UbiComp 2024 Workshop - Design with Autistic Children

About

The emergence of generative artificial intelligence technology such as the Large Language Model (LLM), the Large Vision Model (LVM) has presented promising outcomes in both academic and industrial domains and becomes ubiquitously used. However, still few works have been focused on implementing these technologies for children with Autism Spectrum Disorder(ASD).

In the meantime, the mainstream personalized training with interactive design for children with special needs still faces potential challenges. As such, the goal of this workshop is to provide a platform for researchers, software and medical practitioners, and designers to share and debate both the pros and cons of applying the Large Language Model (LLM) and Internet of Things(IoT) for diagnosis and personalized training for autistic children.

Through hosting multiple activities during the half-day workshop, including oral presentation, demo and panel discussion, we hope to use this opportunity to build a network of experts to dedicate our efforts on benefiting children with special needs and further inspire the research on taking advantage of the emerging ubiquitous technologies for these under-privileged users, caregivers and special education teachers.

Call For Participation

This workshop explores the benefits, challenges, and future directions for involving creative interactive design using LLMs and IoT with/for autistic children in personalized training. By engaging in presentations, demonstrations, and group discussions, participants will have the chance to exchange their related experiences and insights. Submissions of position papers, work-in-progress reports, or demonstration papers for a short presentation or demonstration related to the interactive design with autistic children using LLM and IoT for personalized training or relevant fields are welcomed.

Specifically, the workshop is expecting:

Position papers (2-4 pages) discussing research questions, opportunities, benefits, or challenges
Work-in-progress reports (2-4 pages) highlighting current research
Demonstration papers (1 page) illustrating a leading-edge system in use, under development, or at a testing stage

The suggested topics include (but are not limited to):

Optimized and personalized training for special education
AI, IoT, and/or Smart Sensors for special education
Large Language Models (LLMs), and/or Large Vision Models (LVM) for special education
Technology-Based Intervention(TBI) for special education
Interactive design with children
Emerging Applications for special education or healthcare

Authors of accepted works will be invited to present their submissions in a dedicated presentation or demo session.

Submission format: UbiComp/ISWC 2024 Proceedings Formats

Invited Speaker

Dr. Annuska Zolyomi

University of Washington

Dr. Zolyomi is an Assistant Professor in the Computing and Software Systems (CSS) Division at the University of Washington Bothell. She leads the Interaction Design for Education and Accessibility (IDEA) lab. Employing human-centered and value-sensitive design, she researches ways to make human-computer interaction (HCI) and socio-technical collaboration more inclusive to disabled and neurodiverse communities. Her deep knowledge of software engineering, accessible technology, and user-centered design has been recognized by the ACM Conference on Computer Supported Cooperative Work (CSCW) and the ACM Conference on Computers and Accessibility (ASSETS). She earned her Ph.D. in Information Science, Sc.B. in Industrial Engineering and her M.S. in Human-Centered Design and Engineering from the University of Washington. Prior to earning her Ph.D., Zolyomi worked at Microsoft as an accessibility product strategist, with cross-company influence on technology innovation earning her four patents in HCI.

Origanizers

Yongfu Wang is a PhD student in the University of Nottingham Ningbo China Computer Science program. He received the master degree in Computer Science from Northwestern University (US) and bachelor degree in Computer Science and minor in Mathematical Science at Wenzhou-Kean University. His PhD research interest focuses on utilizing ubiquitous wearable sensors and Internet-of-Things (IoT) devices with haptic sensing for healthcare. His prior work was published at ACM CHI, CSCW and UbiComp conferences.

Mingyue Tang is a Ph.D. student in the Department of Computer Science at the University of Illinois Urbana-Champaign (UIUC). She received her master’s degree from the University of Virginia (UVa) Link Lab. Her research interests include wireless sensing, mobile computing, signal processing, and Internet of Things (IoT) in health. Through her work, she aims to create innovative solutions that can address real-world problems and make a positive impact on society. Her prior work was published at ICLR, KDD, IPSN, SenSys, etc. conferences, and ACM Transactions on Sensor Networks (TOSN), SPJ Health Data Science journals.

Dr. Yifan He is an assistant professor at Dept. of Software Engineering, Zhejiang University of Finance and Economics. He received his Ph.D. and Master’s degree at the University of Tsukuba, Japan in 2023 and 2020, respectively. Currently, his research interests include evolutionary optimization and learning, and evolvable hardware. He aims to build an evolvable and intelligent problem-solving system. Previously, he received his Bachelor’s degree at Wenzhou Kean University, China in 2017, where he conducted several studies in HCI and assistive technology. His prior work was published at GECCO, HCII conferences and Operations Research Perspectives journals, etc. He is a reviewer of several journals and conferences, such as Information Sciences, IEEE Trans. on Evolutionary Computation, and ALIFE, etc.

Dr. Tiffany Y. Tang is an associate professor at Wenzhou-Kean University. In May 2015, she co-founded the Center on Innovation and Assistive Technology for Autism & Neurodevelopmental Disorders at Wenzhou-Kean University (then called Wenzhou-Kean Autism Research Center). Till now, her team has published a total of 26 book chapters, journal and conference papers related to innovative technology for autism. Dr. Tang’s most recent research interests include affective computing and computational sensing on autism, sensing and wearable technologies for humans.