Kai Wu, an assistant professor in the Department of Electrical and Computer Engineering has received the National Science Foundation’s (NSF) CAREER Award
A Texas Tech University researcher is developing a new generation of wearable brain-imaging technology that could move complex neural study out of the lab and into everyday environments.
Kai Wu, an assistant professor in the Department of Electrical and Computer Engineering has received the National Science Foundation’s (NSF) CAREER Award to support the development of "FLEX-MEG," a flexible, quantum-enabled brain-imaging platform. The $500,000 grant, funded through the NSF’s Division of Electrical, Communications and Cyber Systems, recognizes early-career faculty with the potential to serve as academic role models in research and education.
Current brain-imaging systems that detect magnetic signals known as magnetoencephalography (MEG)—are often massive, expensive, and require cryogenic cooling. These constraints typically force patients to remain perfectly still in specialized facilities, making it nearly impossible to study the brain during natural movement or behavior.
Wu’s project aims to eliminate these barriers by using flexible, high sensitivity, magnetic sensor arrays that operate at room temperature. These lightweight arrays are designed to conform to the scalp, allowing the wearer to move freely while the system measures the brain’s weak magnetic signals.
"Understanding how the brain works requires tools that can measure neural activity safely, accurately, and in everyday environments," Wu said.
Technology does more than just "listen" to the brain. The FLEX-MEG platform explores a closed-loop system where magnetic sensing and noninvasive stimulation work together. This integration could eventually lead to precision treatments for neurological disorders through "neuromodulation," or the targeted adjustment of nerve activity.
To manage the massive amount of information generated by such a dense sensor array, Wu is developing "physics-aware compressed sensing" (PACS). This physics-guided, AI-integrated approach allows the hardware to compress and analyze neural data in real-time, preventing data-storage bottlenecks while maintaining high-resolution imaging. The project also includes collaborations with researchers at ETH Zurich, Texas Tech University Health Sciences Center, and Mayo Clinic, enabling integration of advanced sensor technologies with clinical and translational perspectives.
The impact of the research extends beyond the laboratory. The project includes a comprehensive plan for interdisciplinary education, involving undergraduate research courses, graduate training, and K-12 outreach. By partnering with industry leaders, the program aims to prepare students for careers in the emerging fields of quantum sensing and neurotechnology.
The CAREER program is the NSF’s most prestigious award for junior faculty, providing five years of sustained funding to support projects that integrate innovative research with workforce development.
Wu’s work at Texas Tech establishes a new pathway for wearable, noninvasive, high-resolution neural imaging, offering scientists a more realistic look at cognition and sensory processing while paving the way for advanced brain-machine interfaces.
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