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Mental health research can benefit increasingly fruitfully from computational linguistics methods, given the abundant availability of language data in the internet and advances of computational tools. This interdisciplinary project will…
Great advances in computing and communication technology are bringing many benefits to society, with transformative changes and financial opportunities being created in health care, transportation, education, law enforcement, national…
The interdisciplinary nature of Child-Robot Interaction (CRI) fosters incorporating measures and methodologies from many established domains. However, when employing CRI approaches to sensitive avenues of health and wellbeing, caution is…
As an emerging interaction paradigm, physiological computing is increasingly being used to both measure and feed back information about our internal psychophysiological states. While most applications of physiological computing are designed…
The recent advancements in Deep Learning models and techniques have led to significant strides in performance across diverse tasks and modalities. However, while the overall capabilities of models show promising growth, our understanding of…
Purpose of review: We review the literature on the use and potential use of computational psychiatry methods in Borderline Personality Disorder. Recent findings: Computational approaches have been used in psychiatry to increase our…
Computer perception (CP) technologies (digital phenotyping, affective computing and related passive sensing approaches) offer unprecedented opportunities to personalize healthcare, but provoke concerns about privacy, bias and the erosion of…
Reports of human-like behaviors in foundation models are growing, with psychological theories providing enduring tools to investigate these behaviors. However, current research tends to directly apply these human-oriented tools without…
Despite the indisputable personal and societal benefits of regular physical activity, a large portion of the population does not follow the recommended guidelines, harming their health and wellness. The World Health Organization has called…
For safety, medical AI systems undergo thorough evaluations before deployment, validating their predictions against a ground truth which is assumed to be fixed and certain. However, this ground truth is often curated in the form of…
We provide a psychometric-grounded exposition of bias and fairness as applied to a typical machine learning pipeline for affective computing. We expand on an interpersonal communication framework to elucidate how to identify sources of bias…
We propose a real-time human activity analysis system, where a user's activity can be quantiatively evaluated with respect to a ground truth recording. We use two Kinects to solve the ptorblem of self-occlusion through extraction optimal…
Mental health disorders create profound personal and societal burdens, yet conventional diagnostics are resource-intensive and limit accessibility. Advances in artificial intelligence, particularly natural language processing and multimodal…
We present HippoCamp, a new benchmark designed to evaluate agents' capabilities on multimodal file management. Unlike existing agent benchmarks that focus on tasks like web interaction, tool use, or software automation in generic settings,…
Point clouds registration is a fundamental step of many point clouds processing pipelines; however, most algorithms are tested on data that are collected ad-hoc and not shared with the research community. These data often cover only a very…
Health and fitness wearable technology has recently advanced, making it easier for an individual to monitor their behaviours. Previously self generated data interacts with the user to motivate positive behaviour change, but issues arise…
This paper aims to enhance our understanding of substantive questions regarding self-reported happiness and well-being through the specification and use of multi-level models. To date, there have been numerous quantitative research studies…
Is there a relationship between computing costs and the confidence people place in the behavior of computing systems? What are the tuning knobs one can use to optimize systems for human confidence instead of correctness in purely abstract…
Assessment of job performance, personalized health and psychometric measures are domains where data-driven and ubiquitous computing exhibits the potential of a profound impact in the future. Existing techniques use data extracted from…
The emergence of synthetic data for privacy protection, training data generation, or simply convenient access to quasi-realistic data in any shape or volume complicates the concept of ground truth. Synthetic data mimic real-world…