By Peter Murphy
Published April 9, 2025
Wei Bo, a PhD student in computer science and engineering, has been recognized as a Cyber-Physical Systems (CPS) Rising Star. Her research incorporates AI with health technologies, ranging from noninvasive ways to screen for Alzheimer’s Disease to securing the privacy of health monitoring systems.
The National Science Foundation’s CPS Virtual Organization selects its CPS Rising Stars through a competitive process. This year, 30 graduate students and postdocs were selected from a pool of over 170 applicants. Bo will attend the CPS Rising Stars Workshop at Vanderbilt University later this month.
CPS research areas, according to the National Science Foundation, include control, data analytics, machine learning in real-time for control, autonomy, design, Internet of Things, mixed initiatives like human-in- or human-on-the-loop, networking, privacy, real-time systems, safety, security, and verification.
“This is a prestigious honor for PhD students in the field, and it is highly selective,” says Wenyao Xu, professor and associate department chair in the Department of Computer Science and Engineering and Bo’s PhD advisor.
Wei Bo, CPS Rising star and PhD student
Bo uses AI to address critical challenges in early disease detection, home-based health care and secure health monitoring. Some of the tools she developed have helped children who may require speech and language services and adults who may be experiencing Alzheimer's Disease and Related Dementias (ADRD).
“I have developed AI-powered tools that analyze speech patterns to detect language impairments in children and screen for ADRD,” Bo says. “These tools use simple voice recordings to identify early signs of cognitive or speech disorders, allowing for earlier intervention and better outcomes.”
Her tool could have significant impacts on the way the disease is not only detected but treated as well.
“My work explores human voices as a biomarker for early detection—years before symptoms appear, offering a noninvasive and accessible screening method. Early detection allows for timely interventions, slowing disease progression and improving quality of life,” Bo says. “Besides early detection, patients can utilize our smartphone applications for daily cognitive monitoring and practice.”
Bo has also designed secure health monitoring systems using smart devices, including a system combining a 3D-printed device and a smartphone to assist stroke patients with their recovery. Bo’s research is patient-centered, but it also helps advance AI-driven health care. In 2024, she was part of a team that secured $50,000 in funding and earned first place in the National Institute on Aging’s PREPARE Challenge Phase 1, where her team curated a standardized and large-scale dataset to improve early screening in ADRD and contribute to further ADRD research.
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