Workers with intellectual and developmental disability often encounter challenges in professional workplaces, including barriers to effective task performance and equitable participation. Social Collaborative Robots (SCRs) present a promising opportunity to foster inclusive work environments by offering ability-based support tailored to individual strengths. This research aims to explores how SCRs can be leveraged at workplaces to assist workers with intellectual and developmental disability and share responsibilities carried by people in their employment support networks. Preliminary findings from workplace observations and interviews reveal that workers with intellectual and developmental disability can partake in variety of work activities and can benefit from assistive technologies that align with their cognitive abilities and job requirements, ultimately enhancing their task performance and workplace inclusion.
Aphasia, which is a language disorder that affects a person's ability to communicate, can present profound challenges in one's daily life. Augmentative and Alternative Communication (AAC) technology can support people with aphasia (PWA) in navigating such challenges, but often overlooks personalized comunication needs. End-user programming, which allows a user to develop and use their own custom programs, presents a promising solution where people with aphasia can create their own solutions based on their personal communication needs. With the advent of generative AI such as large language models (LLMs) to augment PWA communication, my dissertation investigates how end-user programming can be designed so that PWA can create and customize AI-driven tools to support their communication. I center my research on two research goals. First, by conducting co-design workshops and semi-structured interviews, I will investigate how end-user programming can be accessible for PWA, and its usefulness in various communication settings grounded in PWA's lived experiences. Then, I aim to understand the feasibility of real-world designs by building and evaluating prototypes based on the knowledge gained from the first research goal. This research aims to understand how empowering PWA in creating their own tools can promote conversational agency in AI-driven communication tools.
Psychological safety is the shared belief that team members feel safe to take interpersonal risks in the form of learning behaviors like seeking feedback or admitting mistakes in the workplace. Psychological safety plays an essential role in communication, especially in tightly coupled team activities like mob programming (i.e., mobbing), in which three or more team members develop software together. Mobbing requires members to play different roles while suggesting and digesting new ideas, which makes them particularly vulnerable to interpersonal risk. Autistic software engineers can struggle with mob programming, as they experience high levels of anxiety and stress when communicating with others due to their different cognitive and communication styles, and commonly co-occuring conditions like ADHD and social anxiety. A collaborative space that allows autistic team members to flexibly communicate in neurodiverse teams can increase the psychological safety and accessibility of collaborative software development. To identify tools and practices that foster psychological safety in neurodiverse collaborative mob programming, I will conduct a series of mixed-method, design-based studies. First, I conduct a survey and interview study to uncover the relationship between neurodivergent cognitive and communication traits and psychological safety in teams. Second, I generate design principles for psychological safety through the iterative design and evaluation of a neuroinclusive digital collaboration space. Third, I evaluate the impact of these design principles through an experiment with majority, minority and all neurodivergent teams. My work makes the following contributions to accessible software engineering education and practice: 1) Novel descriptions of psychological safety relating to neurodivergent cognitive and communication attributes; 2) design principles for fostering psychological safety in collaborative software development teams; 3) a software development tool that scaffolds psychologically safe mobbing in neurodiverse software teams.
Actively exercising and spectating sport are popular leisure activities, but have yet to become more accessible. While the SportsHCI research community is growing, technology is primarily researched for the non-disabled body. Further, accessibility often ends at the practical inclusion without aiming for equitable experiences. My PhD project orients towards endeavours in SportsHCI and addresses both active and passive engagement in sport. Through two case studies, I explore the accessibility of sports technology, i.e., study cycling and interactive seat plans, and provide a comprehensive account that considers both facets. Grounded in participatory methods, my research involves exploratory and qualitative methods that lay the foundation for the final prototypes of sports technology for people with reduced mobility.
My research interests are in human-computer interaction, accessibility, and creativity. My goal is to bring accessibility to the forefront of technology, enabling everyone to meet their needs and engage in a creative practice. Over the past year (2024–2025), I conducted research grounded in Crip Technoscience [1] to investigate how disabled artists repurpose technology to express identity and creativity rather than to "fix" disability. This work culminated in a paper, Expanding Norms, Negotiating Bodies: How Artists with Disabilities Perceive and Use Creative Tools [2], which was accepted to the ASSETS 2025 Conference. With the support of the SIGACCESS Travel Award, I was able to travel to Denver, Colorado, and attend the 2025 ASSETS conference in person. The travel grant also funded me to take part in the ASSETS 2025 Participant Recruitment in Accessibility Research Workshop.
Hearing parents of deaf and hard-of-hearing (DHH) children often struggle to provide meaningful sign input while simultaneously learning a new language. This summary includes a series of interactive systems to support accessible and engaging communication for parent-child interaction. Building on the Tabletop Interactive Play System (TIPS), a real-time ASL communication technology, my prior work has examined users' perceptions of system usefulness and autonomy. An ongoing study investigates four ASL support strategies, ranging from manual sign lookup to sentence translation and real-time sign recommendations, to examine their effects on communication effectiveness and user engagement in parent-child interaction. Extending this foundation, this summary proposes a research direction that explores a personalized recommendation model that adapts sign suggestions based on user preference and interaction history. Additionally, I introduce RhymASL, an interactive system that leverages ASL phonological features to support rhyming ASL stories creation that foster playful parent-child interaction. Across these efforts, my research aims to advance the design of assistive communication technologies that are responsive to diverse communicative needs and support meaningful interaction.
Commercial activity trackers frequently fail to meet the needs of older adults by focusing on generic metrics (e.g., step counts) while overlooking the personally meaningful activities that they may want to track in their everyday life. This disconnect stems from a fundamental challenge: the difficulty of capturing accurate ground-truth labels for complex, real-world activities, which forces a reliance on generic, one-size-fits-all models. My doctoral research seeks to address this problem by developing a human-centered approach to recognize activities that truly matter to individual older adults, moving beyond basic posture detection to a rich, semantic understanding of daily life. My research will culminate in a framework for a "teachable" activity tracker that older adults can train themselves. Part of my completed doctoral work establishes the need for personalization by demonstrating significant variability in older adults' movement patterns and deconstructs the challenges of collecting data "in the wild," quantifying the costs and benefits of triangulating sensor data with user-provided verbal reports. This is complemented by technical explorations into data-driven methods for optimizing on-body sensor placement. Ongoing work investigates the feasibility of older adults training their own personalized models in-situ through transfer learning. We are going to explore models capable of inferring high-level, meaningful activities (e.g., "gardening," "playing golf") from a stream of low-level sensor data. Ultimately, this thesis contributes initial steps toward a reframing of activity recognition—from an emphasis on technological capability to an emphasis on user-valued activities—thereby offering insights that could support the development of more personalized tools for older adults.
Visually impaired people (VIP) navigate by walking, using public transport, ride-sharing and getting lifts. While in some places this allows VIP to confidently take journeys at any time, transportation today leaves many accessibility barriers that cause access issues for VIP. In search of a solution to this issue, scholars have explored fully autonomous vehicles (FAVs) to bring VIP greater independence when travelling, but findings suggest FAVs cannot solve all mobility problems for VIP. This project explores the use of intelligent systems embedded into urban infrastructure, co-created with VIP and professionals involved in shaping the urban environment, to find technological solutions to today's accessibility barriers. This project also seeks to contribute an account of conducting human-centred methods from the perspective of a visually impaired researcher. This account aims to guide future work on developing accessible research methods to encourage people with disabilities to approach the HCI field as researchers.
Podcasting has become a significant medium, contributing to domains such as delivering news and entertainment, enriching learning and education, and supporting advocacy and community development. Nowadays, podcast production is no longer limited to professionals with high-end equipment, and amateurs and independent creators produce their own episodes. Technological advances have driven this shift of making podcast production widely available, especially for audio engineering — the craft of recording, manipulating, and reproducing sound. However, research is limited on the accessibility of audio engineering for podcast creation, particularly by deaf and hard of hearing (dHH) individuals. To fill this gap, my dissertation aims to investigate the creation of podcasting by dHH individuals focusing on audio engineering. This research consists of three phases: (1) understanding the current state of accessibility in audio engineering by dHH individuals, (2) identifying the practice of sound design tasks for podcasting in detail, and (3) co-designing and evaluating prototypes to support sound design tasks with dHH individuals. My primary contributions aim to gain a deeper understanding of the creative practices of audio engineering by dHH individuals and to explore design considerations and techniques for accessible audio engineering, specifically relevant to sound design tasks. I envision empowering the dHH individuals' creations through auditory mediums.
Since this was my first time at ASSETS, I felt a mix of nervousness and excitement. I was excited to have the chance to connect with fellow researchers and practitioners working across different areas in accessibility. However, my nerves came from my desire to make the most of every resource available, whether that meant having one-on-one conversations with experts who could offer valuable insights into my future career path or attending talks that gave me the breadth and depth needed to stay informed about our community's innovations and guide my own work. I also worried about feeling out of place, as I expected many conference attendees would already know each other.
This report reflects on my attendance at the ASSETS 2025 conference in Denver, made possible by a SIGACCESS travel grant. As a speaker and co-presenter, I collaborated with Dr. Doga Buse Cavdir to present our paper, "Sonic Agency: A Group Autoethnography of Technology-mediated Performance Practice by Deaf and Hard of Hearing Musicians." This reflection details the significance of our in-person collaboration, the impact of our bilingual presentation, and the professional networking that revealed new academic pathways. The experience validated my technical contributions to accessibility research and opened unexpected doors for completing my degree.
Communication challenges between autistic and neurotypical individuals stem from a mutual lack of understanding of each other's distinct, and often contrasting, communication styles. Yet, autistic individuals are often expected to adapt to neurotypical norms, making interactions inauthentic and mentally exhausting for them. To redress this imbalance, we propose the design of communication technologies that leverage generative artificial intelligence (AI) to facilitate adaptation by both, autistic and non-autistic, conversational partners. First, we present the design and evaluation of NeuroBridge [50], an interactive platform designed to help neurotypical individuals better understand autistic forms of expression and reflect on how their own behavior shapes cross-neurotype interactions. NeuroBridge utilizes large language models (LLMs) to simulate a) an AI character configured to be direct and literal, a style common among many autistic individuals, and b) four cross-neurotype communication scenarios in a feedback-driven conversation between the character and a neurotypical user. Informed by prior work and vetted by an advisory board of autistic individuals, these scenarios reflect common communication challenges faced by autistic individuals. In a user study with 12 neurotypical participants, we find that NeuroBridge improved their understanding of how autistic people may interpret language differently, with all describing autism as a social difference that "needs understanding by others" after completing the simulation. Second, we present the design and evaluation of TwIPS [2], an LLM-assisted texting interface designed specifically for autistic users. TwIPS provides three core features: Interpret, which explains tone and ambiguity in incoming messages; Preview, which forecasts how one's message may be received; and Suggest, which offers alternative phrasings while preserving user intent. In an in-lab study with 8 autistic participants, we find that TwIPS supported clearer expression and interpretation, provided a preferable alternative to tone indicators, and anecdotal evidence indicating that it reduced the cognitive burden associated with masking. Finally, we outline directions to unify the principles established in recent work to develop communication support tools that can assist multiple conversational partners within the same cross-neurotype interaction.
This research explores the use of generic images as a medium for non-verbal communication among individuals with intellectual disabilities. Unlike traditional visual symbols, generic images depicting natural scenes and meaningful life events offer richer contextual cues, making them more intuitive and easier to understand. While existing assistive technologies—such as Augmentative and Alternative Communication (AAC) systems and Visual Scene Displays (VSDs)—primarily emphasize language acquisition, my approach seeks to support broader goals of self-expression, social connection, and group participation. To enhance communication, I leverage image recommendation systems combined with user intent detection to facilitate more accessible and meaningful image selection for communication and clarification. The research adopts a participatory design methodology, involving iterative co-design of prototypes with participants from disability service organizations. Initial exploratory studies examined image-based communication and intent detection using Large Language Models, followed by the development and evaluation of algorithms aimed at improving image accessibility through simulated-user testing. Current work focuses on prototype implementations that investigate image intent interpretation within assistive communication contexts, aiming to identify system requirements and assess the impact on the daily interactions of individuals with intellectual disabilities.
Voice-based conversational agents are becoming increasingly integrated into everyday life through mobile devices and smart speakers. These systems offer considerable potential to enhance social inclusion, independence, and engagement in daily activities for individuals with intellectual disabilities. However, mainstream conversational agents such as Google Home and Alexa Echo Show are primarily designed for neurotypical users and often fail to accommodate the cognitive and communication needs of individuals with intellectual disabilities. Consequently, this population experiences significant barriers when attempting to access and use such technologies meaningfully. This research explores how conversational agents can be effectively designed and developed to support individuals with intellectual disabilities. The study began with a systematic literature review examining existing research on conversational agents for this population. Following this, a user study was conducted over two-month period in a disability support organization, to investigate the specific needs, preferences, and challenges faced by individuals with intellectual disabilities when interacting with off-the-shelf systems. Drawing on these insights, a customized conversational agent is currently being designed and developed to address key accessibility and usability challenges. In the final phase, the agent will be deployed and evaluated in real-world settings to assess its usability, effectiveness, and impact on user engagement.
Co-reading, the practice of parents reading together with their children, is crucial for the development of children's literacy, cognitive skills, and social-emotional growth. However, my published interview study found that visually impaired parents (VIPs) face accessibility barriers inherent to the design of children's books, while their assistive technologies (ATs) fail to be co-accessible to their sighted children and are disruptive in the intimate setting of co-reading; as a result, VIPs often compromise access in favor of more intimate reading modalities. My follow-up study, currently underway, builds on my concept of intimate assistive technologies (IATs), which articulates a need to support relational and emotional connections in assistive technology design, through the participatory design of nondisruptive voice assistants (VAs) to support co-reading. Overall, my research will contribute (1) the concept of IAT, (2) design patterns for developing image descriptions for children's books, and (3) a scalable, freely available IAT for co-reading.
Financial technology (FinTech) increasingly impacts economic and social participation due to the growing adoption of online banking and digital payments in everyday life. As FinTech interests emerge in academic and industry work across the globe, critical needs and opportunities arise for accessible computing communities to lead and shape the discourse on accessible FinTech. To address this, we ran an online workshop (https://accessfintechworkshop.github.io/) as part of the ACM SIGACCESS Conference on Computers and Accessibility (ASSETS'24) to bring together researchers and practitioners interested in designing accessible and inclusive FinTech. By identifying diverse stakeholders, key challenges, design ideas, and research questions, this workshop started developing a research agenda for accessible FinTech. We took a timely step towards building a community to support continued discussion on the complex social and user contexts around FinTech.
Researchers have investigated visual and vibrotactile approaches to making music more accessible to d/Deaf individuals, focusing on music appreciation. However, these approaches often fail to help d/Deaf users fully understand and engage with the various musical elements of a song. My research addresses this gap through a series of design and evaluation studies with d/Deaf and non-d/Deaf participants. It begins with a formative study that identifies key attributes of song signing valued by the Deaf community. Building on this, a controlled study explores the use of disclosure statements to mitigate cultural misrepresentation. Finally, a systems study leverages Large Language Models (LLMs) to support the translation of lyrics to sign language. My next steps involve developing collaborative tools for song signers and facilitating culturally sensitive music experiences. These projects collectively bridge the gap between d/Deaf and non-d/Deaf communities, promoting intercultural understanding and expanding musical inclusivity.
Adulthood brings new opportunities for people with Down syndrome (DS) to pursue occupational goals, yet the reduction in support services after school can create challenges in achieving them. Employment options often focus on roles that do not fully leverage the diverse abilities of individuals with DS, highlighting the need for more tailored training and pathways for advancement. Technology has the potential to bridge these gaps by offering innovative resources to empower individuals to achieve their goals. While research has explored technology design for people with intellectual disabilities, there is a notable need for a deeper understanding of the specific preferences of adults with DS. My research seeks to address this by designing and developing tangible and visual technologies that consider the abilities and interests of adults with DS. By prioritizing age-appropriate and context-sensitive content, I strive to create systems that effectively support and empower adults with DS.
Older adults are increasingly integrating technology into their daily lives but often need guidance to navigate new tools effectively. Some benefit from real-time support from family members, while others prefer self-paced, asynchronous help. To meet their diverse needs, I propose two solutions: HelpCall and SoftBox. HelpCall provides synchronous guidance through an assistive video overlay, helping older adults follow instructions from remote family members. In contrast, to support asynchronous assistance, SoftBox generates guided interactive software mockups from screencast demonstrations to allow learners to independently explore and learn new features in a sandbox-like environment. Through user studies with older adults and their family members, these projects offer complementary insights into synchronous and asynchronous support, advancing accessible technology for diverse learning needs and contexts and moving toward universal accessibility in digital tools.
The 26th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS 2024) was held October 27th to 30th, 2024 as a hybrid event in St. John's, Newfoundland and Labrador, Canada. The ASSETS conference is the premier computing research conference exploring the design, evaluation, and use of computing and information technologies with and for people with disabilities and older adults. This year, the ASSETS conference continued its tradition of presenting innovative research on mainstream and specialized assistive technologies, accessible computing, and assistive applications of computer, network, and information technologies. 341 attendees from 24 countries attended the conference, including 233 in-person, 50 workshop-only, and 58 virtual attendees.
