Research Projects & Applications

Interactive tools, R packages, and research initiatives advancing statistical methodology in agricultural science

🌾 Interactive Applications

Web-based tools and dashboards for agricultural data analysis

Yield Response Curves (YRC) Project

Active

A comprehensive analysis platform for wheat and barley variety yield responses to disease pressure. This national collaboration with GRDC delivers quantitative information on crop resistance and yield relationships.

Key Features:

  • Multi-environment trial (MET) analysis results
  • Dynamic visualization tools for disease comparison
  • Export capabilities for graphs and tables
  • Regional pathogen prioritization

Partners:

Department of Primary Industries and Regional Development WA Department of Agriculture and Fisheries QLD Agriculture Victoria Department of Primary Industries NSW
🌐 Live Application

Crop Protection Analytics System

Internal Development

Jointly developed with CCDM and SAGI West, this system enables rapid and consistent analysis of disease impact economics.

Technologies:

shinydashboard shinyWidgets highcharter

GRDC Disease and Pest Impact Overview

Active

A visualization tool for understanding disease and pest impact on crop yield and profits, supporting agricultural decision-making.

📦 R Packages

Statistical software packages for research and analysis

V-Spline Package

Active

An adaptive V-spline implementation with Bayesian estimates for trajectory reconstruction from noisy GPS data.

Features:

  • Adaptive smoothing splines
  • Bayesian parameter estimation
  • GPS trajectory analysis
  • Real-time processing capabilities
🐙 GitHub Repository

🔬 Research Initiatives

Ongoing research projects and methodological developments

On-Farm Strip Trials Optimization

2020-2024
GRDC Funding

Research Question: Systematic vs. randomized design for on-farm experiments

Key Findings:

  • Systematic designs show superior efficiency in certain conditions
  • Spatial correlation modeling improves trial precision
  • Bayesian approaches provide robust uncertainty quantification

Publications:

  • "Optimal design for on-farm strip trials—systematic or randomised?" Field Crops Research (2024)
  • "Bayesian Inference of Spatially Correlated Random Parameters" Field Crops Research (2022)

Bayesian Workflow for Agricultural Data

2018-Present

Developing comprehensive Bayesian workflows for complex agricultural datasets.

Components:

  • Spatially correlated random effects modeling
  • MCMC diagnostics and convergence assessment
  • Prior specification and sensitivity analysis
  • Posterior predictive checking

Applications:

  • Crop yield prediction
  • Disease resistance assessment
  • Environmental impact analysis

Economic Analysis of Crop Protection

2022-2024

Quantifying the economic value of different crop protection strategies.

Analysis Areas:

  • Fungicide resistance impact assessment
  • Genetic improvement vs. chemical control comparison
  • Risk-benefit analysis for agricultural decisions

Publications:

  • "Economic analysis of crop protection strategies" Pest Management Science (2024)
  • "Socio-economic impact of fungicide resistance" Advances in Agronomy (2023)

🎓 Educational Initiatives

Platforms and tools for statistics education

Stats Journey Platform

Under Development

An interactive learning platform for statistics and data science education.

Features:

  • Interactive visualizations
  • Real-time calculations
  • Comprehensive coverage from basic stats to machine learning
  • Modern web technologies (React, TypeScript, Tailwind CSS)

Mission:

Making statistics accessible through intuitive visualizations and real-time simulations.

🌐 Stats Journey

📊 Statistical Methodologies

Advanced statistical methods and frameworks

Adaptive Sequential MCMC

Application: Combined state and parameter estimation for complex systems

Advantages:

  • Improved convergence properties
  • Efficient sampling for high-dimensional problems
  • Real-time parameter updates

Spatial Analysis Framework

Application: Agricultural field trials and environmental monitoring

Components:

  • Geostatistical modeling
  • Spatial correlation structures
  • Kriging and interpolation methods
  • Uncertainty quantification

Experimental Design Optimization

Application: Agricultural trials and industrial experiments

Methods:

  • Optimal design theory
  • Computer-generated designs
  • Response surface methodology
  • Robust design strategies

🤝 Collaboration Opportunities

Areas of interest for research partnerships

I'm always interested in new research collaborations and partnerships. Current areas of interest include:

🤖 Machine Learning in Agriculture

Integrating ML with traditional statistical methods

⚡ High-Performance Computing

Scaling statistical analyses for big data

🔧 Open Source Development

Contributing to the statistical software ecosystem

🏭 Industry Partnerships

Applied statistical solutions for agricultural challenges

Get in Touch: If you're interested in collaborating on any of these areas or have a specific project in mind, please reach out via email or LinkedIn.