About
Leo is an evolutionary computational biologist interested in (1) large-scale genomics and (2) statistical modelling with uncertainty. In particular, he designs and implements scalable Bayesian models for genomes and diseases, for instance microbial genes of clinical relevance. He is also interested in engineering solutions for analysing and sharing One Health information, including biosurveillance.
He did his PhD under the supervision of Hirohisa Kishino, followed by postdoctoral work in Spain, Switzerland and the UK. He worked with Statistical Evolutionary Biology topics, like genomic heterogeneity in the Tree of Life, the molecular clock hypothesis, and protein structure for evolutionary inference. He specialised in Bayesian phylogenetics, designing models and software for whole-genome settings, deploying them in high-performance computing systems. He also employed Statistical Learning to phylogenomics and to hyperspectral imaging.
Before joining the University of Liverpool, he was the Head of Phylogenomics at the Quadram Institute, where he applied his knowledge to large-scale analyses of bacterial genomics. During this time he was also involved in the COVID-19 Genomics UK (COG-UK) consortium, where he performed studies for SARS-CoV-2 genomes generated at the Institute. For these studies he developed a scalable database search and fast phylodynamics models. He also participated in other pandemic response initiatives, like the Real-time Assessment of Community Transmission (REACT) in the UK and other efforts led by the Africa CDC.
Currently his main research involves (1) developing Bayesian phylogenomics for an integrated view of microbes together with their hosts and environment, and (2) extending evolutionary models for application in general Learning problems. His long-term goal is bridging statistical tools and evolutionary analyses, to apply them into biomedical sciences and healthcare. He is based at the Signal Processing Group, with close links to the Civic Health Innovation Labs (CHIL) and the Microbiome Innovation Centre (MIC).
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)