I am a computational scientist studying complex biological dynamics in changing and human-influenced environments. Using mathematical and computational models, I advance theory on how ecological and evolutionary dynamics interact in human-dominated systems, and develop inference methods to connect this theory to data. I strive to produce actionable, policy-relevant science. For more details, see Research Themes, my Publications, or Google Scholar.
I am currently a Postdoctoral Fellow at Resources for the Future (RFF), a non-profit environmental economics research institute in Washington, DC. At RFF, I work on several projects funded by SESYNC modeling socio-environmental systems to inform policy and management.
My research and current work draw on my previous experiences:
- developing methods to parameterize demographic models from genomic data (with Brad Shaffer and Peter Ralph),
- building theory for how environmental stochasticity affects population persistence given eco-evolutionary dynamics (with Luis-Miguel Chevin and my Ph.D. supervisor Marissa Baskett,
- modeling the effects of coastal salmonid aquaculture on ecological and evolutionary dynamics of sea lice and wild salmon (with Marty Krkosek and my M.Sc. supervisor Mark Lewis).
Predictive tools for integrated socio-environmental systemsnetwork science, dynamical systems, optimization, machine learning
Management of freshwater-coupled human-natural systemsbioeconomic optimization, dynamical systems, decision processes, hydrological models
Inference in complex systemsmachine learning, agent-based models, Bayesian computing, genomic data
Eco-evolutionary dynamics in human-dominated systemsstochastic processes, dynamical systems, quantitative genetics
EFI2019 talk: Ecological forecasts for integrated socio-environmental systems (SES)
in EFI Conference presentation / / /
Optimal investment to enable evolutionary rescue
in Theoretical Ecology / / /
Efficient pedigree recording for fast population genetics simulation
in PLoS Computational Biology / / /
The mechanisms of phenology: the patterns and processes of phenological shifts
in Ecological Monographs / / /
Demographic inference in a spatially-explicit ecological model from genomic data: a proof of concept for the Mojave Desert Tortoise
in bioRxiV / / /
- So, you did some GLMs & compared with AIC. Congrats!
- Easy alternatives to bar charts in native R graphics
- Visualizing fits, inference, implications of (G)LMMs