DISA Seminar December 6th: Machine Learning for Astroparticle Physics

22 November, 2021

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


  1. Y. Becherini et al., 2011 (Astrop. Phys., Vol 34, 12, 2011, 858-870)
  2. Y. Becherini et al., 2012 (Gamma 2012)
  3. Y. Becherini et al., 2012 (arXiv:1211.5997) 
  4. M. Senniappan et al
  5. T. Bylund et al., 

ICT with Industry workshop – Artificial Intelligence for Text Simplification (17-21 January 2022)

20 October, 2021

Are you a young scientist with a background in ICT and do you have a creative and inquisitive mind? Do you like to think outside-the-box? Would you like to get into contact with industrial partners such as KB, RTL, Axini, SIG or Philips and solve a case together? Then apply for the “ICT with Industry 2022” Lorentz Workshop.

Every year, the Lorentz Center and NWO together organize an ICT with Industry workshop. During five days a group of about 50 researchers from IT and Computer Science from a wide range of universities (within the Netherlands and Europe) will work together extensively on challenging problems proposed by companies.

This year the KB has also provided a case: ARTificial Intelligence for Simplified Texts (ARTIST). During the ICT with Industry workshop we aim to explore the possibilities to make news articles, books and other publications more accessible to people with low literacy by applying AI techniques to automatically rewrite publications.

More info

Important dates:
– application deadline: 22 November 2021
– notification: early December 2021
– workshop: 17-21 January 2022


In the Netherlands, about 2.5 million citizens between 16 and 65 years old find it hard to read. This means they face challenges to fully participate in today’s society. Recently we have seen this problem when people with low-level literacy received invitations for the COVID- 19 vaccines that were too complicated for them. But also understanding the news by reading news articles in the newspaper or websites can be difficult making it hard to understand current issues.

The KB, national library of the Netherlands, aims to make all publications available to all Dutch citizens, including people who have reading disabilities. In this use case we propose to explore the possibilities to make news articles, books and other publications more accessible to people with low literacy by applying AI techniques to automatically rewrite publications. In the Netherlands, several initiatives have been undertaken to manually make books or news articles more accessible. However, this is very labour intensive and only makes a small selection of publications available for illiterates. During the ICT with Industry workshop we aim to explore several methods to automatically rewrite news articles/book, making them available for all Dutch citizens.

DISA Seminar November 1st on Visualization Perspectives in Explainable AI

14 October, 2021
  • When? November 1st, 2021 at 12-13
  • Where? Online, links will be sent to those registered
  • Registration via this link

This talk with Professor Andreas Kerren, will overview interactive data visualization research with a focus on the development and use of visualization techniques for explainable artificial intelligence. The field of Information Visualization (InfoVis) uses interactive visualization techniques to help people understand and analyze data. It centers on abstract data without spatial correspondences; that is, usually it is not possible to map this information directly to the physical world. This data is typically inherently discrete. The related field of Visual Analytics (VA) focuses on the analytical reasoning of typically large and complex (often heterogeneous) data sets and combines techniques from interactive visualizations with computational analysis methods. I will show how these two fields belong together and highlight their potential to efficiently analyze data and Machine Learning (ML) models with diverse applications in the context of data-intensive sciences. As ML models are considered as complex and their internal operations are mostly hidden in black boxes, it becomes difficult for model developers but also for analysts to assess and trust their results. Moreover, choosing appropriate ML algorithms or setting hyperparameters are further challenges where the human in the loop is necessary. I will exemplify solutions of some of these challenges with the help of a selection of visualization showcases recently developed by my research groups. These visual analytics examples range from the visual exploration of the most performant and most diverse models for the creation of stacking ensembles (i.e., multiple classifier systems) to ideas of making the black boxes of complex dimensionality reduction techniques more transparent in order to increase the trust into their results.

Did you miss it? If so you can watch it here: https://play.lnu.se/media/t/0_hghpwmkw

information visualization, visual analytics, explainable AI, interaction, machine learning models, trust, explorative analysis, dimensionality reduction, high-dimensional data analysis

Further reading:


Seminar October 18th – Future Position X

1 October, 2021
  • When? Monday October 18th 12-13
  • Where? Online, link will be sent to those who sign up via this link https://forms.gle/NTo7jnysyLkBWaAm8 no later than October 15th

During the seminar Magnus Engström, CTO at Future Position X (FPX) will talk about two clear cases where FPX with data science has contributed to creating the conditions for a viable city center by collecting and combining data from different sources. More specifically, it will be about how we have applied machine learning to be able to predict movements in the city center and how we with a data-driven approach have created an application that helps the University of Gävle to conduct research on how Gävle residents experience their local environment. The presentation will be followed by a Q&A and discussion about potential collaborations with researchers from Linneaus University

Future Position X is an independent Swedish innovation center that works for growth through better health and well-being in the smart, sustainable and vibrant city. FPX contributes both technology and expertise to develop data-driven community solutions.

By initiating projects, creating relationships and building collaborations, FPX contributes to collaboration between business, academia and the public sector. FPX contributes to knowledge development of new technology by creating meeting places and networks around data-driven innovation such as GIS, AI, Internet of Things and blockchain technology. FPX also provides technical solutions, including the Innovation Platform, a data platform that can be used to digitally model societies. We are an important player in the work of strengthening both society and companies to a more sustainable growth.



Workshop “Critical perspectives on cultural heritage: Re-visiting digitisation” 26 October, 9-12hrs

28 September, 2021

Organizers: The workshop is co-organized by Linnaeus University (Centre for Applied Heritage and iInstitute) and Swedish National Heritage Board

Website: https://lnu.se/en/meet-linnaeus-university/current/events/2021/critical-perspectives-on-cultural-heritage-re-visiting-digitisation/

About: Today, the Semantic Web and Linked Open Data are creating new value for the descriptive information in the cultural heritage sector. Libraries, museums, heritage management and archives are seeing new possibilities in sharing by turning their catalogues into open datasets that can be directly accessed, allowing cultural heritage data to be circulated, navigated, analyzed and re-arranged at unprecedented levels. This is supported by research funding bodies, governments and EU policies and numerous political interests, resulting in enormous investment in digitization projects which make cultural heritage information openly available and machine readable. But before deploying this data, one must ask: is this data fit for deployment?

Libraries, museums, heritage management and archives have long histories. Both the collections they house and the language they use(d) to describe said collections are products of that historical legacy, shaped by, amongst others, institutionalized colonialism, racism and patriarchy. Yet descriptive information is now being digitized and shared as if that legacy is not inherent to the collections. Instead, existing units of information are being distributed through new Web 3.0 technologies, bringing with it an outdated knowledge-base. Besides the risk of progressive techniques being applied to regressive content, we may also sacrifice the development of new knowledge in libraries, museums, heritage management and archives aimed at facilitating socially sustainable futures, remediating exploitative historical legacies.

For this workshop, we have invited researchers and practitioners to discuss ways in which digitisation approaches may be set up to change the nature and legacy of cultural collection prior to digital dissemination.


DISA Seminar October 4th on Aggregation as Unsupervised Learning and some of its Applications

24 September, 2021
  • When? October 4th 12-13
  • Where? Online – the link will be sent to those who sign up
  • Registration? Sign up via this link no later than October 3rd.

This seminar will be presented by the DISTA research group within DISA, you will meet and listen to Welf Löwe, Maria Ulan, Morgan Ericsson, Anna Wingkvist

Aggregation combines several independent variables to a dependent variable. The independent variables are different, possible mutually dependent observations of a real world. The dependent variable should preserve properties of the independent variables, e.g., the ranking or relative distance of the independent variable tuples, and ultimately the properties of the real world. However, while there usually exist large amounts independent variable tuples, there is no ground truth data available mapping these tuples to the corresponding dependent variable values. This makes aggregation an unsupervised machine learning problem, as opposed to, e.g., regression where data comprises independent variable tuples and the corresponding dependent variable values.

Instances of the problem frequently occur in software engineering, e.g., when trying to assess the quality of software by metrics. Metrics (independent variables) can easily be measured for a lot of software artifacts, but it is hard to measure quality (dependent variable). Instances also occur in many other assessment situations including, but not limited to the assessment of project proposals, financial investments, and human movements.

In our talk, we present
1) aggregation as unsupervised learning including unweighted and weighted approaches
2) ways to evaluate and compare different aggregation approaches including an evaluation of the approaches introduced in 1)
3) applications to software engineering problems applying the evaluation introduce in 2)

The recording of this session and previous recordings will be available at the following link

NEW DISA Seminar Series starting September 6th 12-13

2 September, 2021

We are now finally starting a new Seminar series within DISA, even if you are not affiliated with DISA you are welcome to attend.

Aim with the seminar series:
Our research centre now have some 10 different research groups, each comprising a trending research topic. In order to make those different subjects of expertize more known outside of the own group and more accessible to PhD students we now launch a research seminar series.

Out first lunch seminar series will be on Monday September 6th 12-13 with Thomas Holgersson
Link to the seminar: https://lnu-se.zoom.us/j/63536937748 (no sign up needed)

Titel: Matrices in different dimensions: high, low and in between
Abstract: I will survey some common methods for statistical analysis of random matrices in fixed and in increasing dimensions. The geometry of high-dimensional objects will discussed from a data-analytic perspective. I will also cover some different modes of asymptotics, with particular focus on scalability.
Keywords: Wishart ensambles, geometry of high-dimensional objects, spectral analysis, Mahalanobis distance, modes of convergence.

Kind regards,
Thomas and Diana

Summer/winter schools available through EUniWell

20 May, 2021

Here is a overview of Summer/Winter schools at Leiden University (in particular at Leiden Medical Center) that is available to us through EUniWell, might be of interest for some of you.

  • Data Science in Health and Disease – Leiden-Brazil Summer School (June 2021, online)
  • Population Health Management – LUMC Summer School (June 2021, online)
  • TechMed – LUMC Summer School (July 2021, online)
  • Artificial Intelligence & Value Based Healthcare – LUMC Summer School (August 2021, online)
  • Regenerative Medicine – Leiden Summer School (October 2021)
  • Translational Research on Neuromuscular Diseases – LUMC / ERN EURO-NMD / TREAT-NMD Winter School (December 2021)

More information and registration:


iInstitute / Digital Humanities webinar: The Ethics of Datafication and AI by Geoffrey Rockwell

18 May, 2021

Summary – We all want artificial intelligence to be responsible, trustworthy, and good… the question is how to get beyond principles and check lists. In this paper I will argue for the importance of the data used in training machines, especially when it comes to avoiding bias. Further, I will argue that there is a role for humanists and others who have been concerned with the datafication of the cultural record for some time. Not only have we traditionally been concerned with social, political and ethical issues, but we have developed practices around the curation of the cultural record. We need to ask about the ethics around big data and the creation of training sets. We need to advocate for an ethic of care and repair when it comes to digital archives that can have cascading impact.

About the speaker – Geoffrey Rockwell is a Professor of Philosophy and Digital Humanities, Director of the Kule Institute for Advanced Study and Associate Director of AI for Society signature area at the University of Alberta. He publishes on textual visualization, text analysis, ethics of technology and on digital humanities including a co-authored book Hermeneutica from MIT Press (2016). He is co-developer of Voyant Tools (voyant-tools.org), an award winning suite of text analysis tools. He is currently the President of the Canadian Society for Digital Humanities.