About Me

Summary

I'm a Master's student in Computer Science researching high-performance rendering for perceptual colourspace visualization with experience in GPU computing (CUDA, Metal, WebGPU, Vulkan). My work spans graphics rendering, ML systems, and scientific computing with applications to colour reproduction and colour vision deficiency. I'm seeking opportunities in graphics, deep learning, AR/VR, and large-scale computation.

If you happen to be looking for my work experience, see work. My personal projects can be found at projects.

This iteration of my website makes use of the Lume framework for Deno, as well as WebGPU.

Research Interests

Graphics, Deep Learning, Perceptual Computing, Scientific Visualization, High Performance Computing.

Skills

• GPU APIs: CUDA, WebGPU, Metal, Vulkan, OpenGL, OpenCL
• Languages: C, C++, Python, Rust, Haskell, TypeScript, Swift, WGSL, MSL, HLSL, Slang
• Libraries: PyTorch, NumPy, SciPy, OpenMP, MPI, Pthreads, Warp, SlangPy, BlenderPy
• Tools: RenderDoc, NSight, GDB, Valgrind, lldb, leaks, Perf, Unity, Git, Nix, Blender
• Other: SQL, WASM, FFI development

Education

• M.Sc. Computer Science @ University of Guelph
  • Expected: May 2025 - June 2027
  • Research focus: perceptual colour science and high-performance tools for research software quality
  • Supervised by Dr. Denis Nikitenko and Dr. David Flatla
  • Coursework: Scientific Computing, Artificial Intelligence
• Honours Bachelor of Computing @ University of Guelph
  • Graduated: September 2025
  • Area of Application in Mathematics
  • Deans list 2023 & 2024. Average: 78%
  • Research Assistant under Dr. Denis Nikitenko and Dr. David Flatla
• Relevant coursework:
  • CIS*6020 - Artificial Intelligence
  • MATH*6020 - Scientific Computing
  • CIS*4910 - Undergraduate Thesis
  • CIS*4800 - Computer Graphics
  • CIS*4780 - Computational Intelligence (Deep Learning)
  • CIS*3090 - Parallel Programming
  • MATH*3100 - Differential Equations II
  • MATH*4310 - Combinatorics and Graph Theory