Competence area Artificial Intelligence

The "Artificial Intelligence" (AI) competence area at the SICP researches and develops AI-based solutions that combine technical innovations with social and societal challenges. Our interdisciplinary approach integrates the latest technologies such as machine learning (ML), natural language processing, knowledge graphs and mathematical optimisation with social, ethical and legal issues in order to create sustainable and responsible AI systems. Accordingly, we focus on the development and evaluation of AI-based methods and systems to support and/or automate decision-making. We attach particular importance to the acceptance as well as the economic and ecological benefits of AI in various fields of application. For example, in application-oriented projects ranging from Industry 4.0 to mobility and energy in order to develop AI solutions with real added value.

 

Sub­ject areas

This is an excerpt of current topics that are continuously expanded and updated.

  • Machine learning/deep learning
  • Natural language and language processing (incl. large language models)
  • Computer vision
  • Explainable AI
  • Knowledge graphs
  • Integration of mathematical optimisation and ML
  • Data-driven decision making
  • Data literacy

Fields of ap­plic­a­tion

Mobility - Using AI to create an efficient mobility system

AI-based systems are revolutionising the field of mobility by optimising the flow of traffic in cities and regions and making logistics more efficient. This includes intelligent traffic management and logistics systems that reduce traffic congestion, shorten delivery times and minimise environmental impact.

Energy supply & smart grids - AI applications for smart grids, predictive maintenance and integrated energy systems

AI can be used to make modern energy systems more efficient and sustainable. AI-based technologies optimise the operation and maintenance of electricity grids and support the development of smart grids, which can react flexibly to electricity demand and energy supply. These systems make it possible to intelligently connect different energy sectors - such as electricity, heat and mobility - and promote the use of renewable energies.

Industry 4.0 - ML for predictive maintenance, energy-efficient production and CO₂ reduction

The use of machine learning makes production smarter, more resource-efficient and more sustainable. Predictive maintenance ensures higher machine availability, energy-optimised control reduces resource consumption and targeted CO₂ reduction contributes to environmental and climate protection. This not only brings industrial companies efficiency gains, but also strengthens their sustainability and competitiveness.

Goals and vis­ions

Our aim is to research AI solutions that address both technological and social challenges. In addition, we want to strengthen human-AI collaboration for intelligent and responsible decision-making processes and develop new AI-based solutions in collaboration between science, business and society.

Selected projects

AProSys -KI-gestützte Assistenz- und Prognosesysteme für den nachhaltigen Einsatz in der intelligenten Verteilnetztechnik

Duration: 2023 - 2025 Funded by: BMWK

More about the project

Climate bOWL: Climate neutral Business in Ostwestfalen-Lippe

Duration: 2022 - 2025 Funded by: MWIKE NRW

More about the project

DC2HEAT - Data Centre HEat Recovery with AI-Technologies

Duration: 2023 - 2026 Funded by: BMUV

More about the project

DynOpt-San

Duration: 2024 - 2026 Funded by: BMWK

More about the project

HeatTransPlan

Duration: 2024 - 2026 Funded by: BMWK

More about the project

Re2Pli

Duration: 2022 - 2025 Funded by: MWIKE NRW

More about the project

arbeitswelt + - KI für die Arbeitswelt des industriellen Mittelstands

Duration: 2020 - 2025 Funded by: BMBF

More about the project

NeMo.bil – System kooperierender Fahrzeuge für einen individualisierten Öffentlichen Verkehr

Duration: 2023 - 2026 Funded by: BMWK

More about the project

Dir­ect­or

Oliver Müller

Office: Q2.457
Phone: +49 5251 60-5100
E-mail: oliver.mueller@uni-paderborn.de

Man­ager

Christoph Weskamp

> Software Innovation Campus Paderborn (SICP)

Coordinator - PostDoc - R&D Manager - Digital Business

Office: ZM2.A.03.25
Phone: +49 5251 60-5240
E-mail: weskamp@sicp.de

Uni­ver­sity lec­tur­ers in­volved

> Databases and Electronic Commerce

Section Owner - Professor

Office: F2.217
Phone: +49 5251 60-6662
E-mail: stb@uni-paderborn.de

> Communications Engineering / Heinz Nixdorf Institute

Head - Professor - Head of Department of Communications Engineering

Office: P7.2.05.3
Phone: +49 5251 60-3626
E-mail: haeb@nt.uni-paderborn.de

> Digital Humanities

Professor

Office: E2.321
Phone: +49 5251 60-3275
E-mail: tobias.matzner@uni-paderborn.de

> Informatik Rechnerbetrieb (IRB)

Head - Professor

Office: F1.225
Phone: +49 5251 60-1761
E-mail: axel.ngonga@uni-paderborn.de

> Data Science for Engineering

Section Owner - Junior Professor

Office: O4.213
Phone: +49 5251 60-5021
E-mail: sebastian.peitz@uni-paderborn.de

Office: FU.231
Phone: +49 5251 60-6309
Phone: +49 1606675582
E-mail: heike.trautmann@uni-paderborn.de

Image source: AdobeStock/Prostock-studio