CV

Contact Information

Name Falk Wiegmann
Professional Title PhD student, Department of Physics & Astronomy, University of British Columbia
Email [email protected]

Professional Summary

In my research, I build and evaluate neural-network-based reconstruction algorithms for preclinical micro-CT scans (NeRF, hash-grid and Gaussian-splatting style methods), alongside work on cone-beam reconstruction and image-quality analysis. My wider interests are in neural-network applications, medical images, financial markets, and the news.

Experience

  • 2023 - present

    Vancouver, BC, Canada

    Graduate Research Assistant
    The University of British Columbia
    • Ford Lab, Department of Physics & Astronomy — micro-CT reconstruction and image-quality research.
  • 2023 - 2026

    Vancouver, BC, Canada

    Teaching Assistant, Department of Physics & Astronomy
    The University of British Columbia
    • Jan – May 2026 — PHYS 545, Anatomy, Physiology and Statistics for Medical Physicists.
    • Jan – May 2025 — PHYS 158, Introductory Physics for Engineers II (Head TA).
    • Sep – Dec 2024 — PHYS 157, Introductory Physics for Engineers I.
    • May – Aug 2024 — PHYS 100, Introductory Physics.
    • Jan – Apr 2024 — PHYS 158, Introductory Physics for Engineers II.
    • Sep – Dec 2023 — PHYS 157, Introductory Physics for Engineers I.

Education

  • 2023 - 2027

    Vancouver, BC, Canada

    Doctor of Philosophy (PhD)
    The University of British Columbia
    Medical Physics
    • Ford Lab, Department of Physics & Astronomy. Research on building and evaluating neural-network-based reconstruction algorithms for preclinical micro-CT scans (NeRF, hash-grid and Gaussian-splatting style algorithms).
    • Completed all required CAMPEP-accredited coursework with a course average of 89%.
    • Activities and societies — UBC Surf Club.
  • 2019 - 2023

    Manchester, United Kingdom

    Integrated Master of Physics (MPhys)
    The University of Manchester
    Physics
    • First-class honours.
    • Master thesis on neural-network-based methods for image segmentation of organs at risk during radiotherapy.
  • 2018

    Perth, Australia

    International Baccalaureate Diploma
    Scotch College
    • 40/45 points.

Publications

2026

  1. Resolution–noise characteristics of common FDK filter kernels: A practical reference for preclinical cone-beam micro-CT
    Falk L. Wiegmann and Nancy L. Ford
    PLOS One, 21(8), e0349360. doi:10.1371/journal.pone.0349360
  2. Reconstruction-independent resolution limits in preclinical cone-beam micro-CT: A closed-form analysis
    Falk L. Wiegmann and Nancy L. Ford
    arXiv preprint arXiv:2607.12998
  3. Impact of Gaussian feathering on diagnostic metrics in tile-based micro-CT sinogram infilling
    Falk L. Wiegmann and Nancy L. Ford
    Scientific Reports. doi:10.1038/s41598-026-57319-2
  4. µPIU-Net: A domain-specific sinogram infilling U-Net for micro-CBCT and the limitations of generalized models
    Falk L. Wiegmann and Nancy L. Ford
    Research Square preprint. doi:10.21203/rs.3.rs-8768201/v1
  5. Visualising Parker weighting in short-scan cone-beam micro-CT: A practical reference
    Falk L. Wiegmann and Nancy L. Ford
    arXiv preprint arXiv:2604.23390
  6. Benchmarking open-source FDK against commercial and iterative reconstruction methods for preclinical micro-CBCT
    Falk L. Wiegmann and Nancy L. Ford
    arXiv preprint arXiv:2604.23047

Skills

Research: Deep learning, large-scale data analysis, neural-network-based image reconstruction (NeRF, hash-grid, Gaussian splatting), cone-beam CT reconstruction (FDK, iterative), image-quality metrics (MTF, NPS, NEQ), ideal-observer models
Programming: Python (NumPy, PyTorch), C++, TypeScript, LaTeX

Certificates

  • Private Pilot License - Federal Aviation Administration, USA
  • Recreational Skipper’s Ticket - Department of Transport, Western Australia
  • Driver’s licence (car and motorbike) - Government of British Columbia, Canada