Welcome to the website of the Chair of Information Systems and Data Analytics! Our research and teaching focuses on how human decision-making processes can be improved through the responsible use of data and algorithms.

News

23.02.2024

Unterstützung im Team von Prof. Dr. Oliver Müller gesucht! (Forschung)

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19.02.2024

Volksbank Sauerland is looking for a Student trainee (m/f/d) with the opportunity to co-operate on final theses

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24.01.2024

Support wanted for Prof Dr Oliver Müller's team!

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More news

Research

The aim of our research is to improve human decision-making processes through the responsible use of data and algorithms. We pursue a socio-technical approach that incorporates the latest technologies (in particular machine learning and artificial intelligence) as well as social and societal aspects. 

The following topics are the focus of our research:

  • Development and evaluation of AI-based methods and systems to support and automate decisions  
  • Acceptance/Adoption and economic value of artificial intelligence

Our research is application-orientated and takes place in interdisciplinary teams. Applications can be found, for example, in the fields of energy, logistics/transport, finance, culture, and sport.

soda.lab - Social & Data-Intensive Computing Lab

The soda.lab is available to our students for final theses and modules in the Department of Information Systems. It includes powerful servers and workstations with GPUs that enable deep learning, complex simulations and realistic visualizations in real time.

Mitarbeitende tauschen sich auf Sofa aus.

Publications

We publish our research results in the leading scientific journals and at international conferences.

Mitarbeiter schreibt etwas an eine Tafel.

Projects

Our application-orientated research often takes place in interdisciplinary projects with members from research and practice.

Teaching

We offer lectures and seminars at the Bachelor's, Master's, and Doctoral levels.

Bachelor

Module name Module type Semester ECTS Language
Fundamentals of management information systems Lecture summer semester 5 DEU
Methods of Data Science (Film) Lecture winter term 5 DEU
Predictive Analytics Student research project SoSe/WiSe 5 DEU/ENG

 

Master

Module name Module type Semester ECTS Language
Data Science for Business Lecture winter term 5 ENG/DEU
Applied Machine Learning for Text Analysis Seminar winter term 10 ENG/DEU
Real-World Machine Learning Projects Seminar summer semester 10 ENG/DEU

 

Doctorate

Module name Module type Semester ECTS Language
Machine Learning for Research Seminar Summer semester (irregular) 6 ENG

 

Application

The Department of Information Systems does not participate in the centralized allocation procedure of the Faculty of Business Administration and Economics. Consequently, the application process varies for each chair.

Our application deadlines are as follows:

  • Winter semester: January 1 - February 28 (29)
  • Summer semester: July 1 - August 31

To apply, please submit the following:

  • Curriculum vitae
  • Current transcript of records
  • Letter of application

Your letter should express your interest in "Data Analytics" topics and include suggested themes for your thesis. Please email your complete application to the chair.

We emphasize the importance of a strong interest in a topic as a key to success. Rather than publishing pre-defined topics, we encourage students to bring their own interests and define their thesis topics in consultation with a chair member.

Occasionally, we offer theses with practice partners, where topics are usually predefined. If applicable, you will find these under the relevant heading.

Preparation (template)

Please use this LaTeX template as a guide when designing your thesis !

Master's thesis with optional internship in the field of "Patent Analytics" (Wilhelm Böllhoff GmbH & Co. KG, Bielefeld)

 

Patents offer two essential functions, namely protection against imitation and the provision of information.

The information function of patents is currently little utilised by companies. However, the potential for utilising information is very high, as it is estimated that 90% of the technical knowledge published worldwide can be found in the patent literature. The currently emerging field of "patent analytics", which is also referred to in the literature as "IP intelligence", for example, is concerned with the procurement, analysis and processing of information from published patents and patent register data.

IP intelligence utilises the fact that patents contain structured bibliographic information such as applicant data, inventor data, time data and technical classifications. The published information on forward and backward citations also offers opportunities for gaining knowledge.

On the other hand, the contents of patent specifications, such as the technically detailed descriptions of the inventive embodiments and the problems to be solved as well as the technical illustrations contained therein, also offer great informative potential. This can be utilised, for example, through semantic, AI-based analyses to identify current technical problems and solutions.

Other information published in the context of patent applications also offers a currently underutilised potential (data on disputes, examination procedures, etc.).

Companies can utilise this information function for better strategic decision-making. For example, idea generation processes for product innovations can be supported. This information is also helpful for identifying new markets or collaborations or M&A, evaluating applicants and analysing patent dependencies.

The aim of the work is to develop and evaluate methods for analysing patent data. These methods will then be used to demonstrate the entrepreneurial benefits of specific case studies.

All details can be found here

Team

Meet the brilliant minds driving research and teaching at the Data Analytics Group. Our team is an interdisciplinary blend of experts, each passionate about data-driven decision making in domains ranging from energy over finance to sports.

 

Find out more about our team here!

Join our team!

Become part of our team, either as a student assistant or research assistant with a Bachelor's degree or as a research assistant after completing your Master's degree.

Contact

Wirtschaftsinformatik, insb. Data Analytics

Paderborn University
Warburger Str. 100
33098 Paderborn
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