Independent quantitative science for clients who need findings that are defensible, rigorous, and honest.
Age-structured models, state-space models, statistical catch-at-age, stock-reduction analysis, and data-limited methods.
Harvest control rule design, management strategy evaluation, biological reference points, and tradeoff analysis under uncertainty.
Bayesian hierarchical models, spatial and spatiotemporal modeling frameworks, mixed-effects models, MCMC, TMB/RTMB/Stan. Fully reproducible pipelines.
Code audits, assessment reviews, and second opinions on quantitative work. Especially useful when existing analyses may have undetected errors or structural problems.
Workshop design and delivery for agency, tribal, and academic partners. Advanced statistical methods and R programming for applied ecologists & fisheries scientists.
Conversion of legacy assessment code from ADMB and TMB to RTMB, with hands-on training so your team owns and understands the resulting workflows.
Over 15 years of applied quantitative science in support of agencies, tribal nations, industry, and academia.
My value to clients is simple: I offer senior quantitative expertise dedicated to your problem. I keep my project load small so that I can deeply engage with the work and deliver clear, honest, and effective analysis when the stakes are high and the problems are complex.
I am an independent quantitative scientist with expertise in stock assessment, population dynamics, and ecological and statistical modeling. I provide clear, rigorous, and defensible analysis for fisheries management, harvest policy design, and complex resource management and ecological modeling challenges. My work spans the Great Lakes, British Columbia coast, Arctic Canada, Alberta, and beyond.
Before independent consulting, I was Associate Director and Assistant Professor at the Quantitative Fisheries Center at Michigan State University, a Postdoctoral Researcher at Simon Fraser University, and a consultant and applied scientist working alongside Alberta Environment and Parks, Fisheries and Oceans Canada, and industry partners.
Making stock assessment accessible — without sacrificing rigor.
RTMB is a native R implementation of Template Model Builder that makes state-of-the-art statistical estimation available to anyone who can write R — no C++ required. I am one of its earliest and most active practitioners, and I believe wider adoption makes fisheries science and quantitative ecology more transparent, reproducible, and equitable.
Legacy assessment code written in ADMB or TMB is often opaque to the biologists and managers who depend on it. When only one or two people in an organization can read or modify a model, that model can become a liability — especially when staff turn over or errors go undetected. RTMB changes that. Models written in RTMB are readable, auditable, and maintainable by a much broader community of scientists.
I convert legacy assessment models to RTMB and train the people who maintain them. The goal is not just working code — it is code that your team understands, owns, and can critique and defend.
I translated the book Spatio-Temporal Models for Ecologists (CRC Press, Authors: Dr. James Thorson and Dr. Kasper Kristensen) to RTMB. I led the conversion of all modeling examples from TMB to RTMB, making the material accessible to a new generation of ecologists and fisheries scientists. Public code is available at: github.com/spacetime-ecologist/spacetime-ecologists-RTMB.
Consulting CV — updated May 2026.
The best engagements start with a conversation about what you need.
I work with government agencies, tribal nations, academic partners, NGOs, and industry on problems that require deep quantitative expertise. A few sentences about the problem and your timeline are usually enough to tell if I'm the right fit — drop me a line.