About Me
Most people who build genomics pipelines have never had to sign off a lab result. I spent over a decade in clinical laboratories, first as a clinical microbiologist and then managing laboratories across 26 regional sites, before I started building pipelines and models. So I know how clinical data is made, and where and why it goes wrong. That judgment shapes everything I build.
Today I build clinical genomics pipelines, from raw sequencing reads to benchmarked variant calls and finished clinical-style reports, and I apply machine learning to genomic and microbial data. I’m looking for clinical bioinformatics roles in Ankara in clinical genetics, molecular pathology or public-health microbiology.
How I work
- Benchmarked, not just run. Every pipeline is measured against public truth sets (GIAB, SEQC2), with accuracy broken down by genomic context, the way clinical lab validation expects.
- Reports are part of the pipeline. Each repo generates a clinical-style PDF report, and every number in it comes from the pipeline’s own output.
- Built for the person running it. QC gates catch real biological problems, outputs fit clinical reporting workflows, and documentation is written for the analyst as well as the developer.
- Public or simulated data only. No patient data, ever.
See the portfolio for how this works in practice.
Toolbox
- Genomics: WGS/WES analysis, germline and somatic variant calling, CNV/SV, trio and ROH analysis, bacterial assembly and typing, AMR tools
- Clinical interpretation: ACMG/AMP, ClinGen CNV (2020), AMP/ASCO/CAP somatic tiers, CPIC pharmacogenomics, EUCAST
- Benchmarking: GIAB, SEQC2, hap.py, som.py, truvari
- Machine learning: PyTorch, Hugging Face Transformers, DNABERT-2, scikit-learn, XGBoost/LightGBM, Optuna, SHAP
- Engineering: Python, R, Nextflow, Snakemake, Docker, conda/mamba, uv, pytest, GitHub Actions, SQL/PostgreSQL, Bash
- Laboratory: culture and PCR diagnostics, bioMérieux VITEK, quality management systems, laboratory data and ETL reporting (PostgreSQL, Apache Superset)
Experience
Project Manager, Spektr Med
- Project planning: estimated the future needs of microbiology laboratories and defined the project goals and required results.
- Equipment: helped procure bioMérieux instruments and managed their installation in the laboratories.
- Training: organised and supervised training for laboratory staff.
Medical Laboratory Manager, Medikus Clinic
- Clinical operations: set up new PCR and molecular testing units from scratch.
- Standardisation: organised the testing workflow across 26 regional sites so every laboratory followed the same SOPs and guidelines under a state tender.
- Quality and team leadership: created and applied a Quality Management System; hired, trained and managed the laboratory team.
- Supply management: improved ordering and delivery of medical supplies so every facility always had the reagents it needed.
- Data and analytics: built ETL pipelines with PostgreSQL and Apache Superset to collect laboratory data and produce performance reports.
Clinical Microbiologist, Medican Hospital
- Pathogen identification: identified bacteria and viruses with culture methods and PCR.
- Automated testing: used VITEK systems for fast bacterial identification and antimicrobial susceptibility testing.
- Clinical support: interpreted results and reported them to physicians to guide antibiotic treatment.
- Quality control: applied strict quality and safety rules to manual and automated testing.
Clinical Microbiologist, Ministry of Defence of the Republic of Azerbaijan
- Pathogen identification: identified disease-causing bacteria and viruses with culture methods and PCR.
- Data reporting: analysed health and disease data with Excel and Python to produce reports for medical teams.
- Disease prevention: worked with military health teams on infection control, vaccination programmes and outbreak prevention.
Education
MSc Bioinformatics, University of Birmingham
Dissertation: Interpretable Deep-Learning and Ensemble Models for Predicting Multidrug Resistance in Klebsiella pneumoniae.
Coursework: Python and R programming, probability and statistics, genomics and next-generation sequencing, statistical machine learning, health data analytics, systems biology.
BSc Clinical Microbiology, Azerbaijan Medical University
Certifications
- Deep Learning Specialization, DeepLearning.AI, September 2026 · Credential SPROBJSVGUZA
- Machine Learning Specialization, DeepLearning.AI & Stanford University, April 2026 · Credential 2HOQQW7M2TOO
Languages
- Azerbaijani: Native
- English: Full professional proficiency