Expertise
Four core areas of expertise spanning analytics, workflows, modeling, and digital transformation; and currently also exploring AI for life sciences.
Multi-omics Analytics
I leverage high-throughput sequencing and omics technologies to understand biological systems, identify disease mechanisms, and generate actionable hypotheses for research and drug discovery. My experience spans the complete analytical lifecycle: from experimental design and quality control through statistical analysis, biological interpretation, and visualization.
Areas of experience
RNA sequencing (bulk and small RNA-seq), ChIP-seq and transcription factor binding analysis, ATAC-seq and chromatin accessibility analysis, Whole genome sequencing, Comparative transcriptomics, Differential expression analysis, Functional enrichment and pathway analysis, Variant annotation and interpretation, Multi-omics data integration
Applications
Biomarker discovery, Target identification, Disease mechanism characterization, Gene regulatory analysis, Comparative biology and evolution
Bioinformatics Workflows & Platforms
I design, implement, validate, and document scalable bioinformatics workflows that enable reproducible and efficient analysis of large-scale biological datasets. My focus is not only on analysis, but also on making analyses repeatable, maintainable, and deployable across research teams and computing environments.
Areas of experience
Nextflow workflow development, nf-core pipelines, Workflow orchestration, Cloud-native bioinformatics solutions, Containerized scientific workflows, Pipeline validation and benchmarking, Bioinformatics platform architecture, CI/CD for scientific software
Technologies
Nextflow, Seqera Platform, Docker, GitHub Actions, Azure DevOps, AWS, Google Cloud Platform, R, Python, Bash, MATLAB
Applications
Production-scale omics analysis, Cloud migration initiatives, Scientific workflow modernization, Research computing infrastructure
Systems Biology & Computational Modeling
My research training was grounded in systems biology, where the goal is to understand how biological behavior emerges from interactions between genes, proteins, pathways, and cells.
I use computational models to move beyond descriptive analysis and investigate biological mechanisms.
Areas of experience
Gene regulatory networks, Biological network reconstruction, Boolean modeling, Ordinary differential equation (ODE) modeling, Sensitivity analysis, Parameter estimation, Mechanistic hypothesis generation
Applications
Cell fate regulation, Signal transduction, Post-translational modification networks, Complex disease mechanisms, Systems-level interpretation of omics data
Pharma R&D Digital Transformation
I help pharmaceutical organizations assess and improve how scientific data, workflows, and laboratory operations support research productivity.
My recent work has focused on understanding how digital technologies can accelerate drug discovery by improving data accessibility, workflow efficiency, and scientific collaboration.
Areas of experience
Laboratory digital maturity assessments, Data strategy and governance, Workflow digitalization, Scientific data integration, FAIR data principles, Laboratory automation strategy, Scientific software evaluation, R&D technology roadmapping
Applications
Connected laboratories, Data democratization, Digital laboratory transformation, Research workflow optimization, Productivity improvement initiatives
Current Exploration: AI for Life Sciences
I am actively tracking and exploring how artificial intelligence can support scientific productivity through AI-assisted data analysis, knowledge extraction from literature, and emerging agentic systems for bioinformatics workflows.
Areas of interest
AI-assisted bioinformatics, Knowledge extraction from scientific literature, AI-driven workflow automation
Certifications
- AI-Empowered SAFe 6 Scrum Master — Scaled Agile, Inc.
- AI-Empowered SAFe 6 Product Owner/Product Manager — Scaled Agile, Inc.