Leilei Shi Research Focus

Research Focus: Dr. Leilei Shi
Assistant Profesor, Electrical Engineering
College of Charleston

Dr. Leilei Shi is an Assistant Professor of Electrical Engineering at the College of Charleston, where he leads research in microfluidics, bioelectronics, and AI-assisted sensing systems for biomedical applications. He serves as the contributing faculty for Thrust 1 (XAI-Enabled Biomedical Devices for Diagnostic and Planning Applications) of the ADAPT in SC project.

AI-Assisted Electrical Impedance Sensing for Exosome Characterization

Cancer remains a leading cause of mortality worldwide, largely due to late-stage diagnosis. Exosomes (40–150 nm), which carry molecular signatures of their cells of origin, have emerged as promising biomarkers for early cancer detection. However, conventional characterization methods (e.g., TEM, NTA, and western blotting) are often time-consuming, low throughput, and limited in capturing comprehensive biophysical properties.

To address these limitations, Dr. Shi’s work focuses on developing a label-free, non-invasive, and rapid platform based on Electrical Impedance Spectroscopy (EIS) integrated with artificial intelligence to probe the intrinsic dielectric properties of exosomes. We designed a microelectrode array with dielectrophoretic (DEP) manipulation, enabling active concentration of particles into the sensing region. This is combined with a resonance-enhanced impedance response in the MHz range, significantly improving signal sensitivity. Following signal acquisition, machine learning algorithms are applied to process the data, extract key features, and classify exosome subtypes.

Dr. Shi’s team is currently investigating optimal conditions for signal differentiation, including the tuning of external circuit components (e.g., inductors) and variations in suspending media. In parallel, we are evaluating the performance of different AI models, such as LSTM and CNN architectures, for improved signal processing and classification.