Digital Input
Image or scene data enters the pipeline.
Building real-time holographic systems through computation and optical wavefront control.
We are building real-time holographic systems by combining computational methods with optical wavefront control.
Our approach focuses on transforming digital data into physically realizable light fields, enabling spatial reconstruction without traditional displays.
A unified pipeline connecting digital information, computation, phase encoding, optical modulation, and holographic output.
Image or scene data enters the pipeline.
Algorithms process structure and depth-related information.
Data is converted into phase patterns for optical reconstruction.
Light is modulated through engineered optical elements.
The encoded wavefront reconstructs a spatial visual result.
Each stage is essential. Together, they enable real-time holographic systems that transform digital information into physically realizable light fields.
The key pillars that enable our holographic systems.
We develop algorithms that convert digital inputs into phase-encoded representations suitable for optical reconstruction.
These methods define how information is structured before interacting with physical systems.
We engineer mechanisms to control the phase and propagation of light.
This enables precise shaping of wavefronts required for holographic reconstruction.
We design and evaluate optical architectures that translate encoded information into observable spatial outputs.
This includes the study of propagation, interference, and reconstruction behavior.
We focus on combining computation and optics into a unified pipeline.
The objective is to ensure that algorithms, materials, and physical systems operate together under real-world constraints.
Digital information is encoded into a phase distribution and reconstructed through optical systems.
Digital information enters the system.
Information is encoded into phase patterns.
The encoded wavefront reconstructs a spatial light field.
Our work is focused on bridging the gap between theoretical models and physically realizable systems.
We prioritize architectures that can evolve toward real-time performance and practical deployment.
We welcome conversations with researchers, engineers, and organizations working in related areas.
