Current projects #

I am a believer in the principles of Open Science, Open Data and Open Source. Thus, I am currently working on a reproducible way of conducting my research on simulation of Fluorescence Correlation Spectroscopy (FCS) measurements and correcting artifacts using neural networks, such as Convolutional Neural Nets (CNNs). I do not have my workflow fixed yet, but to have an insight in my current approach - and with the principles of Open-notebook science in mind:

Fluotracify - doctoral research project done in a reproducible way

Description: In a current project, we apply Deep Learning techniques on Fluorescence Correlation Spectroscopy (FCS) data to correct a variety of hardware- and sample-related artifacts, such as photobleaching, contamination from additional slow moving particles, or sudden drops in intensity because of detector anomalies.

Conference talks #

• Seltmann A, Eggeling C, Waithe D. Automated, User-independent Correction of Artifacts in Fluorescence Correlation Spectroscopy Measurements using Convolutional Neural Networks. Quantitative BioImaging Conference (QBI); 2020 Jan 6-9; Oxford, UK