Project 1

AI-Assisted Classification of Single Yeast Cells Using Impedance Spectroscopy

(PROF. Stuart Williams, ME)

This project will explore the use of single-cell impedance spectroscopy and machine learning to classify yeast cells based on physiological state. The student will fabricate or assemble a simple microfluidic impedance sensor, collect impedance data from viable and stressed yeast populations, and use machine learning tools to distinguish between cell states using electrical signatures. The project will introduce students to microfabrication, biosensors, data analytics, and AI-assisted classification methods. Outcomes may include a proof-of-concept model for automated cell-state classification and a dataset suitable for future studies involving industrial fermentation processes.