Leilei Shi
Research Summary
My current research mainly focused on biomedical electronics, microfluidics, lab-on-chip devices, biosensors, wearable and flexible electronics, and the implementation of machine learning and deep learning in healthcare applications. More specifically, my primary research is focused on developing smart healthcare platform for health monitoring, early disease diagnosis, prognosis, and disease treatment.
The main techniques used in our lab include dielectrophoresis (DEP), micro-farbication, electrical impedance spectroscopy (EIS), microfluidic simulation, and machine learning/ deep learning (ML/DL).
Major Research Directions
Rapid and Label-free Microfluidic Device for Biomarker Detection
This project's primary objective is the develop of point-of-care diagnostic tools based on liquid biopsies, enhancing early disease detection, treatment, and prevention. The target biomarkers include exosomes, microRNAs, cell-free DNAs, bacteria, and Cells.
In addition to disease diagnostic applications, the detection tool could be expanded to monitor and characterize the bacteria in drinking water management, and potentially reduce the risk of spread of contamination.
Wearable and Flexible Sensing Platform
The most precise way to monitor patients’ health conditions is by testing multiple physiological and biochemical indexes continuously and giving comprehensive real-time feedback. Although various wearable sensors have been developed, the general mechanical, electrical, optical, and chemical sensing modalities have remained isolated from each other.
The objective of this project is to fuse different sensors on the same platform, which should offer a more comprehensive monitoring and understanding of an individual’s physiological state. For example, instead of just measuring heart rate, we could understand the origin or cause of increased heart rate and attribute it as healthy or not (e.g., exercise vs. a cardiac event, or positive excitement vs. a panic attack, etc.).