Benchmarking Kendall's Tau in R and Rcpp
Implement and benchmark a fast Kendall’s tau-a in C++ via Rcpp against base R, discuss tie handling (tau-b), and when to move from R to C++.
PhD in Statistics
University of Sao Paulo
MSc in Statistics
University of Sao Paulo
BSc in Agricultural Engineering
University of Sao Paulo
As a Consultant Statistician at AbacusBio, I lead cross-functional teams that deliver genetic-evaluation pipelines, automated QC/ETL workflows, and decision dashboards for livestock, crop, and agri-tech partners. That work depends on production-grade code in R, C++, bash, and SQL, Docker-based reproducible environments, and early collaboration between domain scientists and data engineers.
Earlier, I held a Marie Sklodowska-Curie COFUND fellowship at the Roslin Institute (University of Edinburgh), worked with multidisciplinary research and industry teams, and lectured in statistics at USP. Along the way I have published across Nature-branded journals, advised national breeding programmes, and mentored teams on delivering transparent, auditable analyses for agriculture and genomics.
Whether the brief is accelerating genetic gain, improving farm-system resilience, or strengthening agricultural production systems, my bias is toward rigour, reproducibility, and decision-ready outputs. Browse my recent publications and projects, and get in touch if you would like to collaborate or have a specific challenge in mind.
Implement and benchmark a fast Kendall’s tau-a in C++ via Rcpp against base R, discuss tie handling (tau-b), and when to move from R to C++.
As a statistician, I teach SQL from zero using a realistic agriculture dataset: tables, keys, joins, summaries, quality checks, and a mini treatment-effect analysis.
what each tool solves, when to reach for it, and ready-to-paste code.
This post explores the performance of various compression techniques in R for reading and writing operations, highlighting file size, speed, and memory usage.
This post explores the performance of various data formats in R for reading and writing operations, highlighting file size, speed, and memory usage.
I focus on advanced statistical modelling, economic and sustainability selection indices, interactive dashboards, and reproducible (Dockerised) pipelines that deliver decision-ready insights for agriculture and genomics.
Agriculture. Design and analyse agronomic and farm-systems experiments, including multi-environment trials and spatial models, to optimise yield, resource use, and sustainability.
Genetics. Build genetic-evaluation pipelines and economic and sustainability selection indices that maximise genetic gain and inform breeding objectives.
Agri-tech analytics. Build practical decision-support tools that connect statistical modelling, data engineering, and stakeholder communication.
Explore my publications, projects, and recent work. If you are interested in collaborating or would like to learn more, please get in touch.
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