Leo Bolero, PhD

Bio

Leo gained independent degrees in computer science and molecular genetics (with honours) in 2004 at the University of NSW in Sydney, Australia. He then completed a post-graduate biotech commercialisation specialisation in 2006 and the same year was runner-up in the Deutsche Bank International Business Planning competition for a rapid HIV typing technology.

After graduation, Leo joined the Symbolic Machine Learning division at National ICT working as a research mathematical programmer in high-dimensional solutions to the P=NP conjecture using machine learning. This is one of the Millennium Prize problems with a $1m bounty posted by the Clay Institute of Mathematics. A novel ultra-fast approximation method was developed from this work, but the prize remains unclaimed as of today.

Returning to academia as an epidemiologist and statistician with the Faculty of Medicine at The University of Sydney in 2008, Leo assisted PhD researchers, physicians and public health scientists frame and analyse over 100 projects in 20+ countries.

Leo then gained a PhD in AI for medical informatics in 2011 under a joint scholarship between Australia’s most prestigious medical and computer science schools, The University of Sydney, and the University of NSW respectively. This PhD was conferred in 2011 via “thesis by publication” of a number of peer-reviewed papers in top-ranked journals in the field generated during his research. An outcome of  this work was his release of the world’s first AI software for analysing mass spectrometry data by combining neural networks with classical statistics for fully automated data processing. This body of work won him a national AusBiotech student excellence award.

Moving to the Queensland Facility for Advanced Bioinformatics at the University of Queensland in 2012, Leo worked as a Senior Computational Biologist. This role involved academic and commercial projects in Omics analysis, study design, and general statistical and high-performance computing advice and support services. Leo was the primary bioinformatician and biostatistician for a number of academic research programs at the University of Queensland and the Queensland University of Technology in areas such as biodiversity, wound-healing, infection, and human and animal health and diagnostics.

Leo was selected to build and lead the discovery and analysis team for ImmuneXpress Inc, and accordingly moved to the USA to take up the position in Seattle, Washington. In this role he interacted extensively with the US regulator, FDA and authored a paper in collaboration an FDA statistician on a novel method to better interpret clinical trial data under conditions of imperfect gold standards. While at ImmuneXpress he completed a post-graduate qualification in International Regulations for Medical Devices at The Johns Hopkins University. Leo guided the science team at ImmuneXpress resulting in the world’s first FDA cleared molecular diagnostic for sepsis using machine learning methods, first as a manual kit, then as a fully automated platform.

In 2018 Leo joined Biocartis, based in Belgium, as Principal Biostatistician where he managed the biostatistics team and oversaw successful regulatory submissions in the US, EU, China and Australia for a number of novel diagnostics on an advanced genomic platform in the oncology and infectious disease space.

In 2024 Leo completed an AI in Healthcare Specialization through Stanford University. 

Since 2020 Leo has been distilling his expertise through his biostatistical consultancy specialising in machine learning and AI in clinical trials and medical devices. His clients range from start-ups through to publicly listed multi-nationals. 

He lives in sunny Brisbane, Australia with his wife and maintains a strong interest in working closely with teams to deliver cutting-edge medical technologies in areas of high unmet need.