Dr Adam Richard-Bollans
Future Leader Fellow
Department
Team
Specialism
Machine learning, data analysis, computing.
There are an estimated 343,000 known vascular plant species that remain largely unexplored scientifically, and in my research I aim to develop machine learning approaches to efficiently search these plants for new compounds of pharmaceutical interest.
In my work I hope to reinforce the importance of protecting plant biodiversity while accelerating the search for new medicinal plant-derived compounds.
- PhD Computing - The University of Leeds - 2021
Richard-Bollans Adam, Aitken Conal, Antonelli Alexandre, Bitencourt Cássia, Goyder David, Lucas Eve, Ondo Ian, Pérez-Escobar Oscar A., Pironon Samuel, Richardson James E., Russell David, Silvestro Daniele, Wright Colin W., Howes Melanie-Jayne R. (2023)
Machine Learning Enhances Prediction of Plants as Potential Sources of Antimalarials,
Frontiers in Plant Science 14
Get in touch
a.richard-bollans@kew.org