Imaging science
for transdisciplinary impact
Accelerate scientific and industrial insights
through visual exploration across fields
Inverse Problem in Imaging
To develop interpretable solutions for image reconstruction from partial, noisy, or indirect measurements, with a particular emphasis on incorporating physical constraints and domain knowledge into the algorithm.
Computational Microscopy
To overcome fundamental physical constraints of conventional microscopy through leveraging advanced computing, elevating image quality, sensitivity and spatial-temporal resolution.
AI for Science
To integrate Artificial intelligence (AI) to accelerate hypotheses generation, experiments design, advanced characterization and data interpretabilition, unlocking scientific discoveries that were previously out of reach.
We are kindly supported by
