Lukas Radl

Lukas Radl is a University Assistant and PhD Student at the Institute of Visual Computing, Graz University of Technology, where he works on 3D Scene Representations for View Synthesis under the supervision of Markus Steinberger. His research focuses on advancing real-time rendering techniques, particularly in Neural Radiance Fields (NeRF) and Gaussian Splatting, to bridge digital and physical world representation.

Education:

• Master of Science in Computer Science (with distinction), Graz University of Technology, 2018-2023
• Bachelor of Science in Software Engineering, Graz University of Technology, 2018-2023

Research Focus: Radl's work intersects Computer Graphics, Computer Vision, Machine Learning, and Parallel Processing. He pioneers practical implementations of Radiance Field Representations, addressing critical challenges in view consistency, anti-aliasing, and real-time performance for interactive applications. His innovations enable robust rendering in virtual reality and complex lighting scenarios through novel geometric and neural approaches.

Publication Impact: Recent publications (2024-2025) demonstrate a cohesive trajectory toward production-ready radiance field systems. Key advances include sorting algorithms for view consistency (StopThePop), anti-aliasing frameworks for Gaussian Splatting (AAA-Gaussians), and VR-optimized pipelines (VRSplat). These contributions establish new standards for real-time performance while maintaining visual fidelity across diverse hardware platforms.

Scientific Recognition:

• Dean's List (top 5% of students) at Graz University of Technology (2019, 2020)

Mentorship & Service: Radl actively shapes academic discourse as a reviewer for premier venues (CGF, ICCV, TVCG) and mentors students through open projects in real-time rendering. His teaching portfolio spans exercise coordination for core visual computing courses since 2020, with current leadership in Real-Time Graphics and Computer Graphics instruction. He fosters talent through student projects advancing Gaussian Splatting implementations.

Research Ecosystem: Embedded in Graz University of Technology's Institute of Visual Computing, Radl collaborates within a specialized team focused on radiance field optimization. The group maintains active pipelines for NeRF and Gaussian Splatting research, with strong industry connections evidenced by his upcoming Meta Reality Labs internship. Current projects target foveated rendering, geometric consistency, and editing capabilities for next-generation AR/VR systems.