Plant Biology
Together with the Laboratory of Plant Cell and Developmental Biology (KAUST), we developed an imaging platform that can monitor thousands of seeds from germination to root development.
Profiling the plant root architecture is vital for selecting resilient crops that can efficiently take up water and nutrients. The high-performance imaging tools available to study root-growth dynamics with the optimal resolution are costly and stationary. We developed the MultipleXLab: a modular, mobile, and cost-effective setup to tackle these limitations
Read more here:
https://plantmethods.biomedcentral.com/articles/10.1186/s13007-022-00864-4
Profiling the plant root architecture is vital for selecting resilient crops that can efficiently take up water and nutrients. The high-performance imaging tools available to study root-growth dynamics with the optimal resolution are costly and stationary. We developed the MultipleXLab: a modular, mobile, and cost-effective setup to tackle these limitations
Read more here:
https://plantmethods.biomedcentral.com/articles/10.1186/s13007-022-00864-4
Medicine
Tzanck smear test is a low-cost, fast and accurate diagnostic test for skin diseases. It causes minimal patient discomfort therefore anesthesia is not required. Unfortunately its use is limited because it requires expertise to interpret cell images. Therefore alternative diagnostic tests are preferred that are expensive or invasive.
To solve this problem we developed TzanckNet, a neural network that can identify cells in Tzanck smear images. It has the potential to lower the experience barrier needed to use this test, broadening its user base, and hence improving patient well-being.
Read more here:
https://www.nature.com/articles/s41598-020-75546-z
To solve this problem we developed TzanckNet, a neural network that can identify cells in Tzanck smear images. It has the potential to lower the experience barrier needed to use this test, broadening its user base, and hence improving patient well-being.
Read more here:
https://www.nature.com/articles/s41598-020-75546-z
Physics
Measuring particle sizes accurately is crucial for many industries such as pharmaceutical, chemical and food. Light scattering is a fundamental property that can be exploited to create particle size analyzers. The most common particle size analyzers rely on measuring the scattering angles from a sample illuminated by a laser beam. Compared to other non-light-based counterparts, such a laser diffraction scheme offers precision, but it does so at the expense of size, complexity and cost.
We built a machine learning model that can predict particle sizes accurately from scattered light, for a novel particle size analyzer that is 10x smaller than the traditional ones.
Read more here:
https://www.nature.com/articles/s41377-020-0255-6
We built a machine learning model that can predict particle sizes accurately from scattered light, for a novel particle size analyzer that is 10x smaller than the traditional ones.
Read more here:
https://www.nature.com/articles/s41377-020-0255-6
Biology
The global burden of infections is more apparent than ever. Direct and fast assessment of antimicrobial surface activity is important for developing better anti-microbial surfaces. We developed a computer program that can quantify bacteria activity over time.
Read more here:
https://pubs.acs.org/doi/abs/10.1021/acs.analchem.0c00367
Read more here:
https://pubs.acs.org/doi/abs/10.1021/acs.analchem.0c00367
Trainings
AI talent shortage is the most pressing issue for industry and academia. We have given high-level workshops (Eindhoven Physics Symposium), hands-on trainings (FruitPunch AI code) as well as supported schools as teaching assistants (JADS). We arranged tailor made trainings for companies as well. We started our blog to share what we know.