Howard worked tirelessly to translate science into effective actions to improve the lives of some of the poorest people in the world. His passion, humour and determination inspired many of us and one of his greatest wishes was to see that work to prevent konzo continue. We will do our best to honour his legacy.
Howard Bradbury followed in his father’s footsteps. “Dad was a chemist and he used to keep telling me stories about it all the time. I couldn’t understand what he said, but somehow something just rubbed off and so I always thought science would be real fun, so I just went into it. I must say I’ve enjoyed every minute."
Tackling one of tropical Africa's crippling epidemic diseases has been an interesting and demanding retirement project, as HOWARD BRADBURY AM writes. Through our work, konzo has now been prevented in 16 villages, which has involved more than 10,000 people.
Plants synthesize an amazing diversity of volatile organic compounds (VOCs) that facilitate interactions with their environment, ranging from attracting pollinators and seed dispersers to protecting themselves from pathogens, parasites, and herbivores.
This seminar is presented by Dr Emily Stringer and Dr Jarrod Sopniewski, Postdoctoral Research Fellows from the Centre for Conservation Ecology and Genomics at the University of Canberra.
Many flowering plants have evolved diverse strategies to communicate with and attract animal pollinators. We have discovered exciting new evidence for the role of anthocyanins and terpenes in the evolution of the highly diverse terrestrial orchid subtribe Caladeniinae (Diurideae).
Using case studies from my research on black-cockatoos and a formal partnership with Bush Heritage Australia, I will discuss how bioacoustics’ focus on machine learning and analysis over the last decade has now landed us in a place to use the technology in applied conservation settings.
Dietary shifts—particularly the inclusion of animal resources—were pivotal in human evolution, yet direct evidence of meat consumption in early hominins remains limited and debated.
By addressing key modeling challenges in mass spectrometry and tissue image analysis, this research advances the scalability, precision, and applicability of deep learning in clinical genomics, computational pathology, and personalized medicine.