About
Dr de Oliveira Martins is an evolutionary computational biologist interested in statistical modelling with uncertainty and large-scale genomics. In particular, the design and implementation of Bayesian scalable models for the evolution of genomes and diseases, with special interest in microbes and genes of potential clinical interest.
He did his PhD at the University of Tokyo under the supervision of Hirohisa Kishino, followed by postdoctoral work in Spain, Switzerland and the UK. During his PhD and throughout his postdoc experience he worked with advanced topics in Statistical Evolutionary Biology: genomic heterogeneity, the molecular clock hypothesis, homology and orthology across the Tree of Life, and the limits of protein structure for evolutionary inference. He specialised in Bayesian phylogenetics, where he designed new statistical models and high-throughput software for whole-genome settings, deploying them in high-performance computing (HPC) systems. More recently he employed Statistical Learning to phylogenomics and also to hyperspectral imaging.
Before joining the University of Liverpool, he was a core scientist at the Quadram Institute, a BBSRC strategically funded institute in Norwich, where he applied his knowledge to large-scale analyses of bacterial genomics, from design to deployment. During this time he was also involved in the COVID-19 Genomics UK (COG-UK) consortium, where he performed phylogenetic analyses of SARS-CoV-2 genomes generated at the Institute. For these analyses he developed new tools (e.g. fast, scalable database search) and novel approaches (e.g. phylogeny-based migration inference).
His research plan involves developing Bayesian phylogenomics for an integrated view of microbes together with their hosts and environment, with a long-term goal of bringing proper statistical thinking to large-scale evolutionary analyses and from there into the health setting.
Prizes or Honours
- Seal of Excellence award H2020-MSCA-IF-2016 (European Commission, 2016)
- Japanese Ministry of Education, Culture, Sports, Science and Technology (MOMBUSHO, 2004)
Funded Fellowships
- Early Career Funding Scheme (COG-UK, 2022)