Our research is situated at the intersection of computer science and biomedical research, with a strong emphasis on the design and application of data mining and machine learning techniques.
We perform fundamental research on robustness and interpretability of these techniques, and focus on applications in biomedicine and translating machine learning applications to the clinic. Many of our applications deal with single-cell technologies, including cytometry data, single-cell (multi)omics, and single-cell imaging data types.
Clinical applications include allergies and asthma, rheumatology, cancer (lung cancer and leukemia) and primary immune deficiencies (PID).
