Predicting Trust In Autonomous Vehicles: Modeling Young Adult Psychosocial Traits, Risk-Benefit Attitudes, And Driving Factors With Machine LearningLow trust remains a significant barrier to Autonomous Vehicle (AV) adoption. To design trustworthy AVs, we need to better understand the individual traits, attitudes, and experiences that impact people's trust judgements. We use machine learning to understand the most important factors that contribute to young adult t…2025RKRobert A Kaufman et al.University of CaliforniaAutomated Driving Interface & Takeover DesignExplainable AI (XAI)AI-Assisted Decision-Making & AutomationCHI
Interactions Beyond the Pandemic: Lessons Learned from Large-scale Emergency Remote Teaching in Higher EducationOnline education — given the enhanced access for diverse populations and flexible participation — has been a topic of interest for many computer science and learning science researchers. The sudden shift to online settings during the COVID-19 Emergency Remote Teaching (ERT) provided a valuable opportunity to examine t…2025MYMatin Yarmand et al.University of CaliforniaOnline Learning & MOOC PlatformsCollaborative Learning & Peer TeachingCHI
Towards Dialogic and On-Demand Metaphors for Interdisciplinary ReadingThe interdisciplinary field of Human-Computer Interaction (HCI) thrives on productive engagement with different domains, yet this engagement often breaks due to idiosyncratic writing styles and unfamiliar concepts. Inspired by the dialogic model of abstract metaphors, as well as the potential of Large Language Models…2025MYMatin Yarmand et al.University of CaliforniaHuman-LLM CollaborationPrivacy by Design & User ControlTechnology Ethics & Critical HCICHI
What Did My Car Say? Impact of Autonomous Vehicle Explanation Errors and Driving Context On Comfort, Reliance, Satisfaction, and Driving ConfidenceExplanations for autonomous vehicle (AV) decisions may build trust, however, explanations can contain errors. In a simulated driving study (n = 232), we tested how AV explanation errors, driving context characteristics (perceived harm and driving difficulty), and personal traits (prior trust and expertise) affected a…2025RKRobert A Kaufman et al.University of CaliforniaAutomated Driving Interface & Takeover DesignExplainable AI (XAI)AI-Assisted Decision-Making & AutomationCHI
Enhancing Accuracy, Time Spent, and Ubiquity in Critical Healthcare Delineation via Cross-Device ContouringImproving accuracy, time spent, and ubiquity of delineation has been a long-standing design aim, yet many HCI works have overlooked high-stakes and complex healthcare annotation. We explore contouring, a critical workflow aimed at identifying and segmenting tumors, usually performed on immobile desktop computers in cl…2024MYMatin Yarmand et al.University of CaliforniaTelemedicine & Remote Patient MonitoringSurgical Assistance & Medical TrainingDIS
ConverSense: An Automated Approach to Assess Patient-Provider Interactions using Social SignalsPatient-provider communication influences patient health outcomes, and analyzing such communication could help providers identify opportunities for improvement, leading to better care. Interpersonal communication can be assessed through “social-signals” expressed in non-verbal, vocal behaviors like interruptions, tur…2024MBManas Satish Bedmutha et al.University of CaliforniaIntelligent Tutoring Systems & Learning AnalyticsMental Health Apps & Online Support CommunitiesTelemedicine & Remote Patient MonitoringCHI
Designing Communication Feedback Systems To Reduce Healthcare Providers’ Implicit Biases In Patient EncountersHealthcare providers’ implicit bias, based on patients’ physical characteristics and perceived identities, negatively impacts healthcare access, care quality, and outcomes. Feedback tools are needed to help providers identify and learn from their biases. To incorporate providers’ perspectives on the most effective way…2024EBEmily Bascom et al.University Of WashingtonAI Ethics, Fairness & AccountabilityPrivacy by Design & User ControlEmpowerment of Marginalized GroupsCHI
"I'd be watching him contour till 10 o'clock at night'': Understanding Tensions between Teaching Methods and Learning Needs in Healthcare ApprenticeshipApprenticeship is the predominant method for transferring specialized medical skills, yet the inter-dynamics between faculty and residents, including methods of feedback exchange are under-explored. We specifically investigate contouring: outlining tumors in preparation for radiotherapy, a critical skill that when per…2024MYMatin Yarmand et al.University of CaliforniaEV Charging & Eco-Driving InterfacesPrototyping & User TestingField StudiesCHI
PaperToPlace: Transforming Instruction Documents into Spatialized and Context-Aware Mixed Reality ExperiencesWhile paper instructions are one of the mainstream medium for sharing knowledge, consuming such instructions and translating them into activities are inefficient due to the lack of connectivity with physical environment. We present PaperToPlace, a novel workflow comprising an authoring pipeline, which allows the autho…2023CCChen Chen et al.University of California San DiegoMixed Reality WorkspacesContext-Aware ComputingUIST
UnMapped: Leveraging Experts' Situated Experiences to Ease Remote Guidance in Collaborative Mixed RealityCollaborative Mixed Reality (MR) systems that help extend expertise for physical tasks to remote environments often situate experts in an immersive view of the task environment to bring the collaboration closer to collocated settings. In this paper, we design UnMapped, an alternative interface for remote experts that…2023JJJanet G Johnson et al.University of CaliforniaMixed Reality WorkspacesContext-Aware ComputingTeleoperation & TelepresenceCHI
ARTEMIS: A Collaborative Mixed-Reality System for Immersive Surgical TelementoringTraumatic injuries require timely intervention, but medical expertise is not always available at the patient's location. Despite recent advances in telecommunications, surgeons still have limited tools to remotely help inexperienced surgeons. Mixed Reality hints at a future where remote collaborators work side-by-side…2021DGDanilo Gasques et al.University of CaliforniaMixed Reality WorkspacesTeleoperation & TelepresenceCHI
"It Feels Like I am Talking into a Void": Understanding Interaction Gaps in Synchronous Online ClassroomsThis paper investigates in-class interactions in synchronous online classrooms when the choice of modality is discretionary, such that students choose when and if they turn on their cameras and microphones. Instructor interviews (N = 7) revealed that most students preferred not to share videos and verbally participate…2021MYMatin Yarmand et al.University of CaliforniaOnline Learning & MOOC PlatformsCollaborative Learning & Peer TeachingCHI
Do You Really Need to Know Where 'That' Is? Enhancing Support for Referencing in Collaborative Mixed Reality EnvironmentsMixed Reality has been shown to enhance remote guidance and is especially well-suited for physical tasks. Conversations during these tasks are heavily anchored around task objects and their spatial relationships in the real world, making referencing - the ability to refer to an object in a way that is understood by ot…2021JJJanet G Johnson et al.University of CaliforniaMixed Reality WorkspacesKnowledge Management & Team AwarenessCHI
ExtraSensory App: Data Collection In-the-Wild with Rich User Interface to Self-Report BehaviorWe introduce a mobile app for collecting in-the-wild data, including sensor measurements and self-reported labels describing people's behavioral context (e.g., driving, eating, in class, shower). Labeled data is necessary for developing context-recognition systems that serve health monitoring, aging care, and more. A…2018YVYonatan Vaizman et al.University of CaliforniaHuman Pose & Activity RecognitionBiosensors & Physiological MonitoringCHI