For Scientists
Featured Talks
Full list in my CV →
Archived Talks
Climate Invariant Machine Learning with Dan Li, NASA GISS, Feb 2024 Read More →
What I Offer to Scientific Collaborators
- Robustness reasoning: Explaining why agreement and disagreement across models can each provide insight—how convergence boosts confidence, and how divergence points to hidden mechanisms or new knowledge.
- Model evaluation: Developing conceptual tools for explaining model biases, interpreting ensemble spread, and showing how even “worse” models can play a constructive role in constraining estimates and resolving discrepancies.
- Philosophical integration: Bringing frameworks from philosophy of science (robustness, pursuit-worthiness, levels of understanding) into day-to-day scientific practice in climate and Earth system modeling.
- Decision support: Helping connect model-based insights to real-world contexts—turning technical evaluations of uncertainty into actionable guidance for policymakers, funders, and interdisciplinary teams.
- Encouraging reflection and big-picture thinking: Creating space for scientists to step back, examine their everyday practices, and see how conceptual clarity can sharpen both individual projects and collective research agendas.
Ongoing Collaborations
I have worked with scientists at NASA GISS, NCAR, Cornell University, and Indiana University, helping refine how models are evaluated and how uncertainty is communicated.
Let’s collaborate
Updated: September 5, 2025