Research and teaching in the areas Data Science, Machine Learning, and Visual Analytics.Current key research areas:● Latent space representations of complex data using deep learning (e.g. mass spectra, audio, text)● Cheminformatics/Computational Metabolomics --> predictions on unknown compounds and complex biological mixtures● Graph-based data analysis and visualization● NLP (conversation analysis, chatbots)

Applying machine-learning techniques to various research projects, for instance to:● Compare + cluster mass spectrometry data and gene sequences (with Wageningen University).● Classify and cluster EEG time series data (with Utrecht University).● Classify time series from sensor data or images of pieces of art.Data analytics, statistical methods, and software development for research projects.● Detecting and classifying correlations in large data sets.● Selecting and developing statistical methods for data analysis.● Work on scientific software packages (Python).Science & technology communication and teaching:● Organization of applied Machine Learning for Research workshop.● Data exploration and machine learning trainings.● Blogging, e.g. on ML/AI topics: medium.com/@f.huber

Developed Monte-Carlo computer-simulation that allows to explain a large set of experimental observations of microtubule growth dynamics.

I founded KÄNDI in 2015 in Amsterdam to develop and produce better tasting, better looking, more sustainable candy. Starting a small company comes with many different exciting tasks, including:● Development of organic, sustainable sweets and food concepts● Setting up a small-scale artisanal production for premium candy in Amsterdam.● Presentations, workshops, and demonstrations on the science and perception of candy (or food in general).

Independent research in the group of Marileen Dogterom.● Development of novel computer simulations to model and analyze microtubule tip dynamics (Python based).

Independent research in the groups of Marileen Dogterom and Gijsje Koenderink.● Develpment of computer simulations and data analysis tools to model and analysis microtubule dynamics. (MATLAB, Python)● Design and construction of complex in vitro experiments on cytoskeleton organization and self-regulation with a focus on microtubule-actin crosstalk. ● Development of automated image analysis tools to interpret experimental data (MATLAB, Python, ImageJ)

● Experimental research to mimic the self-organization of actin networks in living cells. ● Design, development and application of computer simulations to understand lamellipodium network formation as seen in crawling mammalian cells.● Design, development and application of a complementing mathematical modeling on actin network formation in crawling mammalian cells.

● Conception and organization of the microfestival 'doppelplusfrei' on free improvised music combined with video art installation. ● Acquisition of subsidies and support money.

Construction of an experimental setup to observe vesicle / liposome deformation under flow.

Working as a nurse in a retirement home. Helps to appreciate solid food, day shifts, and the years to come.