heteRogEneous iNtegrAted multimodal nanoSensors with in-Sensor leArNing and inferenCE (RENAISSANCE) for TBI-on-a-chip
Interdisciplinary Areas: | Data and Engineering Applications, Engineering-Medicine, Innovation and Making, Future Manufacturing, Micro-, Nano-, and Quantum Engineering, Integrated Neuroscience and Engineering |
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Project Description
The ability to comprehend and forecast real-time changes in critical biomarkers can improve personalized treatment for many disorders, such as traumatic brain injuries (TBI). By leveraging accurate models of human physiology, TBI-on-a-chip holds immense potential in illuminating critical pathological mechanisms in a simplified and translatable model system. Nevertheless, several challenges impede the realization of TBI-on-a-chip’s full potential. Among these challenges is the limited ability to correlate biochemical pathological changes with functional changes (e.g., in electrophysiology) longitudinally in real time. While wearable nanosensors promise to enable non-invasive, continuous, sensitive monitoring of biomarkers, few can incorporate simultaneous monitoring of biochemical and electrophysiological biomarkers. Moreover, few studies have reported nanomaterials-based sensors for monitoring critical TBI-related biomarkers, primarily due to the intrinsic limitations of related materials. The RENAISSANCE framework will exploit across-the-stack innovation ranging from nanoscale semiconductors, sensor design, artificial intelligence, and neuropathology research. It will also engineer their seamless convergence to create a TBI-on-a-chip platform with the desired in-sensor learning capability. The developed system is expected to monitor levels of biochemical and electrophysiological biomarkers and deliver therapeutics to provide a multimodal approach for diagnosing and treating post-TBI neurodegeneration.
Start Date
03/01/2025
Post Doc Qualifications
The candidate should have a PhD in material sciences, biomedical engineering, electrical engineering, mechanical engineering, or related fields. Research expertise in electrophysiology, neuronal network, microfabrication, wearable sensors or nanomaterials is preferred.
Co-Advisors
Wenzhuo Wu
wu966@purdue.edu
Professor and University Faculty Scholar
School of Industrial Engineering
https://engineering.purdue.edu/wugroup
Riyi Shi
riyi@purdue.edu
Mari Hulman George Endowed Professor of Applied Neuroscience
Professor of Biomedical Engineering
Director, Center for Paralysis Research
Department of Basic Medical Sciences
Weldon School of Biomedical Engineering
College of Veterinary Medicine and Engineering
https://vet.purdue.edu/discovery/riyi/research.php
Bibliography
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