November 2021

DISA Lunch seminar – Industry – Novotek

2021-11-30

Welcome to a DISA Industry Seminar with Novotek. There is a genuine interest to find research collaboration related to water and wastewater management together with them and Kalmar Vatten.

When? December 9th 12-13
Where? Online – you will get a link when you register
Registration? https://forms.gle/FUtjyV4H7kYRcegB6

During the seminar you will meet Thomas Lundqvist

In Swedish water and wastewater management, there are great opportunities to create large savings and environmental benefits by starting to work systematically with advanced data analysis, which is often called “analytics” or “machine learning”. Examples of areas where this methodology has great potential are:

Leak detection and leak detection in water and sewage systems.
Reduction of chemical consumption in the water purification process
Improving water quality
Reduction of energy consumption
Improved control of flue gas production which leads to increased process yield. Simply more biogas from the same amount of feedstock.

Although the analysis technique has been known for a long time, there are some challenges when starting to work with this in, for example, a municipal treatment plant. It requires a certain type of competence that is usually not available in a simple way. Advanced software is also required for this purpose. Once you have acquired the skills and tools, you come to the problem that is usually even more difficult to solve. There is a lack of sufficient data. This may be because:

You do not have enough sensors that measure relevant things.
The sensors are not connected and the data is not stored.
If sensor values are stored, the measurements are usually truncated incorrectly to save storage space and cost.
Large amounts of redundant information are often stored completely unnecessarily.

If you were to solve all this, you still have a big challenge as you lack other similar facilities to compare your analyzes with. There is a great potential to be able to share data between several municipalities and waterworks to learn from others and to simply get a much larger data base for their analyzes.
Novotek, together with Linnaeus University and Kalmar Vatten, wants to start a collaboration with the aim of finding a long-term solution together to the challenges that all waterworks and treatment plants face when society places increased demands on water treatment and water production, now and in the future!

Come and discuss with us and see how we can solve these challenges together!

DISA Seminar December 6th: Machine Learning for Astroparticle Physics

2021-11-22

When? December 6th, 2021 at 12-13
Where? Online, links will be sent to those registered
Registration via https://forms.gle/rKTXw3r6xmBhHGgw7

Astroparticle physics is a sub-branch of Physics dealing with the detection of gamma-rays, neutrinos, gravitational waves and cosmic rays from the Universe. In this seminar, we will focus on the field of extragalactic gamma-ray astronomy.

The two main types of datasets in the field are those produced via simulations and those acquired via detector equipments (“real”), leading to a large amount of data to be calibrated, prepared, filtered, reconstructed and analysed. Simulations are especially needed in order to understand the sensitivity of the given equipment to a given searched physics “signal” and to prepare the data analysis procedure before looking at the real data. Decades of experience in data analysis in the field lead to the ability to publish solid results.

In this context, machine learning is giving a big boost in speeding up the data analysis procedures. The first successful applications of supervised Machine Learning in the field date back to the years 2010-2013 and concern classification and regression methods. Nowadays, there is a huge effort to exploit Deep Learning methods to achieve faster simulations and to improve the current data analysis methods, where physicists cannot “see” or “predict” any significant features describing the datasets.

I will present the current activities and future challenges of my research groups at Linnaeus University and at the University of Paris and, more generally, the challenges of the field.

Keywords: gamma-ray astronomy, supervised machine learning, event classification, feature regression

Papers: