CIS Department Sabbatical Presentations: Dr. Heidi Feng and Dr. Wei Yu

Department of Computer and Information Sciences 

12:00 PM, Friday May 5, 2023 

7800 York Rd. Room 459

 

Title: Making Personal Health Data Accessible to People with Down Syndrome

Presenter: Jinjuan Heidi Feng, Ph.D., Professor, Department of Computer and Information Sciences

Abstract: Most patient-facing health portals present health data to people with Down Syndrome (DS) in ways that are inaccessible to them, making it difficult to interpret, understand and utilize the data to make informed decisions and behavioral changes. Previous literature suggests that storytelling may make data presentation more accessible and engaging. We are working on a multi-phase, mixed methods co-design project to investigate the potential of data storytelling at improving the accessibility and understanding of personal health data for adults with DS. Through the project, we gained understanding on the capabilities of people with DS regarding graphical information recognition, interpretation and engagement as well as the challenges that they encounter during the process. We also developed inclusive design methods and materials for facilitating the involvement of people with DS in design studies.

 

Title: Foundation and Application of Building Edge Intelligence in Cyber-Physical Systems

Presenter: Wei Yu, Ph.D., Professor, Department of Computer and Information Sciences

Abstract: Advancements in information technologies (sensing, computing, network communication, and data science, among others) have driven the development of cyber-physical systems (CPS), enabling various smart systems in energy, transportation, and manufacturing. While machine learning has been achieving remarkable success in several areas in recent years, applying machine learning in CPS to realize edge intelligence faces significant challenges and must consider the strict requirements concerning performance and security. Thus, it is critical to establish the foundations and applications of synergizing machine learning in CPS and address the two interconnected issues: how to leverage machine learning as a viable data analytics tool to improve the performance of CPS and the investigation of the security risk of integrating machine learning in CPS and the design of countermeasures. In this talk, I will introduce some of our recent research efforts in both directions, collaborating with Ph.D. students in my research group.

 

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This post was written by Ecton, Abbie S.