James (Ben) Brown, PhD, develops novel machine algorithms for the biological and environmental sciences. At Lawrence Berkeley National Laboratory he leads the development of new machine-learning methods for scientific applications (https://ml4sci.lbl.gov). His group develops "third-wave" learning algorithms that combine the interpretability and reliability of classical statistics with the predictive performance of deep learning.

Ben has published 42 papers in areas including functional genomics, metagenomics, precision medicine, ecotoxicology, theoretical statistics, machine learning, and, more generally, technologies to automate learning from massively multimodal, complex datasets. His work has been collectively cited more than 11,000 times, and his H-index is 25. He is a past fellow of the Alan Turing Institute and a current fellow of Chan Zuckerberg Biohub.