Linas Beresna

Vancouver, Canada

Education

PhD in Computer Graphics

Simon Fraser University, Canada

Supervised by Eugene Fiume.

MEng Computer Science and Mathematics

University College London, UK

Graduated with first-class honours. Exchange at University of Waterloo, Canada (2017–2018).

Technical Skills

AdvancedC++, gdb, Linux, Python, Mitsuba
IntermediateGit, OSL, USD
Basic KnowledgeHoudini, Maya, JavaScript, OpenGL, Qt

Experience

Part-time Rendering Engineer

Image Engine Design · Vancouver, Canada

  • Supporting lighting and lookdev departments by maintaining legacy software and Gaffer integration.
  • Developing and optimising rendering tools using C++, Python, and OSL.
Research Intern – Digital Humans

Disney Research Zurich · Zurich, Switzerland

  • Conducted research and development within the Digital Humans team.
RnD Rendering Engineer

Animal Logic · Sydney, Australia

  • Built and supported the proprietary renderer Glimpse using C++14, USD, and OptiX.
  • Created artist-facing tools and shaders for Maya, Houdini, and in-house applications.
RnD Software Engineer – On-Set Tools

DNEG · London, UK

  • Created and supported tools for the shoot department to automate importing and sorting large datasets.
  • Developed cross-platform applications using C++, Python, and Qt.
Software Engineer Intern

Gambit Research · London, UK

  • Redesigned user-input logging services, migrating the codebase from Node.js to Python.
  • Utilised Docker and Kubernetes for containerised deployment.
Research Intern

UCL – Surgical Robot Vision Group · London, UK

  • Investigated binary classification for cancer cells using Deep Learning (TensorFlow).
  • Automated microscope hardware using C++ and OpenCV for edge detection and auto-focusing.

Publications

  • Neary-Zajiczek, L.,Beresna, L., et al. (2023). Minimum resolution requirements of digital pathology images for accurate classification.Medical Image Analysis, 89:102891. [PubMed]