David Cha

dblp:424/4562 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2025
0009-0003-1758-4946ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author · 1 since 2021Human-computer interaction and ubiquitous computing · 1 · 1 first-author · 1 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
1 paper
Computational fabrication · 50% Geometric modeling and processing · 50%
Theoretical computer science
1 paper
Mathematical optimization · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computational fabrication
computational design
0.912025
Computational Design of Shape-Aware Sieves · SIGGRAPH Asia 2025
Geometric modeling and processing
rigid transformation
0.912025
Computational Design of Shape-Aware Sieves · SIGGRAPH Asia 2025
Mathematical optimization
global optimization
0.312025
Computational Design of Shape-Aware Sieves · SIGGRAPH Asia 2025
Mathematical optimization › metaheuristic optimization › swarm intelligence
particle swarm optimization
0.312025
Computational Design of Shape-Aware Sieves · SIGGRAPH Asia 2025

Methods — techniques the papers use, named apart from their topics

particle swarm optimization · 1.7gradient-based optimization · 1.7differentiable rendering · 1.7
YearPublicationVenuePosition
2025 Computational Design of Shape-Aware Sieves
abstract
We introduce mathematical tools to describe the geometric problem of sieves, two-dimensional holes that admit certain three-dimensional objects to pass through them, but block others. This is achieved by formulating the sieve design problem as a two-player game where both players (the one that wants to pass, and the one that wants to block) try to find a set of rigid transformations to achieve their objective. We also introduce an algorithm for solving this game by solving a global optimization problem employing both differentiable rendering with gradient-based optimization as well as particle swarm optimization. Our procedure accounts for real-world manufacturing concerns, and we fabricate a variety of examples demonstrating the practical viability of our sieves. Our implementation takes advantage of GPUs and does not rely on any clean or manifold input geometry as long as it is a triangle mesh. We can produce intricate sieves that block an arbitrary set of shapes \(\mathcal {B}\) but admit another arbitrary set of shapes \(\mathcal {A}\) (if finding a solution is possible for our method).
David Cha, Oded Stein
SIGGRAPH Asia1