Max Piochowiak, M.Sc. Max Piochowiak

Max Piochowiak, M.Sc.

  • Am Fasanengarten 5, Gebäude 50.34, 1. OG, 76131 Karlsruhe, Germany

Publications

SVDAG Compression for Segmentation Volume Path Tracing
Mirco Werner, Max Piochowiak, Carsten Dachsbacher

International Symposium on Vision, Modeling, and Visualization (VMV), 2024
Fast Compressed Segmentation Volumes for Scientific Visualization
Max Piochowiak, Carsten Dachsbacher

IEEE Transactions on Visualization and Computer Graphics (IEEE Vis23), 30(1), 2024: 12-22
Best Paper Award
Minimal Convolutional Neural Networks for Temporal Anti Aliasing
Killian Herveau, Max Piochowiak, Carsten Dachsbacher

High-Performance Graphics - Symposium Papers, 2023
Stochastic Volume Rendering of Multi-Phase SPH Data
Max Piochowiak, Tobias Rapp, Carsten Dachsbacher

Computer Graphics Forum, 40(1), 2021: 97-109

Projects

Helmholtz Project Pilot Program Core Informatics
HIDSS4Health logo Helmholtz Information & Data Science School for Health (HIDSS4Health)
ZIM Project Neural Networks for Temporal Anti-Aliasing with Enscape

 

Supervised Theses

2023 Two-Step Wave Function Collapse Bachelor Thesis
2023 Interactive Surface Rendering and Area Measurement for Cell Data Master Thesis
2023 Sparse voxel DAGs for Segmented Volumes Master Thesis
2022 Ambient Occlusion for Cell Growth Voxel Data Bachelor Thesis
2022 Optimizing interval trees for parallelized marching cubes Bachelor Thesis
2022 SGGX Microflake Distributions for Direct Volume Visualization Master Thesis
2022 Volumetric Compression for Cell Growth Simulations Bachelor Thesis
2021 Fast Velocity Computation and Denoising of Monte Carlo Renderings Master Thesis
2021 Visualizing Particles with Dye Injection Bachelor Thesis

Teaching

2024 Seminar Fortgeschrittene Algorithmen der Computergrafik  
2023 Übung zur Vorlesung Computergrafik  
2023 Übung zur Vorlesung Visualisierung  
2022 Proseminar Algorithmen für Computerspiele  
2022 Übung zur Vorlesung Visualisierung  
2021 Proseminar Algorithmen für Computerspiele  
2021 Übung zur Vorlesung Visualisierung  
2020 Übung zur Vorlesung Computergrafik   (Faculty award for best mandatory exercise)  
2020 Übung zur Vorlesung Visualisierung