Dylan Esguerra
Research Scientist Engineer | Quantitative Systems Pharmacology & Mathematical Modeling | Alzheimer’s Disease • Dynamical Systems • Scientific Computing • Data Science
- Role
- Research Scientist Engineer 2 at UW Medicine
- Location
- Seattle, WA, US
- LinkedIn followers
- 500 followers
About Dylan Esguerra
Currently at UW Medicine, I develop Quantitative Systems Pharmacology (QSP) and PKPD models informing therapeutic development programs in neurodegeneration. My work sits at the intersection of applied mathematics, systems biology, and high-performance scientific computing, using tools like Python, JAX, and SBML to bridge mechanistic modeling with data-driven inference.My MS thesis in Statistical Science (UCSC) introduced a nonparametric forecasting algorithm for noisy nonlinear dynamical systems, now published in Methods in Ecology and Evolution.
Experience
Research Scientist Engineer 2
Jan 2025 — Present · Seattle, WA, US
Led development of a multi-scale mechanistic Quantitative Systems Pharmacology (QSP) and PKPD model for Alzheimer\'s disease; simulations informed disease progression and drug effect in a therapeutic development program.Prototyped and scaled novel computational methods by integrating the Diffrax solver suite into the SBML-to-ODE-JAX library, improving performance for stiff systems.Parameterized Quantitative Systems Pharmacology (QSP) models using: Nelder-Mead, Differential Evolution, on positron emission tomography (PET) imaging data and other biomarkersDeveloped data visualization and analysis pipelines (pandas, matplotlib, seaborn) to quantify protein turnover and clearance rates in the CNS, contributing to a peer-reviewed publication on hydrocephalus.Contributed to software development for a simulation modeling mass transport in the brain, utilizing Python scripting and 3D neuron meshes for a simulation modeling mass transport in the brain.Collaborated with the UW Center for Reproducible Biomedical Modeling to ensure reproducibility best practices for scientific computing Collaborate with international Roche modeling teams to deliver emerging Systems Biology modeling tools (Python/SBML/XML/Antimony); championed text-based, non-GUI frameworks to ensure compatibility with AI coding agents and automated discovery pipelines; built an open-source MCP server exposing BioModels search and Antimony retrieval to LLM agents.Maintained rigorous version control practices and reproducibility standards using Git/GitHub, ensuring all modeling code met scientific computing best practices for collaborative research
Education
University of California, Santa Cruz
Bachelor of Arts - BA, Math/Economics
2018 — 2022
University of California, Santa Cruz
Master of Science - MS, Statistics
2021 — 2023
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