature communications (2019)
  • Roca CP et al., AutoSpill is a principled framework that simplifies the analysis of multichromatic flow cytometry data. Nature communications (2021)