Machine learning in high-throughput imaging enabled label-free cell screening


Recently, I have been exploring potential collaborations with my colleagues, Dr Chao Wang and Dr Farzin Deravi at Kent in the area of bio-photonics . At the same time, a friend of mine took up a job as a manager of Centre for Nano- and Biophotonics at Ghent University. He pointed out to me there is a travel grant scheme to encourage Kent-Ghent collaboration. One things led to another, we have now been awarded a small travel grant to explore how machine learning techniques can be used to analyse cell images.

The proposed project aims to integrate machine learning based feature extraction with high-throughput cell imaging technologies for high-precision label-free cell screening.  The project will bring together complementary expertise and allow both Kent and Ghent teams to explore new research opportunities in the interdisciplinary field of biophotonics, big data photonics and computational photonics.  It is anticipated that this collaborative project will lead to a long-term collaboration between the groups underpinned by Kent’s policy as the European University.

I realise this is not the usual kind of research I do, but I am pretty excited to learn something new and potentially fun!


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