Speaker
Description
With the advent of high-speed multi-megapixel detectors, previously unimaginable in situ time-resolved and high throughput experiments using synchrotron and free-electron laser X-ray sources have become possible. Such detectors generate massive quantities of data are far in excess of what human experimenters can manually interpret and analyse rendering old school data analysis methods of ‘collect and take home to analyse later’ obsolete. Analysing data sufficiently quickly to keep the experimenter in the loop and able to make agile decisions on how to proceed with the experiment at the pace experiments can be performed is now a major challenge. We would like to exploit AI-based data analysis to guide decisions during the course of an experiment, as well as in subsequent data selection. The key is to deliver preliminary results at high speed to users in a timely manner, enabling experimenters to focus on the best data and to analyse much larger data volumes, and thereby increasing the scientific output of our large scale facilities.
Please describe your expertise/areas in which you would like to contribute / advise.
Analysis of X-ray data; near-real-time and rapid offline data analysis and reduction; X-ray diffraction and coherent scattering analysis
In ErUM-Data, what kind of data are you dealing with?
Large scale data sets (up to 750TB per experiment) at high data rates (3500 fps+/multi-TB per hour) from state of the art area detectors.
My current most burning research question, I like to find partners for, is:
How to exploit AI for rapid data analysis at large scale facilities; finding the niche for AI in an environment where experiments can change weekly.
What is your expertise in computing and / or software development?
Head of scientific computing, DESY photon science
Please describe areas in which you can contribute to “data handling” teaching.
Through Daphne4NFDI project
What is your field and role?
Coherent X-ray scattering
Serial femtosecond crystallography
Large scale data reduction and analysis
Implementation at large scale facilities
Please describe areas in which you would like to improve your knowledge / skills.
Application of Artificial Intelligence & Machine Learning algorithms to analysis of data from diverse X-ray experiments at large scale facilities
| Your ErUM - Committee is | More than one |
|---|---|
| List of Committees: | KFS, KFN |
| Do you consent to the data usage and public abstract data posting in the ErUM-Data Community Information Exchange? | Yes |
