Project Portfolio
May 19, 2024
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1 min read
My project work spans breeding analytics, reproducible software, and sports/public-health modelling. The table below highlights recurring domains, while the later sections point to specific deliverables and where to find code or publications.
Snapshot
| Domain | What I deliver the most |
|---|---|
| Agriculture & genetics | Spatial/multilevel models, genetic-evaluation pipelines, economic & sustainability selection indexes. |
| Sports & health | Athlete-performance analytics, ON score dashboards, COVID-19 forecasting pipelines. |
| Tooling | Reproducible analytics stacks (R/C++/Docker), R packages (matrixCorr, AlphaPart, AGHmatrix), Shiny apps. |
Current highlights
| Project | Theme | Outcome & references |
|---|---|---|
| Correlation & concordance research (matrixCorr + lcc) | Statistical methods | Unified correlation/association package and longitudinal agreement framework. → R Packages section |
| Drivers of genetic change | Breeding analytics | Partitioned genetic mean/variance, delivered management scenarios. → Pipelines section |
| Reads2Map & AlphaPart tooling | GBS pipelines | Package + Docker image adopted in linkage-map studies. → R Packages / Pipelines |
| Sustainability indexes | GHG & methane | Decision-ready dashboards and indexes for breeding clients. |
| Oliveira–Newell score | Sports analytics | Multilevel NBA evaluation framework validated across seasons. |
How to explore
- R Packages: matrixCorr, AlphaPart, AGHmatrix, AlphaSimR, lcc, Reads2Map Tools.
- Pipelines: DAG-based animal models, Additive-variance analysis, COVID-19 forecasting, ON score scripts, AlphaPart variance workflows.
- Completed/Discontinued: Historical detail and publications for archived initiatives.