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Human Computer Interaction (HCI) has been redefined in this era. People want to interact with their devices in such a way that has physical significance in the real world, in other words, they want ergonomic input devices. In this paper, we…
Adapting an interface requires taking into account both the positive and negative effects that changes may have on the user. A carelessly picked adaptation may impose high costs to the user -- for example, due to surprise or relearning…
The investigation of tangible user interfaces commenced approximately thirty years ago. Questions on its commercial potential become more pressing as the field becomes mature. To take the field one step further -- as the emergence of…
Human-Computer Interaction (HCI) is a diverse field bringing together theories and methods from fields such as computer science, psychology, and human factors. Historically, HCI has focused on the human through ``user'' or ``human''…
Interactive Machine Learning is concerned with creating systems that operate in environments alongside humans to achieve a task. A typical use is to extend or amplify the capabilities of a human in cognitive or physical ways, requiring the…
Recent approaches in robotics follow the insight that perception is facilitated by interaction with the environment. These approaches are subsumed under the term of Interactive Perception (IP). It provides the following benefits: (i)…
Swarms of robots will revolutionize many industrial applications, from targeted material delivery to precision farming. Controlling the motion and behavior of these swarms presents unique challenges for human operators, who cannot yet…
The continuous adaptation of software systems to meet the evolving needs of users is very important for enhancing user experience (UX). User interface (UI) adaptation, which involves adjusting the layout, navigation, and content…
Human-Computer Interaction has been shown to lead to improvements in machine learning systems by boosting model performance, accelerating learning and building user confidence. In this work, we aim to alleviate the expectation that human…
We present a method to simulate movement in interaction with computers, using Model Predictive Control (MPC). The method starts from understanding interaction from an Optimal Feedback Control (OFC) perspective. We assume that users aim to…
As automated machine learning (AutoML) systems continue to progress in both sophistication and performance, it becomes important to understand the `how' and `why' of human-computer interaction (HCI) within these frameworks, both current and…
As Artificial Intelligence (AI) technology becomes more and more prevalent, it becomes increasingly important to explore how we as humans interact with AI. The Human-AI Interaction (HAI) sub-field has emerged from the Human-Computer…
Including pairwise interactions between the predictors of a regression model can produce better predicting models. However, to fit such interaction models on typical data sets in biology and other fields can often require solving enormous…
Center touchscreens are the main HMI (Human-Machine Interface) between the driver and the vehicle. They are becoming, larger, increasingly complex and replace functions that could previously be controlled using haptic interfaces. To ensure…
Human interaction relies on a wide range of signals, including non-verbal cues. In order to develop effective Explainable Planning (XAIP) agents it is important that we understand the range and utility of these communication channels. Our…
The way humans interact with each other, including interpersonal distances, spatial configuration, and motion, varies significantly across different situations. To enable machines to understand such complex, context-dependent behaviors, it…
Explainable AI (XAI) interfaces seek to make large language models more transparent, yet explanation alone does not produce understanding. Explaining a system's behavior is not the same as being able to engage with it, to probe and…
Participatory design effectively engages stakeholders in technology development but is often constrained by small, resource-intensive activities. This study explores a scalable complementary method, enabling broad pattern identification in…
Human-Object Interaction (HOI) detection is a core task for human-centric image understanding. Recent one-stage methods adopt a transformer decoder to collect image-wide cues that are useful for interaction prediction; however, the…
The principles of statistical mechanics and information theory play an important role in learning and have inspired both theory and the design of numerous machine learning algorithms. The new aspect in this paper is a focus on integrating…