Based at the Demographic Science Unit and Leverhulme Centre for Demographic Science, Saul is an interdisciplinary scholar with a doctorate from the John Curtin School of Medical Research at the Australian National University, a previous position as a plant scientist with the Australian government and the ANU Research School of Biology, and a general interest in aging, machines, biology, and death.
Saul is currently open to new positions in a broad range of fields outside demography. Recent and upcoming publications span several fields including genomics, remote sensing, demography, statistics, and interpretable machine learning.
Saul’s current interests involve the mortality patterns of complex systems, human aging, and the statistics of survival processes.
Early-life physical performance predicts the aging and death of elite athletes.
Newman SJ., (2023), Sci Adv, 9
Author Correction: A multiple species, continent-wide, million-phenotype agronomic plant dataset.
Newman SJ. and Furbank RT., (2022), Sci Data, 9
Author Correction: Explainable machine learning models of major crop traits from satellite-monitored continent-wide field trial data.
Newman SJ. and Furbank RT., (2022), Nat Plants, 8
Wheat physiology predictor: predicting physiological traits in wheat from hyperspectral reflectance measurements using deep learning.
Furbank RT. et al, (2021), Plant Methods, 17
Explainable machine learning models of major crop traits from satellite-monitored continent-wide field trial data.
Newman SJ. and Furbank RT., (2021), Nat Plants, 7, 1354 - 1363