Real-time coherent diffraction inversion using deep generative networks. - Mathew J. Cherukara; Youssef S. G. Nashed; Ross J. Harder (CoRR, 2018)

BLAST: Bridging Length/time scales via Atomistic Simulation Toolkit. - Henry Chan; Badri Narayanan 003; Mathew J. Cherukara; Troy D. Loeffler; Michael G. Sternberg; Anthony Avarca; Subramanian K. R. S. Sankaranarayanan (CoRR, 2020)

Real-time sparse-sampled Ptychographic imaging through deep neural networks. - Mathew J. Cherukara; Tao Zhou; Youssef S. G. Nashed; Pablo Enfedaque; Alex Hexemer; Ross J. Harder; Martin V. Holt (CoRR, 2020)

Real-time 3D Nanoscale Coherent Imaging via Physics-aware Deep Learning. - Henry Chan; Youssef S. G. Nashed; Saugat Kandel; Stephan Hruszkewycz; Subramanian Sankaranarayanan; Ross J. Harder; Mathew J. Cherukara (CoRR, 2020)

High resolution functional imaging through Lorentz transmission electron microscopy and differentiable programming. - Tao Zhou; Mathew J. Cherukara; Charudatta Phatak (CoRR, 2020)

High-Performance Ptychographic Reconstruction with Federated Facilities. - Tekin Bicer; Xiaodong Yu 001; Daniel J. Ching; Ryan Chard; Mathew J. Cherukara; Bogdan Nicolae; Rajkumar Kettimuthu; Ian T. Foster (SMC, 2021)

AutoPhaseNN: Unsupervised Physics-aware Deep Learning of 3D Nanoscale Coherent Imaging. - Yudong Yao; Henry Chan; Subramanian Sankaranarayanan; Prasanna Balaprakash; Ross J. Harder; Mathew J. Cherukara (CoRR, 2021)

Automated Continual Learning of Defect Identification in Coherent Diffraction Imaging. - Orcun Yildiz; Henry Chan; Krishnan Raghavan; William Judge; Mathew J. Cherukara; Prasanna Balaprakash; Subramanian Sankaranarayanan; Tom Peterka (AI4S, 2022)

Deep learning at the edge enables real-time streaming ptychographic imaging. - Anakha V. Babu; Tao Zhou; Saugat Kandel; Tekin Bicer; Zhengchun Liu; William Judge; Daniel J. Ching; Yi Jiang; Sinisa Veseli; Steven Henke; Ryan Chard; Yudong Yao; et al. (CoRR, 2022)

AI-assisted automated workflow for real-time x-ray ptychography data analysis via federated resources. - Anakha V. Babu; Tekin Bicer; Saugat Kandel; Tao Zhou; Daniel J. Ching; Steven Henke; Sinisa Veseli; Ryan Chard; Antonino Miceli; Mathew Joseph Cherukara (High Performance Computing for Imaging, 2023)

Opportunities for Retrieval and Tool Augmented Large Language Models in Scientific Facilities. - Michael H. Prince; Henry Chan; Aikaterini Vriza; Tao Zhou; Varuni K. Sastry; Matthew T. Dearing; Ross J. Harder; Rama K. Vasudevan; Mathew J. Cherukara (CoRR, 2023)

Predicting ptychography probe positions using single-shot phase retrieval neural network. - Ming Du; Tao Zhou; Junjing Deng; Daniel J. Ching; Steven Henke; Mathew J. Cherukara (CoRR, 2024)

Homomorphic data compression for real time photon correlation analysis. - Sebastian Strempfer; Zichao Wendy Di; Kazutomo Yoshii; Yue Cao; Qingteng Zhang; Eric M. Dufresne; Mathew J. Cherukara; Suresh Narayanan; Martin V. Holt; Antonino Miceli; Tao Zhou (CoRR, 2024)

Automated defect identification in coherent diffraction imaging with smart continual learning. - Orcun Yildiz; Krishnan Raghavan; Henry Chan; Mathew J. Cherukara; Prasanna Balaprakash; Subramanian Sankaranarayanan; Tom Peterka (Neural Comput. Appl., 2024)

Demonstration of an AI-driven workflow for dynamic x-ray spectroscopy. - Ming Du; Mark Wolfman; Chengjun Sun; Shelly D. Kelly; Mathew J. Cherukara (CoRR, 2025)

DONUT: Physics-aware Machine Learning for Real-time X-ray Nanodiffraction Analysis. - Aileen Luo; Tao Zhou; Ming Du; Martin V. Holt; Andrej Singer; Mathew J. Cherukara (CoRR, 2025)