Markus Worchel
Research Associate
Berlin, Germany
Summary
👤
Senior🎓
Top SchoolMarkus Worchel is a research associate in computer graphics at TU Berlin with 11 years of software and research experience focused on differentiable and real-time physically-based rendering. He has transitioned from industry-facing visualization and embedded systems work to academic research, contributing practical GPGPU and rendering expertise gained at Fraunhofer HHI and in automotive visualization projects. Markus contributes to open-source differentiable renderer projects—bringing Windows support, build-system and compiler fixes, and quality improvements—demonstrating a knack for making research code robust and cross-platform. His background combines hands-on engine implementation (deferred renderer, SSAO, SMAA/SSAA) with inverse graphics and differentiation techniques, enabling both applied and theoretical advances. Based in Berlin, he pairs rigorous academic training (MSc/BSc TU Berlin) with a pragmatic engineering eye for reproducible, production-ready research code.
11 years of coding experience
5 years of employment as a software developer
Bachelor of Science (B.Sc.), Bachelor of Science (B.Sc.) at Technische Universität Berlin
German, English
Stackoverflow
26reputation
500reached
1answer
0questions
Github Skills (13)
windows10
c-language10
cmake10
cprogramming-language10
msvcrt10
rendering9
render9
computer-graphics9
pytorch8
direct3d6
sharpdx6
directx6
tensorflow5
Programming languages (7)
Github contributions (5)
BachiLi/redner
Dec 2019 - Mar 2021
Differentiable rendering without approximation.
Role in this project:
Software Engineer
Software EngineerContributions:12 commits, 8 PRs, 31 comments in 1 year 3 months
Contributions summary:Markus contributed to the project by implementing support for Windows operating systems, which involved adapting build processes using CMake and integrating necessary dependencies. They addressed specific compiler issues, including MSVC replacements for GCC intrinsics and fixing the ffs intrinsic. Furthermore, the user made improvements to existing code by adjusting parameters and fixing assertions, such as for the normal maps and roughness values, demonstrating a focus on code quality.
pytorchdifferentiablecomputer-graphicscomputer-visionrendering
fraunhoferhhi/neural-deferred-shading
Mar 2022 - Jul 2022
Multi-View Mesh Reconstruction with Neural Deferred Shading (CVPR 2022)
Contributions:29 commits, 2 PRs, 25 pushes in 4 months
structure-from-motioncomputer-visioncvprdifferentiable-renderingmesh
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