Resume

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Nicholas C. Dorn

Computational Modeling, CFD & Medical Software Engineer

Summary

Computational biomechanics PhD candidate applying physics-based cardiovascular simulation and reduced-order modeling to improve surgical planning and reduce clinical uncertainty. Deliver validated software used in multi-institution modeling studies and drive engineering adoption for translational research.

Technical Skills

  • Languages & Tools: Python, C++, Swift, Bash, Git
  • Cardiovascular Modeling: CFD and 0D/1D cardiovascular modeling
  • Platforms: SimVascular, Linux/HPC (Slurm), profiling, CI/CD (GitHub Actions), unit testing
  • Data & ML: DICOM/VTK/ITK pipelines, NumPy/Pandas, scikit-learn, PyTorch
  • Methods: Optimization methods; numerical V&V practices for medical software

Experience

PhD Candidate, Cardiovascular Biomechanics Computation Lab

Stanford University Apr 2023 – Present
  • Created the first automated pipeline for adaptive pulmonary CFD boundary condition tuning in SimVascular, improving agreement with clinical pressure/flow data.
  • Built svZeroDTrees, enabling rapid microvascular boundary condition and impedance computation for 2 labs across 5+ studies.
  • Executed multi-patient HPC studies on Slurm with performance debugging to reduce runtime and improve stability.
  • Communicated modeling outcomes with clinicians to support adoption for patient-specific treatment planning.

Key Open-Source Contributions

  • svZeroDTrees | Core Developer: Automated boundary condition generation and built an end-to-end pipeline from image segmentation to predicted post-surgical hemodynamics.
  • svZeroDSolver | Core Contributor: Led 7+ merged issues/PRs improving CI robustness; mentored an undergraduate contributor; collaborate with 14+ developers across 3 institutions.

Undergraduate Researcher, Nanoscale Materials & Cell Engineering Lab

UC San Diego Sept 2019 – Jun 2022
  • Led in vivo and in vitro studies of a novel nanoparticle platform for delivering short-chain fatty acids to treat arthritis.
  • Published a co-first-author paper (30+ citations) and presented findings in three conference talks.

Software Projects

PacerBrain | iOS Performance Strategy App

SwiftUI, Core Data
  • Developed a pacing and fueling modeling app used for personal race planning and execution; demonstrated to 30+ peers with positive feedback.

Publications & Talks (Select)

  • Menon, Dorn et al. svZeroDSolver: A modular package for lumped-parameter cardiovascular simulations. JOSS, 2025.
  • Dorn et al. Modeling vascular adaptation for prediction of surgical outcomes in pulmonary stenosis repair. In preparation.
  • Dorn et al. Comparative CFD analysis in a sheep model of Fontan circulation. Talk, CMBBE 2025, Barcelona.
  • McBride*, Dorn* et al. Advanced Science, 2023; Drug Deliv. Transl. Res., 2022 (*co-first).

Education

  • MS & PhD, Chemical Engineering (Cardiovascular Biomechanics) — Stanford University (MS Jun 2025; PhD exp. 2027)
  • BS, Chemical Engineering (Minor: Mathematics) — UC San Diego (GPA 3.82; Jun 2022)

Awards & Leadership

  • NSF Graduate Research Fellow (2022–2025)
  • Vice President, Project Bluewater Racing — nonprofit cleaning up San Diego waterways and providing tuition-free science and sailing education to 100 students; improved website data capture and CRM integration (2023–present).
  • President, UCSD Sailing Team — led competition and operations for 40 athletes (2020–2022).