Clinical data becomes useful when it remains traceable, reusable, and reviewable.
Regulated biomedical work depends on secure data flow, reproducible analysis, traceable decisions, clear documentation, and outputs that support review, audit, and reuse.
My work connects clinical genomics, EHR-linked data, multi-omics, governance, secure compute, and structured reporting.
What this work resolves
Traceable evidence
Clinical data workflows need clear links between source data, processing, analysis, interpretation, and final output.
Secure reuse
Biomedical data becomes more valuable when it can be reused safely across research, clinical, governance, and translational contexts.
Regulated reporting
Reports, databases, pipelines, and documentation need enough structure to support review, quality control, and later audit.
Cross-functional delivery
Clinical infrastructure has to satisfy clinicians, data scientists, bioinformaticians, governance teams, software teams, and decision-makers at the same time.
Evidence at a glance
>1,000
patients in secure clinical genomic, multi-omic, and EHR-linked workflows
>100 TB
biomedical data managed through traceable analytical infrastructure
>10
hospitals connected through multi-institutional clinical research programmes
>CHF 6M
in combined national funding programmes
Methods, standards, and systems
Clinical data workflows
Patient-level data, EHR-linked workflows, phenotype-linked molecular data, cohort definition, missingness, data quality, and longitudinal data structures.
Secure infrastructure
High-performance computing, Unix, Linux, encrypted storage, controlled file transfer, AWS, Azure, Docker, Singularity or Apptainer, and structured data environments.
Regulated delivery
Good Clinical Practice, GLP-aware laboratory delivery, ICH-aligned documentation discipline, audit-ready workflows, traceability, version control, and quality records.
Analytical reproducibility
R, Python, Git, workflow automation, reproducible reports, machine-readable outputs, versioned pipelines, QC checks, and structured analytical documentation.
Biomedical systems
SQL, PostgreSQL, APIs, HTML reporting, Next.js, React, TypeScript, Supabase, authenticated systems, and user-facing scientific platforms.
Stakeholder translation
Clinical research, data governance, genomics, bioinformatics, data science, neonatology, intensive care, scientific leadership, and external partner coordination.
Selected publications
ORCID record:
0000-0001-8496-3725
Application of qualifying variants for genomic analysis.
Bioinformatics, 42(2), btaf676, 2026.
Germline TET2 loss of function causes childhood immunodeficiency and lymphoma.
Blood, 136(9), 1055-1066, 2020.
Biallelic mutations in calcium release activated channel regulator 2A (CRACR2A) cause a primary immunodeficiency disorder.
eLife, 10(), , 2021.
A case of adult-onset Still's disease caused by a novel splicing mutation in TNFAIP3 successfully treated with tocilizumab.
Frontiers in Immunology, 9(), , 2018.
Relevant experience
2023 to present · Universitäts-Kinderspital Zürich
Secure clinical genomics and data infrastructure
Designed analytical workflows and clinical research databases for paediatric critical care, rare disease, genomics, multi-omics, and EHR-linked research.
Approximately 1,000 children, more than 100 TB of biomedical data, three hospitals, SwissPedHealth National Data Stream, Swiss Pediatric Sepsis Study, governance-facing workflows.
2018 to 2023 · EPFL Global Health Institute
Translational cohort systems and analytical delivery
Built reproducible computational workflows for infectious, inflammatory, and translational studies across Swiss and international collaborators.
Cohorts up to 5,000 participants, multidisciplinary teams across EPFL, ETH Zürich, Swiss university hospitals, Swiss TPH, and international partners.
2014 to 2015 · ACM Global Laboratories
Regulated laboratory and clinical trial delivery
Delivered biomarker and assay workflows in a regulated bioanalytical laboratory serving global clinical trial programmes.
Quality-controlled assay delivery, documentation discipline, biomarker workflows, regulated laboratory operations, development-stage decision support.
Working fit
Clinical and regulated data teams need evidence systems that can be inspected, reused, and defended. The useful output is not only analysis, but a reliable chain from source data to structured decision support.