5 papers
Domain Knowledge Guided Bayesian Optimization For Autonomous Alignment Of Complex Scientific Instruments
Aashwin Mishra, Matt Seaberg, Ryan Roussel +2
Bayesian Optimization (BO) is a powerful tool for optimizing complex non-linear systems. However, its performance degrades in high-dimensional problems with tightly coupled paramet…
Deep Learning Enabled Nanoscale X-ray Photoemission Electron Microscopy (nanoXPEEM)
Aashwin Mishra, Daniel Ratner, Quynh Nguyen
Understanding and manipulating two-dimensional materials for real-world applications remains challenging due to a lack of effective and high-throughput characterization techniques.…
Data Driven Drift Correction For Complex Optical Systems
Aashwin Mishra, Matt Seaberg, Ryan Roussel +4
To exploit the thousand-fold increase in spectral brightness of modern light sources, increasingly intricate experiments are being conducted that demand extremely precise beam traj…
A Start To End Machine Learning Approach To Maximize Scientific Throughput From The LCLS-II-HE
Aashwin Mishra, Matt Seaberg, Ryan Roussel +5
With the increasing brightness of Light sources, including the Diffraction-Limited brightness upgrade of APS and the high-repetition-rate upgrade of LCLS, the proposed experiments…
Leveraging Prior Mean Models for Faster Bayesian Optimization of Particle Accelerators
Tobias Boltz, Jose L. Martinez, Connie Xu +7
Tuning particle accelerators is a challenging and time-consuming task that can be automated and carried out efficiently using suitable optimization algorithms, such as model-based…