Streaming Point Cloud Visualizer
Vulkan app that smoothly displays a city-scale 180 GB pointcloud
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Piotr Rybicki
I build high-performance software for GPU computing, robotics,
scientific applications, and large-scale visualization.
Selected work
Vulkan app that smoothly displays a city-scale 180 GB pointcloud
View projectRaytracing library allowing to simulate hundreds of LiDARs in realtime
View projectScientific tool for aligning scans, annotating neurons, and inspecting fluorescence signal
View projectCUDA CFD solver to inspect fluid flow around static 3D geometry
View projectBuilding GPU projects, including a viewer that renders a 180 GB, 13-billion-point scan at 120 FPS within a 4 GB GPU budget.
Implemented and validated low-level C++ features, including L1/L2 cache intrinsics, for a next-generation AI accelerator before silicon.
Led the architecture, API, GPU execution model, and performance of LiDAR simulation libraries capable of handling hundreds of LiDAR sensors in realtime
Reduced per-camera CPU use in the RealSense stack from 111% to 13%, enabling 16 cameras on one PC at 150 ms capture latency.
Built Python and Qt tools with neuroscientists to annotate and analyze two-photon microscopy data.
Worked on CUDA driver internals and developed memory-copy tooling that helped achieve up to 4× speedups.
Delivered a multi-GPU D3Q19 lattice Boltzmann solver, networking protocol, and real-time visualization client.
Built Gazebo simulations, integrated neural perception, and coauthored research on robust robotic grasping.
Parallelized protein-chain evolution on the GPU, reaching about 100× the CPU implementation's performance.
Got data that's outgrown your tools? That's my kind of problem.
Have a system to build, or want to talk shop over coffee in Warsaw? I'd be glad to hear from you.