Computational biologist with over 20 years of experience analyzing complex biological data and deploying scalable infrastructure. Originally trained in molecular biology and genetics at Eötvös Loránd University, I transitioned to computational biology during my Master's studies and subsequently earned a PhD in Classical and Molecular Genetics, focusing on the evolutionary conservation of gene expression regulation. My career spans high-impact roles across agricultural biotechnology, cancer genomics, and molecular diagnostics, where I specialized in engineering end- to-end bioinformatics pipelines, developing novel analytical tools, and bridging the gap between dry-lab and wet-lab teams. Across these roles, I handled multi-terabyte datasets, analyzed hundreds of patient samples, and frequently managed research projects.

Available for consulting engagements, pipeline development or workflow auditing, to turn your next-generation sequencing results into actionable insights. Let’s discuss your project needs [link to Calendly].

Currently operating as an independent consultant, I partner with biotech startups, academic laboratories, and independent researchers to translate raw sequencing data into biological discoveries, utilizing R, Python, Snakemake, and cloud infrastructure (AWS/GCP). To complement my deep expertise in genomics and transcriptomics, I also hold a Master’s in Human Ecology. This unique combination allows me to apply systems-level thinking—integrating sociology, ecology, and data science—to complex biological problems, making me a highly adaptable partner for projects requiring both granular genetic analysis and macro-scale environmental or ecological context.

Experience

Bioinformatics Consultant | The Bioinformatics CRO (Orlando, Florida, US) December 2020 – Present

• Partnering with diverse clients to translate next-generation sequencing (NGS) data into biological insights, specializing in custom genomics and transcriptomics pipelines.

Bioinformatics Group Leader | Semmelweis University (Budapest, HU) September 2018 – December 2021

• Directed genomics and molecular diagnostics research initiatives, managed a dedicated bioinformatics team, mentored junior scientists, and instructed university-level data science courses.

Postdoctoral researcher | IFOM-ETS (Milan, IT) September 2015 – August 2018

• Analyzed complex genomic datasets to uncover mechanisms driving cancer and rare diseases; engineered novel biostatistical methods and software tools to model chromatin architecture.

Postdoctoral researcher | GRIB-UPF (Barcelona, ES) February 2012 – August 2015

• Processed large-scale cancer genomic and transcriptomic cohorts, developing a novel computational framework to detect transcript isoform and alternative splicing switches across tumor samples.

Bioinformatician | Agricultural Research Institute of the Hungarian Academy of Sciences (Martonvásár, HU) January 2006 – January 2012

• Spearheaded bioinformatics, biostatistics, and data visualization workflows supporting agricultural genomics and plant genetics. Advanced agritech initiatives through custom database integration and multi-omics analysis of non-model organisms.

PhD Candidate | Agricultural Biotechnology Center (Gödöllő, HU) September 2003 – August 2006

• Executed agricultural bioinformatics and biostatistical analyses, building and managing specialized databases and web-accessible tools to support high-throughput genomics research.

Education

MA in Human Ecology | Eötvös Loránd University 2021 – 2023

• Research focus: Modeling long-term landscape transformation in the Middle-Ipoly region by integrating quantitative GIS and meteorological datasets with qualitative interviews and historical source analysis.

PhD in Classical and Molecular Genetics | Eötvös Loránd University 2003 – 2006

• Research focus: Development of DoOP and DoOPSearch, web-based eukaryotic promoter motif search and enrichment tools for comparative genomics.

MSc in Biology | Eötvös Loránd University 1998 – 2003

• Research focus: Analysis of the evolutionary conservation of eukaryotic transcription factor binding sites and promoter regions.