University of Michigan – Dearborn
Predoctoral fellows have been nominated by their programs and are selected through a competitive review process based on the creativity and impact of the research they are pursuing. The abstracts for recipients at the University of Michigan – Dearborn describe the framework, aims, and significance of each fellow’s dissertation and demonstrate the breadth of Rackham doctoral programs.
Abstracts
Private Edge as a Supplement to Public Edge
Zhengquan Li, Computer and Information Science
While current public edge infrastructures—such as Akamai edge servers and Content Delivery Networks (CDNs)—provide geographically distributed computation and storage, they often fall short for emerging application scenarios. a) Latency Constraints: My empirical measurements show that public edge servers are often far enough from end users to create communication latencies above 50 milliseconds, which is unacceptable for latency-sensitive applications like AR/VR and autonomous driving. b) Privacy Concerns: Public edge systems also pose privacy risks for applications that involve processing sensitive user data in shared environments. To address these challenges, my research leverages home routers and WiFi access points as “private edge” devices. These devices are typically only one hop away from users, privately owned, and underutilized in terms of computational and communication resources. By tailoring systems to specific application requirements, we can deliver ultra-low latency performance while preserving user data privacy, effectively positioning the private edge as a vital supplement to public edge infrastructures.
A Data-Driven Approach to Adaptive Vehicle Interfaces for Special Needs Users: Measuring Reactions, Concerns, and Emergency Requirements
Chengxin Zhang, Industrial and Systems Engineering
This dissertation focuses on enhancing vehicle interfaces and assistive functions for users with special needs, targeting human-machine interaction (HMI) in Level 0–2 automated vehicles. Building on preliminary findings that highlight user concerns during unexpected emergencies, the research combines literature review, virtual reality (VR) experiments, and simulated crisis scenarios to identify critical needs and barriers. Mixed-methods data (quantitative/qualitative) will be analyzed via advanced statistics to derive actionable insights. The outcomes aim to inform technical solutions that prioritize inclusivity, bridging gaps between current HMI standards and the diverse requirements of users. By integrating empirical evidence with design innovation, this work seeks to establish a framework for universally accessible vehicle interfaces, ensuring equitable access to emerging automotive technologies.