Demo Data from EDBT 2026 / reviewers in the wild / expert
Felix Wechsler
dblp:392/1571
· DBLP profile ↗
2ranked-venue papers
1as first author
2since 2021 · last 2026
0000-0001-8763-2948ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 2 · 1 first-author · 2 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer graphics and multimedia
2 papers |
Rendering · 45% Computational fabrication · 35% Computational photography and imaging · 20% | |
| Theoretical computer science
1 paper |
Mathematical optimization · 100% |
Topics — the 7 heaviest of 7, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computational fabrication
additive manufacturing |
1.8 | 2 | 2026 | Single-View Holographic Volumetric 3D Printing with Coupled Differentiable Wave-Optical and Photochemical Optimization · ACM Trans. Graph. 2026 Inverse Rendering for Tomographic Volumetric Additive Manufacturing · ACM Trans. Graph. 2024 |
Computational photography and imaging › holography
hologram generation |
1.0 | 1 | 2026 | Single-View Holographic Volumetric 3D Printing with Coupled Differentiable Wave-Optical and Photochemical Optimization · ACM Trans. Graph. 2026 |
Rendering
differentiable rendering |
0.8 | 1 | 2024 | Inverse Rendering for Tomographic Volumetric Additive Manufacturing · ACM Trans. Graph. 2024 |
Rendering › light transport
inverse light transport |
0.8 | 1 | 2024 | Inverse Rendering for Tomographic Volumetric Additive Manufacturing · ACM Trans. Graph. 2024 |
Rendering
inverse rendering |
0.8 | 1 | 2024 | Inverse Rendering for Tomographic Volumetric Additive Manufacturing · ACM Trans. Graph. 2024 |
Mathematical optimization › optimization for machine learning
differentiable optimization |
0.3 | 1 | 2026 | Single-View Holographic Volumetric 3D Printing with Coupled Differentiable Wave-Optical and Photochemical Optimization · ACM Trans. Graph. 2026 |
Mathematical optimization
inverse problems |
0.3 | 1 | 2026 | Single-View Holographic Volumetric 3D Printing with Coupled Differentiable Wave-Optical and Photochemical Optimization · ACM Trans. Graph. 2026 |
Methods — techniques the papers use, named apart from their topics
photochemical model · 2.0phase-only hologram optimization · 2.0differentiable wave-optical model · 2.0ray tracing · 0.8physically based differentiable rendering · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Single-View Holographic Volumetric 3D Printing with Coupled Differentiable Wave-Optical and Photochemical OptimizationabstractVolumetric additive manufacturing promises near-instantaneous fabrication of 3D objects, yet achieving high fidelity at the micro-scale remains challenging due to the complex interplay between optical diffraction and chemical effects. We present Single-View Holographic Volumetric Additive Manufacturing (SHVAM), a mechanically static system that shapes volumetric dose distributions using time-multiplexed, phase-only holograms projected from a single optical axis. To achieve high resolution with SHVAM, we formulate hologram synthesis as a coupled inverse problem, integrating a differentiable wave-optical forward model with a simplified photochemical model that explicitly captures inhibitor diffusion and non-linear dose response. Optimizing hologram sequences under these coupled constraints allows us to pre-compensate for chemical blur, yielding higher print fidelity than optical-only optimization. We demonstrate the efficacy of SHVAM by fabricating simple 2D and 3D structures with lateral feature sizes of approximately 10 μm within a 0.8 mm × 0.8 mm × 3 mm volume in seconds. Felix Wechsler, Riccardo Rizzo, Christophe Moser |
ACM Trans. Graph. | 1 |
| 2024 | Inverse Rendering for Tomographic Volumetric Additive ManufacturingabstractTomographic Volumetric Additive Manufacturing (TVAM) is an emerging 3D printing technology that can create complex objects in under a minute. The key idea is to project intense light patterns onto a rotating vial of photo-sensitive resin, causing polymerization where the cumulative dose of these patterns reaches the polymerization threshold. We formulate the pattern calculation as an inverse light transport problem and solve it via physically based differentiable rendering. In doing so, we address longstanding limitations of prior work by accurately modeling and correcting for scattering in composite resins, printing in non-symmetric vials, and supporting unusual printing geometries. We also introduce an improved discretization scheme that exploits the ray tracing operation to mitigate resolution-related artifacts in prints. We demonstrate the benefits of our method in real-world experiments, where our computed patterns produce prints with an improved fidelity. Baptiste Nicolet, Felix Wechsler, Jorge Madrid-Wolff, Christophe Moser, Wenzel Jakob |
ACM Trans. Graph. | 2 |