151 citations · 250 across the 14 of their papers we have counts for
15 papers
Deep learning at the edge enables real-time streaming ptychographic imaging
Anakha V Babu, Tao Zhou, Saugat Kandel +15
Coherent microscopy techniques provide an unparalleled multi-scale view of materials across scientific and technological fields, from structural materials to quantum devices, from…
Masked Sinogram Model with Transformer for ill-Posed Computed Tomography Reconstruction: a Preliminary Study
Zhengchun Liu, Rajkumar Kettimuthu, Ian Foster
Computed Tomography (CT) is an imaging technique where information about an object are collected at different angles (called projections or scans). Then the cross-sectional image s…
FAIR principles for AI models with a practical application for accelerated high energy diffraction microscopy
Nikil Ravi, Pranshu Chaturvedi, E. A. Huerta +7
A concise and measurable set of FAIR (Findable, Accessible, Interoperable and Reusable) principles for scientific data is transforming the state-of-practice for data management and…
Real-Time Streaming and Event-driven Control of Scientific Experiments
Jakob R. Elias, Ryan Chard, Maksim Levental +3
Advancements in scientific instrument sensors and connected devices provide unprecedented insight into ongoing experiments and present new opportunities for control, optimization,…
fairDMS: Rapid Model Training by Data and Model Reuse
Ahsan Ali, Hemant Sharma, Rajkumar Kettimuthu +7
Extracting actionable information rapidly from data produced by instruments such as the Linac Coherent Light Source (LCLS-II) and Advanced Photon Source Upgrade (APS-U) is becoming…
BFTrainer: Low-Cost Training of Neural Networks on Unfillable Supercomputer Nodes
Zhengchun Liu, Rajkumar Kettimuthu, Michael E. Papka +1
Supercomputer FCFS-based scheduling policies result in many transient idle nodes, a phenomenon that is only partially alleviated by backfill scheduling methods that promote small j…
Bridging Data Center AI Systems with Edge Computing for Actionable Information Retrieval
Zhengchun Liu, Ahsan Ali, Peter Kenesei +11
Extremely high data rates at modern synchrotron and X-ray free-electron laser light source beamlines motivate the use of machine learning methods for data reduction, feature detect…
Fast and accurate learned multiresolution dynamical downscaling for precipitation
Jiali Wang, Zhengchun Liu, Ian Foster +3
This study develops a neural network-based approach for emulating high-resolution modeled precipitation data with comparable statistical properties but at greatly reduced computati…
Deep Learning-based Low-dose Tomography Reconstruction with Hybrid-dose Measurements
Ziling Wu, Tekin Bicer, Zhengchun Liu +3
Synchrotron-based X-ray computed tomography is widely used for investigating inner structures of specimens at high spatial resolutions. However, potential beam damage to samples of…
Design and Evaluation of a Simple Data Interface for Efficient Data Transfer Across Diverse Storage
Zhengchun Liu, Rajkumar Kettimuthu, Joaquin Chung +3
Modern science and engineering computing environments often feature storage systems of different types, from parallel file systems in high-performance computing centers to object s…
Joint ptycho-tomography with deep generative priors
Selin Aslan, Zhengchun Liu, Viktor Nikitin +3
Joint ptycho-tomography is a powerful computational imaging framework to recover the refractive properties of a 3D object while relaxing the requirements for probe overlap that is…
BraggNN: Fast X-ray Bragg Peak Analysis Using Deep Learning
Zhengchun Liu, Hemant Sharma, Jun-Sang Park +5
X-ray diffraction based microscopy techniques such as High Energy Diffraction Microscopy rely on knowledge of the position of diffraction peaks with high precision. These positions…
Scientific Image Restoration Anywhere
Vibhatha Abeykoon, Zhengchun Liu, Rajkumar Kettimuthu +2
The use of deep learning models within scientific experimental facilities frequently requires low-latency inference, so that, for example, quality control operations can be perform…
Deep Learning Accelerated Light Source Experiments
Zhengchun Liu, Tekin Bicer, Rajkumar Kettimuthu +1
Experimental protocols at synchrotron light sources typically process and validate data only after an experiment has completed, which can lead to undetected errors and cannot enabl…
TomoGAN: Low-Dose Synchrotron X-Ray Tomography with Generative Adversarial Networks
Zhengchun Liu, Tekin Bicer, Rajkumar Kettimuthu +3
Synchrotron-based x-ray tomography is a noninvasive imaging technique that allows for reconstructing the internal structure of materials at high spatial resolutions from tens of mi…