Biomedical evidence, software, infrastructure, and product delivery.
I work across genomics, multi-omics, clinical data, statistical inference, secure computing, and scientific software. My focus is the chain from evidence to usable systems: data structure, method, provenance, documentation, interface, governance, and decision support.
Professional profile: lawless.ch
Major commercial outputs: Switzerland Omics
Main academic outputs: ORCID · Google Scholar
Design and product systems: design.lawless.ch
I build verifiable analytical systems for precision medicine, diagnostics, biomarker research, and biomedical data infrastructure. I am especially interested in converting our basic research into sucessful products for biotech, pharma, and diagnostics. That work depends collaboration, infrastructure, documentation, IP awareness, regulatory judgement, and a clear understanding of how scientific products reach real users.
Core areas:
- Statistical genomics, Bayesian inference, and uncertainty quantification
- Rare disease, infectious disease, host genetics, and precision medicine
- Whole-genome sequencing, RNA-seq, proteomics, metabolomics, and EHR-linked data
- Reproducible R, Python, SQL, Linux, HPC, and cloud workflows
- Scientific software, structured reports, evidence databases, and product-facing systems
- Secure and governance-aware biomedical data infrastructure
My software and product work is grounded in academic and clinical research across genomics, immunology, infectious disease, rare disease, and translational medicine.
| Period | Institution | Focus |
|---|---|---|
| 2023 to present | Universitäts-Kinderspital Zürich and University of Zurich | Intensive care and neonatolgy, Translational medicine, paediatric critical care, clinical genomics, multi-omics, and secure biomedical data infrastructure |
| 2018 to 2023 | EPFL Global Health Institute | Fellay lab, Human genomics of infection and immunity, host-pathogen biology, statistical genetics, and translational cohort analysis |
| 2015 to 2019 | University of Leeds School of Medicine and St James’s University Hospital | PhD in Medicine, rare immune disease discovery, genomic interpretation, and functional validation |
| 2014 to 2015 | EPFL Global Health Institute | Ablasser lab, Innate Immunity |
| 2013 to 2014 | Trinity College Dublin | MSc Immunology, first class honours |
| 2009 to 2013 | University College Cork | BSc Microbiology, host-pathogen biology, and immunology |
Selected awards include the FKZ Children’s Research Centre research prize, Microsoft Azure Research Award, Wellcome Genome Campus visitor research grant, and University of Leeds postgraduate research scholarships.
| Output | Scope | Links |
|---|---|---|
| QuantBayes Studio | Evidence-based conclusions for AI, science, engineering, and regulated work | site |
| QuantBayes | Bayesian quantification of genomic evidence sufficiency with posterior intervals | site · article · CRAN · Zenodo |
| Archipelago | Variant set association statistics and visualisation for complex genomic studies | site · article · CRAN |
| VCFheader | VCF header parsing and structured standalone HTML reporting | site · browser · CRAN |
| Evidence ratio | Likelihood-based evidence scale for clinical trials, studies, and analytical results | site · CRAN |
| PanelAppRex AI | Harmonised disease-gene panels from structured clinical and genetic queries | site · article · repository · dataset |
| Qualifying variant database | Reusable YAML criteria for reproducible genomic variant interpretation | site · article |
| Genomic Vault | Long-term custody and controlled access for genomics and precision medicine | platform |
| IEI genetics database | Genetic panels and prior probabilities for disease-causing variants in inborn errors of immunity | site · article |
This account contains research code, R packages, analysis workflows, documentation sites, data products, and product prototypes.
Main repository areas:
- Statistical modelling, machine learning, and reproducible analysis
- Genomics, multi-omics, and biomedical evidence systems
- R and Python packages for scientific computing and reporting
- Secure data workflows, clinical research infrastructure, and structured outputs
- Web products, documentation systems, and scientific interfaces
Languages R · Python · SQL · Bash · C · Rust · TypeScript
Data WGS · RNA-seq · proteomics · metabolomics · EHR-linked data
Statistics Regression · Bayesian inference · machine learning · statistical learning · uncertainty quantification
Systems Linux · HPC · Docker · Apptainer · Nextflow · Snakemake
Platforms PostgreSQL · Supabase · Next.js · React · Vercel · APIs
AI retrieval · embeddings · structured extraction · agentic workflows
Governance provenance · auditability · secure data · GDPR/FADP · IVDR-aware workflows
