I specialize in co-developing and using quantitative models to help organizations make good decisions under uncertainty. I perform independent research to enable public and private sector stakeholders to make better choices about flood risk management, environmental policy, AI governance, and other issues. And I offer consulting services to organizations looking to develop or improve their own decision processes or stress-test processes, analytical methods, and models.
Consulting Services
Engagements range from a short independent review of an existing model to building and deploying a full decision-analysis framework. If you're not sure which of these you need, say so in an email and we'll work it out.
Problem Formulation
Translating messy real-world problems into concrete mathematical terms, and using insights from subject-matter experts with hands-on experience to build mathematical, statistical, and simulation models of the problem.
Decision Analysis Under Uncertainty
Evaluating the outcomes of strategic decisions quantitatively, with selective attention to the details that matter to your decision-making. When is there a surefire win, when is there a smart gamble, and when is it time to hedge your bets because the odds can't be predicted?
Independent Model Review & Validation
Quality-checks and validation to verify whether a model you have on hand is appropriate and reliable, and to help you understand its limitations. Useful before you stake a large investment—or a safety-critical decision—on someone else's numbers.
Simulation & Risk Modeling
Designing and deploying rigorous system models—statistical, probabilistic, simulation, ML—on cloud-native infrastructure (AWS, Databricks, Spark), with the automated, scalable tooling to make them tractable in production.
Making Sense of Model Output
Distilling big datasets of complex model results into actionable insights and coherent narratives using AI/ML data-mining techniques.
Participatory Modeling & Decision Processes
Running the modeling and analysis with the decision-makers in the room, gathering buy-in at each judgment call rather than handing down a recommendation nobody trusts.
Research Areas
These are the fields I've worked in and continue to publish on. Each has its own page with more detail and links to relevant work.
Flood Risk Analysis
I've spent a lot of time working on probabilistic flood risk analysis. That means coming up with a probabilistic model of severe storms and their behaviors, using physics-driven hydrodynamic simulations to estimate the flooding they produce, and evaluating the resulting damage to structures on the ground with and without mitigation investments. I'm also deeply concerned about the lack of mathematical rigor in the state of practice, and I write about it at length.
Deep Uncertainty in the Future Climate and Economy
Traditional methods for decision-making under uncertainty assume uncertain outcomes can always be modeled with a probability distribution. That's often not the case; sometimes all we can do is propose an upper and lower bound, shrug our shoulders, and say "it's probably somewhere in there." I'm specifically trained in deriving actionable insight anyway.
Stochastic Simulation
I have a particular interest in the evolution of random processes over time—soil moisture responding to evaporation, drainage, and random shocks of precipitation; small sandy islands eroding and accreting; disease transmission through a community; the drift of a buoy in the ocean or your rating on a competitive ladder.
Machine Learning & Theory-Grounded Feature Engineering
Deep neural networks are great, but you can get a lot of mileage and more interpretability out of feature engineering and other means of baking your problem structure into your modeling efforts. If you can build a reasonable structural model of your process and infer its theoretically grounded latent features with ML, you can make the problem much simpler.
Economic Modeling
I've spent a good amount of time on economic policy modeling using computable general equilibrium models—network models of microeconomic relationships between sectors and regions, solved for equilibrium or simulated dynamically. I have experience evaluating policy outcomes with these while leveraging principles from decision-making under uncertainty. Most recently, I co-authored a study in npj Climate Action finding that AI's fossil fuel applications outweigh its climate benefits.
Contact
Get in touch to discuss how I can help you design, improve, or quality-check your decision process or model.