(generated by CPMIS)
Assoc. Prof. Pizzanu Kanongchaiyos, Ph.D.
Associate Professor, Department of Computer Engineering
Faculty of Engineering, Chulalongkorn University, Thailand
Assoc. Prof. Pizzanu Kanongchaiyos is a researcher in Computer
Graphics and Visual Computing, with more than two decades of research
experience spanning geometric modeling, computer animation, 3D
visualization, computer vision, and AI-driven visual computing.
His research focuses on developing computational methods for
understanding, representing, reconstructing, simulating, and visualizing
complex geometric and visual information. His work lies at the intersection
of Computer Graphics, Computational Geometry, Computer Vision,
Artificial Intelligence, and Scientific Visualization, with an emphasis on
geometry-aware and topology-aware approaches to intelligent 3D computing.
– Computer Graphics and Visual Computing
– Geometric and Topological Modeling
– 3D Reconstruction and Differentiable Geometry
– Topology-Aware 3D Computing
– Computer Animation and Motion Modeling
– Computer Vision and AI for Visual Understanding
– 3D Visualization and Scientific Visualization
– Digital Twins and Intelligent 3D Systems
– AI-assisted Graphics and Visual Computing
– Interactive Graphics, XR, and Emerging Visualization Technologies
A particular research theme is the integration of geometric structure, topological information, and learning-based methods into modern graphics and vision pipelines. This direction extends classical computational geometry and computer graphics toward contemporary differentiable, data-driven, and AI-enabled 3D computing.
The research aims to bridge the gap between geometric foundations and intelligent visual computing: developing algorithms that do not merely generate visually plausible results, but also preserve and reason about the underlying shape, structure, topology, motion, and semantics of visual information.
This perspective supports applications ranging from 3D content creation and computer animation to scientific visualization, computer vision, digital twins, and AI-based visual systems.
Research Areas
Primary Area
Computer Graphics and Visual Computing
Core Expertise
Computational Geometry · Geometric Modeling · Topological Modeling ·
3D Reconstruction · Computer Animation · Computer Vision ·
Artificial Intelligence · Scientific Visualization
Emerging Directions
Differentiable Graphics · Topology-Aware Learning · AI for 3D Computing ·
Digital Twins · Intelligent Visualization · XR/Interactive Visual Computing
Selected Research Themes
Geometry & Topology
Shape representation, geometric modeling, mesh processing,
topology-aware algorithms, and structure-preserving 3D computation.
Animation & Simulation
Computer animation, motion representation, physically based and
controllable simulation, and computational methods for dynamic visual content.
AI & Visual Computing
Integration of machine learning and AI with graphics, vision,
geometric reasoning, and visual scene understanding.
3D Reconstruction & Representation
Algorithms for reconstructing, representing, simplifying, and analyzing
3D objects and scenes while preserving important geometric and
topological properties.
Scientific & Interactive Visualization
Visual representations and interactive systems for exploring complex
scientific, engineering, and spatial information.
Selected Recent Research Direction
Recent work extends the group’s long-standing expertise in computational geometry toward topology-aware differentiable 3D reconstruction, investigating how persistent-homology-based objectives can explicitly preserve topological structures that conventional geometric or photometric losses may fail to capture.
This research direction represents a transition from traditional geometry processing toward structure-aware and differentiable visual computing, connecting classical Computer Graphics with contemporary AI and 3D reconstruction research.
