Computational Methods for Next-Generation Microscopy

Computational microscopy is transforming the quantitative characterization of advanced materials and biological systems, shifting the primary bottleneck from hardware limitations to computational challenges. Modern imaging platforms enable micro- and nanoscale, high-dimensional, in-situ, and operando measurements; consequently, reconstruction and analysis algorithms now determine the fidelity, interpretability, and ultimate scientific value of the data. This workshop will highlight emerging computational methodologies that drive advances in microscopy, including physics-informed learning, large-scale tomographic reconstruction, multimodal data fusion, and uncertainty quantification. Beyond image formation, discussions will emphasize scalable and robust algorithms that integrate into scientific and industrial workflows across X-ray, electron, and optical modalities. By identifying open challenges and incorporating industrial perspectives, the workshop seeks to advance quantitative, high-dimensional imaging methodologies that directly support technological innovation and scientific discovery.

TBC

ICIP 2026 • Doğa Gürsoy (dgursoy@anl.gov) • Jizhou Li (jzli@ee.cuhk.edu.hk)