https://matrixopticslab.github.io/tag/holography/HolographyHugo Blox Builder (https://hugoblox.com)en-usSun, 28 Dec 2025 00:00:00 +0000https://matrixopticslab.github.io/media/icon_hu17334560117968675030.pnghttps://matrixopticslab.github.io/tag/holography/https://matrixopticslab.github.io/post/liangcaicao/Sun, 28 Dec 2025 00:00:00 +0000https://matrixopticslab.github.io/post/liangcaicao/<p>On December 28, 2025, we were honored to host <strong>Prof. Liangcai Cao</strong> from the Department of Precision Instruments at <strong>Tsinghua University</strong> for an academic seminar titled <strong>&ldquo;Computational Optics Wavefront Sensing and Phase Imaging Technology.&rdquo;</strong></p> <p>Prof. Cao is a renowned expert in holographic display and computational imaging. During his presentation, he shared his group&rsquo;s latest breakthroughs in integrating physical models with neural networks, specifically highlighting:</p> <ul> <li><strong>Propagation-Adaptive Holography</strong>: Utilizing physics-constrained spatial and Fourier neural operators to achieve high-fidelity 4K computer-generated holography.</li> <li><strong>Computational Wavefront Sensing</strong>: Implementing high-resolution wavefront characterization for complex wavefields in biological imaging.</li> <li><strong>Physics-Informed Deep Learning</strong>: Applications in adaptive aberration-corrected quantitative phase microscopy to overcome traditional imaging limits.</li> </ul> <p>The seminar sparked extensive discussions among our group members regarding the intersection of <strong>random matrix theory</strong> and <strong>holographic reconstruction</strong>. We sincerely thank Prof. Cao for his profound insights and the valuable academic exchange.</p>