Screen or No Screen? Lessons Learnt from a Real-World Deployment Study of Using Voice Assistants With and Without Touchscreen for Older Adults


How do Older Adults Set Up Voice Assistants? Lessons Learned from a Deployment Experience for Older Adults to Set Up Standalone Voice Assistants

DIS 2023

Design and Development of a Training and Immediate Feedback Tool to Support Healthcare Apprenticeship

CHI 2023

UnMapped: Leveraging Experts’ Situated Experiences to Ease Remote Guidance in Collaborative Mixed Reality

CHI 2023

Investigating Input Modality and Task Geometry on Precision–first 3D Drawing in Virtual Reality

ISMAR 2022

VRContour - Bringing Contour Delineations of Medical Structures Into Virtual Reality

ISMAR 2022

Towards Visualization of Time–Series Ecological Momentary Assessment (EMA) Data on Standalone Voice–First Virtual Assistants

ASSETS 2022 To explore the potential opportunities for visualizing time-series based EMA data on standalone IVAs, we designed a prototype system, where older adults are able to query and examine the time–series EMA data on Amazon Echo Show — a widely used commercially available standalone screen–based IVA

Exploring Needs and Design Opportunities for Virtual Reality-based Contour Delineations of Medical Structures

EICS 2022 We present an exploratory study that uses iterative design to understand needs and opportunities to bring contour delineation into an immersive 3D space, such as the one enabled by today’s head-mounted VR displays

Evaluating Accuracy, Completion Time and Usability of Everyday Touch Devices for Contouring

ASTRO 2022 Daily re-evaluation of contours associated with adaptive planning is time-intensive and difficult to access. This project evaluated the efficacy of everyday touch devices for contouring using a novel cross-platform interface.

Battling Bias in Primary Care Encounters: Informatics Designs to Support Clinicians

CHI 2022 To understand the perspectives of clinicians on the design of effective educational strategies and for tools to help identify implicit bias, we conducted 21 semi-structured interviews with primary care clinicians about their perspectives and design recommendations for tools to improve patient-centered communication and to help mitigate implicit bias.