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"We make no apologies for making these excursions into other fields, because the separation of fields, as we have emphasized, is merely a human convenience, and an unnatural thing. Nature is not interested in our separations, and many of the interesting phenomena bridge the gaps between fields."
Richard Feynman, from Lectures on Physics
Machine Learning strategies for Marine Cloud Brightening (2023-present)
Machine Learning strategies for Marine Cloud Brightening (2023-present)
Theme: (1) Environmental; (2) Measurements and models
Marine Cloud Brightening (MCB) could offer a feasible way to yield a cooling effect over the oceans. This project aims at using existing data sets and machine learning techniques to develop techniques that can reliably distinguish the number of particles in clouds and their effects, and their susceptibility to MCB, which in due course could help inform optimal MCB strategies. In particular, it will focus on tackling challenges uniquely related to aerosol-cloud interaction: (i) satellite image resolution; (ii) sparsity and noisy data; (iii) spatial and temporal correlation. It will also tackle challenges related to integrating knowledge of ship journeys.
In collaboration with the Cambridge Centre for Climate repair and AEROSOL CDT
Animal Vibration (2019-present)
Animal Vibration (2019-present)
Collaboration with the Animal Vibration Lab in the Oxford University Biology Department on testing and modelling for investigating:
vibration generation mechanism in planthoppers
spider dynamics
Spider dynamics, Picture taken from https://royalsocietypublishing.org/doi/full/10.1098/rsif.2023.0365
Wu J., Miller T. E., Cicirello A., Mortimer B., Spider dynamics under vertical vibration and its implications for biological vibration sensing, Royal Society Interface, 2023.
https://doi.org/10.1098/rsif.2023.0365Davranoglou L-R., Cicirello A., Taylor G.K., Mortimer B., Planthopper bugs use a fast, cyclic elastic recoil mechanism for effective vibrational communication at small body size. PLoS Biology, 2019.
https://doi.org/10.1371/journal.pbio.3000155
Open for new collaborations!
Much of the cross-disciplinary research that has been carried out within the DVU group was the result of finding common passion in addressing a fundamental gap in knowledge!
The projects carried out have resulted in fundamental understanding, new methodologies, (mostly open access) tools, publications, and datasets.
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