Research
Research Areas
Our research focuses on transdisciplinary imaging science, combining advanced computational methods with cutting-edge imaging technologies to solve complex problems across multiple domains.
Research Themes
Inverse Problem in Imaging
Solving image reconstruction challenges to recover high-quality images from incomplete or noisy data.
Key Areas:
- Compressed sensing
- Super-resolution imaging
- Image denoising and restoration
- Computational photography
Computational Microscopy
Leveraging advanced computing to overcome physical limitations in conventional microscopy.
Key Areas:
- Computational super-resolution microscopy
- Phase retrieval algorithms
- 3D reconstruction techniques
- Real-time imaging systems
AI for Materials Characterization
Integrating AI to accelerate scientific discoveries through advanced materials characterization.
Key Areas:
- Machine learning for materials analysis
- Automated image analysis
- Pattern recognition in microscopy
- Predictive modeling
Current Projects
Coming soon - detailed project information will be added here
Collaborations
We collaborate with leading institutions and industry partners worldwide to advance the field of imaging science.
For more information about our research, please contact us or visit our Publications page.