Computational biologist and biomedical engineer focused on aging, longevity, and translational multi-omics research.
I develop reproducible computational workflows for evaluating aging-related biological signals, with particular attention to:
- Multi-omics and single-cell analysis
- Aging biomarkers and intervention response
- Evidence grading and uncertainty
- Reproducible scientific software
- Biologically responsible interpretation
A reproducible workflow integrating transcriptomics, plasma proteomics, and methylation data to evaluate rejuvenation-associated signals in primates.
The project emphasizes cross-validation, multimodal concordance, data-linkage auditing, sensitivity analyses, and explicit limits on causal interpretation.
A reproducible single-cell workflow for studying age-associated changes in immune-cell composition, molecular signatures, and predictive patterns in human PBMC data.
The project uses scVI, Snakemake, age-associated signature analysis, and model evaluation on real-world public data.
An auditable comparative-genomics workflow for evaluating candidate mechanisms associated with extreme vertebrate longevity.
The project emphasizes orthology, annotation quality, evidence tiers, artifact detection, provenance, and claim-level traceability.
My current focus is computational geroscience: connecting aging biology, multi-omics data, biomarker validation, and reproducible analysis to support more credible evaluation of healthspan interventions.
I am particularly interested in methods that make aging-related evidence more comparable across cohorts, populations, and translational environments.
Python · R · Snakemake · scVI · Scanpy · Statistical modeling · RNA-seq · Single-cell analysis · Multi-omics integration · Reproducible research
Reproducibility · Claim discipline · Transparent uncertainty · Biological interpretation · Collaboration-ready outputs