Our research in human-computer interaction focuses on creating and evaluating interactive systems. Acting as user advocates first and technology advocates second, we create advanced user interfaces and applications that incorporate mobile and collaborative technologies, interactive visualizations, and a wide range of interactions to improve the chance that new information technologies can be used and enjoyed by people for real purposes. We do this by studying the social, cognitive, and affective aspects of the user experience, as well as consequences for communities, organizations, and society. Specifically, we explore applications in areas such as behavior change for health and wellness, peer-to-peer exchange systems, collaborative learning environments, and geo-deliberation and decision-making in local communities.
Research Labs and Centers
The Applied Cognitive Science Laboratory aims to understand how the mind works by modeling its output and process through precise, computational, predictive descriptions. Our projects focus on models that explain human behavior for testing human-computer interfaces, expand our understanding of network formation, and explore how moderators such as caffeine and stress influence behavior. Our simulations show how the mind interacts with networked teams and communities and how these properties give rise to emergent group cognition.
The Artificial Intelligence Research Laboratory conducts research in artificial intelligence, machine learning, data mining, information integration, and semantic web. Its projects explore applications in bioinformatics, engineering informatics, cheminformatics, materials informatics, social informatics, and related areas.
The Center for Human-Computer Interaction is an interdisciplinary organizational unit for human-computer interaction research, instruction, and outreach within Penn State and beyond. The center seeks to leverage and integrate diverse HCI activities throughout the University to facilitate interdisciplinary faculty interaction relating to HCI issues, problems, and opportunities. Our work currently focuses on software and information design, end-user programming and design, collaborative learning, online communities, training and instructional design, community health applications, and many other areas.
The Collaboration and Innovation Laboratory works in concert with the Center for Human-Computer Interaction. Our research addresses a wide range of challenge areas in which people collectively and individually use information technology to learn and solve problems. Our work currently focuses on software and information design, end-user programming and design, collaborative learning, online communities, training and instructional design, community health applications, and many other areas.
The Crowd-AI Laboratory focuses on combining artificial intelligence with crowdsourcing to create systems that are more usable, robust, and intelligent. Our researchers work on real-time crowdsourcing, conversational agents, technical human-computer interaction, and natural language processing to understand how people can use automated technologies in context and how automated technologies serve people’s practical needs.
The Knowledge Visualization Laboratory seeks to understand the frontier issues in visual analytics, an area with a goal to augment data-driven decision-making by bridging computational capacities of computing systems and analytical skills of human beings. Our research focuses on the visualization-based tools that have become essential to human-data interaction by exploring the relevant cognitive theories, such as visual cognition, problem-solving theories, and learning theories, that impact human-computer interaction and decision-making.
The User Agency Lab studies issues involving how information, user information, and systems structure influence user agency. Current and past projects have explored ride sharing, collaborative documents, crowdsourcing, and social media.
The Wellbeing & Health Innovation Laboratory aims to develop novel human-computer interaction and UbiComp technologies to improve health and wellbeing at scale. Our research leverages mobile phones, sensors, and online data to passively model health behaviors and contexts. We also design data-driven and just-in-time interventions with a focus on sustained engagement. Our interdisciplinary research includes passive sensing of sleep and circadian disruption, relapse detection in bipolar disorder, and using Amazon Alexa for effective PTSD interventions.