Below you can find a selection of the CCS members' current research projects. Follow the links for more details, demos and related papers.

SEGMENT – 3D scene understanding in two glances

In project "SEGMENT", Professor Thomas Wallis and his team are investigating what is known as visual segmentation. This is when the human brain attempts to recognise which parts of a scene shown, for instance, in a photo belong to which objects. The researchers want to find out how people combine information from active 3D vision, and how they can learn this combination from visual experiences.

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ACTOR – Towards a computational account of natural sequential behavior

The European Research Council is funding the project "ACTOR – Towards a computational account of natural sequential behaviour" over a period of five years. The aim of the project is to gain a better understanding of human behaviour in everyday tasks by means of cognitive computational models, i.e. by applying algorithms similar to artificial intelligence. ACTOR has been awarded as an “ERC Consolidator Grant" to Constantin Rothkopf.

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The Adaptive Mind

The Universities of Giessen, Marburg, and Darmstadt together with the University of Frankfurt and the Frankfurt Institute for Advanced Studies (FIAS) aim to strategically strengthen research in the field of Mind, Brain, and Behavior. The goal is to observe empirically, describe quantitatively, and model computationally how the human mind continually adapts in an ever-changing and often unpredictable world.
Ongoing research funded by Hessen State Ministry for Higher Education, Research and the Arts.

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WhiteBox – explainable models for human and artificial intelligence

The LOEWE Research Cluster “WhiteBox – explainable models for human and artificial intelligence” is aimed at developing methods at the intersection between Cognitive Science and AI to make human and artificial intelligence more understandable.
Ongoing research funded by Hessen State Ministry for Higher Education, Research and the Arts.

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IKIDA

The overall technical and scientific goal of IKIDA is the development of interactive, probabilistic AI algorithms, which benefit from direct interaction with users. Enabling such direct interaction between AI algorithms and users is also intended to lower application hurdles of AI solutions and can potentially increase their sustainability and acceptance. For the development of the AI algorithms we particularly plan to incorporate and develop new cognitive models for human-AI interaction.
Ongoing research funded by the German Ministry of Education and Research (BMBF).

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3AI – The Third Wave of Artificial Intelligence

3AI – The Third Wave of Artificial Intelligence aims to explore the Third Wave of Artificial Intelligence: AI systems should acquire human-like communication and reasoning capabilities and be able to recognize, classify and adapt to new situations autonomously. The goal is not to replace human intelligence, but to extend it reliably and for the benefit of society in an increasingly complex world.
3AI is a collaborative endeavour of the Universities of Darmstadt, Frankfurt, Mainz and the Frankfurt Institute for Advanced Studies (FIAS).
Ongoing research funded by Hessen State Ministry for Higher Education, Research and the Arts.

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PlexPlain – Explaining AI

PlexPlain („Erklärende KI für Komplexe Lineare Programme am Beispiel intelligenter Energiesysteme”) aims at the automated generation of explanations for complex linear programs with a focus on applications in the energy sector.
Ongoing research funded by the German Federal Ministry of Education and Research (BMBF).

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KompAKI

The joint project “KompAKI – Kompetenzzentrum für Arbeit und Künstliche Intelligenz” (Competence Center for Work and Artificial Intelligence) will tap into new potential for human-centric AI applications and their business models, develop new approaches to cooperative AI that enable users to use AI more transparently and easily, and develop new methods for evaluating work in AI-based work systems.
Ongoing research project funded by the German Ministry of Education and Research (BMBF).

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LokoAssist

LokoAssist aims at a “seamless” integration of assistive devices into the human body schema. This requires an automatic recognition of different movement intentions to create and intuitive and predictable motor behavior. Such assistance systems promise a significantly expanded range of motion with lower metabolic energy expenditure, better individual adaptability, and greater ease of movement.
Ongoing research funded by DFG – Deutsche Forschungsgemeinschaft (German Research Foundation).

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Active Vision

This project aims at experimentally investigating and quantifying human behavior in sequential tasks that require human subjects to detect spatial or temporal visual targets.
Ongoing research funded by DFG – Deutsche Forschungsgemeinschaft (German Research Foundation).

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Understanding decision criterion learning

This project conducts behavioral and neurophysiological experiments to achieve a deeper understanding of adaptive choice algorithms and their neural implementation.
Ongoing research funded by DFG – Deutsche Forschungsgemeinschaft (German Research Foundation).

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RED – Robust, Explainable Deep Networks in Computer Vision

The goal of his project is to develop methods that make artificial neural networks in computer vision, particularly so-called deep networks, more robust and more explainable. One particular aim is to increase user trust in machine learning approaches to computer vision, for example in the context of autonomous vehicles.

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You can also view our former projects here