Applying mathematics to find patterns in high-dimensional single cell data. By quantifying immune cell population compositions -- by cluster, or cell subset type -- in patient samples of blood or tissue, we gain deeper, more precise understanding of patient differences, in terms of measures of clinical outcome and success.

Built high-performance, high-fidelity computational pipelines for integrating and clustering scores of batches of (moderately) high-dimensional cytometry data (e.g., ~20 dimensions in flow cytometry or ~ 50 dimensions in CyTOF data). The cells belong to participants in large-cohort, longitudinal clinical studies of disease, or vaccination, and the cell snapshots provide estimates of the respective amounts of 20+ different surface protein complexes on every cell. Using respective cluster frequencies over time, per participant and per blood (or per tissue) sample, we quantify phenotypic and functional immune cell responses to infection, vaccination and/or disease, in relation to clinical information on the individuals participating in a given study.At Fred Hutchinson Cancer Center, in the Evan Newell Lab, I've applied statistical learning, computational science, and mathematics to arrive at dimensionality reduction and clustering routines effective for integrating batches of cytometry data for a growing list of biological contexts (e.g., COVID, acute leukemia, CAR T immunotherapy). Cluster validation and verification is paramount, and there remains room for advancing aspects of quantitative systems immunology in this respect.

Research, data analysis and policy analysis, including financial and regulatory aspects of expanded fossil fuel production and consumption. Highlights: Authored sections incorporated in Gov. Inslee's presidential campaign climate plan documents; Co-authored article examining ways in which grassroots divestment pressure is absorbed by multinational banks. Tools: R; Python

Expand and apply technical knowledge and understanding of the U.S. energy system, the U.S. financial system, regulatory policy, climate science, geology and political economy in support of organization campaigns; Assemble and analyze datasets and narratives to identify and track business and finance trends and patterns, in quantitative and qualitative terms.

Combine broad scientific knowledge and fluency, research skills, and communication skills to help inform Senator Menendez and senior staff on diverse energy and environmental policy issues and meet constituent concerns.

Methods and areas: numerical analysis of partial differential equations and inverse problems (dynamical systems, functional analysis, finite elements, parameter identification); stochastic processes and uncertainty quantification for multi-scale modeling (reduced-order modeling, polynomial chaos expansions, sparse-sampling of high-dimensional spaces). [Languages: Fortran; C++; Matlab; Python]Collaborated across scientific disciplines to develop applied mathematics and computational science ideas and tools for advancing understanding, and published and presented research findings focused on questions about neuron production from neural stem cells. Designed and taught graduate and undergraduate courses in functional analysis, undergraduate analysis, mathematical biology, and engineering calculus; advised and managed graduate and undergraduate student projects, served on faculty committees, and organized seminars.

Developed software in Matlab for modeling genomic diversification of neurons from neural progenitor cells as a numerical stochastic branching process.

Studied stochastic PDE’s, uncertainty quantification, and reduced-order modeling; Researched molecular-level factors in cell cycle and cell fate control during development; participated in lab meetings, giving informal research presentations and mentoring graduate and undergraduate students; developed and taught undergraduate course in numerical analysis; volunteered tutoring "at-risk" middle school students in pre-algebra and algebra.

Helped formulate and build a multi-scale mathematical model of neurotransmitter diffusion and reaction at the junction between nerve and muscle cells, and published and presented research; initiated research on the mechanisms of neuron production during development.