Statistician, combining research and practice for probabilistic and risk modelling in the earth sciences.
View CVI am a senior data scientist at BGC Engineering, specializing in practical and innovative probabilistic modeling. I combine advanced statistical methods with real-world applications, focusing on earth systems modelling, extreme events, and communication.
My research focuses on expanding how we answer the question, “What’s possible?”–not just “What’s most likely?” I draw on the strengths of both classical statistics and machine learning, building probabilistic models of complex, interdependent systems. My work often centers on understanding extremes in climate and hydrology, where I bridge theoretical innovation with practical application.
The following are research initiatives I’m leading.
Leverage a robust foundation in probability theory, extreme value modeling, and machine learning to craft novel methods tailored to real-world challenges.
Isolate and communicate multiple sources of uncertainty using a tailored mix of approaches.
Ensure that all models are grounded in reality, considering data availability, domain expertise, and end-user needs, avoiding over-engineered solutions.
Uphold best practices in computation, using version control, defensive programming, and clear documentation to deliver projects that are both reproducible and scalable.
Foster knowledge exchange with domain experts to understand the problem space deeply, ensuring that model results are interpretable, actionable, and presented clearly.
Design intuitive R packages and Shiny applications, making complex analyses accessible and empowering teams to conduct probabilistic modeling seamlessly.
Articles in scientific journals, proceedings, and preprints.
I’m curious about projects that push boundaries and could benefit from a fresh, statistically-driven approach. If that sounds like what you have in mind, I encourage you to connect with me.
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