Join us for a three-day hands-on workshop on QUASAR, and learn to preprocess data, build visual workflows, and apply machine learning methods to infrared spectroscopy and microscopy datasets!
When: 4-6 November, 2025
Where: LINXS, The Loop, Rydbergs torg 4, 224 84 Lund
Organisers: ECL and AIDA Themes at LINXS
Limitations: The workshop is open for up to 30 participants on the first-come first-served basis. We will keep a reserve list in case of cancellations.
Target group: The event is open to both experienced and novice users of different spectroscopy techniques, with particular focus on vibrational (infrared and Raman) spectroscopy, who want to learn using open source data analysis software QUASAR for both pre-processing the spectral datasets, but also using different types of analyses, from multivariate approaches to machine learning. We particularly welcome early career researchers (PhD students and postdocs) to participate.
ABOUT
The researcher communities from different fields using spectroscopy-based approaches, either alone or in combination, often face the challenge of finding a single user-friendly platform for the data analysis. To address this, an open-source QUASAR software offers a collection of data analysis toolboxes, which allow gaining better insight to the data through interactive visualization, powerful machine learning methods and combining different datasets in easy-to-understand visual workflows.
In this QUASAR for Spectral Data Analysis workshop, Dr. Ferenc Borondics (SOLEIL synchrotron facility, France) and Dr. Stuart Read (Canadian Light Source, Canada) will give an introduction into the QUASAR project and its use for spectral datasets: from pre-processing to creating complex machine learning-based workflows. The workshop will offer hands-on data analysis sessions, where participants are welcome to bring their own data to work on.
The focus will be placed on infrared (IR) spectroscopy and microscopy (including O-PTIR and AFM-IR), but QUASAR also offers capabilities for other techniques, including Raman spectroscopy or X-ray microscopy, and users of those are welcome.
Preliminary program
Tuesday 4th of November
09:30 – 10:30 Arrival and registration
10:30 – 12:00 Session I
Introduction into the workshop and basics of visual programming, installation of QUASAR
12:00 – 13:15 Lunch
13:15 – 14:30 Session II
Visualizations and selections, pre-processing
14:30 – 15:00 Coffee break
15:00 – 16:15 Session III
Advanced pre-processing of spectroscopy data
16:15 – 16:30 Small break
16:30 – 17:45 Session IV
Assignments based on day 1 activities (using example or own data)
Wednesday 5th of November
09:00 – 10:30 Session I
Discussion/questions from Day 1, introduction to unsupervised methods on spectroscopy data
10:30 – 11:00 Coffee break
11:00 – 12:15 Session II
Clustering
12:15 – 13:30 Lunch
13:30 – 14:30 Session III
Advanced clustering
14:30 – 15:00 Coffee break
15:00 – 16:30 Session IV
Assignment for unsupervised methods based on the day 2 activities, discussion of potential solutions
17:00 Workshop dinner (pizza and drinks)
Thursday 6th of November
09:00 – 10:30 Session I
Discussion/questions from Day 2, data classification
10:30 – 11:00 Coffee break
11:00 – 12:30 Session II
Advanced classification
12:30 – 13:30 Lunch
13:30 – 15:15 Session III
Common errors and how to avoid them
15:15 Coffee, free discussion and workshop end
Topics that will be covered during the workshop:
Data import and exploration
Pre-processing
Visualization
Statistical exploration
Introduction to unsupervised learning
Clustering of spectral and hyperspectral datasets
Introduction to supervised learning
Classification of spectral and hyperspectral datasets
Model Inspection and cross-validation
Predictions
Common errors
Hands-on exercises
Contact
For questions about the workshop, please contact Milda Pucetaite milda.pucetaite@biol.lu.se or Karina Thånell karina.thanell@maxiv.lu.se
For general questions about the venue and registration, please contact Josefin Martell, josefin.martell@linxs.lu.se
The event is free of charge, but please note that we have a no-show fee of 200 SEK to offset the cost of ordered food.
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