Yuanting Liu

fortiss · Human-Centered Engineering

Supporting pilots with a decision support tool (DST) during high-workload scenarios is a promising and potentially very helpful application for AI in aviation. Nevertheless, design requirements and opportunities for trustworthy DSTs within the aviation domain have not been explored much in the scientific literature. To address this gap, we explore...

As the aviation industry is actively working on adopting AI for air traffic, stakeholders agree on the need for a human-centered approach. However, automation design is often driven by user-centered intentions, while the development is actually technology-centered. This can be attributed to a discrepancy between the system designers’ perspective an...

Decision support systems based on AI are usually designed to generate complete outputs entirely automatically and to explain those to users. However, explanations, no matter how well designed, might not adequately address the output uncertainty of such systems in many applications. This is especially the case when the human-out-of-the-loop problem...

In graph neural networks (GNNs), message passing iteratively aggregates nodes' information from their direct neighbors while neglecting the sequential nature of multi-hop node connections. Such sequential node connections e.g., metapaths, capture critical insights for downstream tasks. Concretely, in recommender systems (RSs), disregarding these in...

Classifying stress in firefighters poses challenges, such as accurate personalized labeling, unobtrusive recording, and training of adequate models. Acquisition of labeled data and verification in cage mazes or during hot trainings is time consuming. Virtual Reality (VR) and Internet of Things (IoT) wearables provide new opportunities to create bet...

The purpose of image restoration is to recover the original state of damaged images. To mitigate the disadvantages of the manual image restoration process such as the high time consumption, we present interactive Deep Image Prior by extending Deep Image Prior with a user interface to an interactive process with the human in the loop. In this proces...

Machine learning and many of its applications are considered hard to approach due to their complexity and lack of transparency. One mission of human-centric machine learning is to improve algorithm transparency and user satisfaction while ensuring an acceptable task accuracy. In this work, we present an interactive image restoration framework, whic...

Integrated Development Environments (IDEs) are used for a varietyof software development tasks. Their complexity makes them chal-lenging to use though, especially for less experienced developers. In this paper, we outline our approach for an user-adaptive IDE that is able to track the interactions, recognize the user's intent and expertise, and pro...

Driving in autonomous cars requires trust, especially in case of unexpected driving behavior of the vehicle. This work evaluates mental models that experts and non-expert users have of autonomous driving to provide an explanation of the vehicle's past driving behavior. We identified a target mental model that enhances the user's mental model by add...

Situation awareness in highly automated vehicles can help the driver to get back in the loop during a take-over request (TOR). We propose to present the driver a detailed digital representation of situations causing a TOR via a scaled down digital twin of the highway inside the car. The digital twin virtualizes real time traffic information and is...