Research Projects

Integrated CMOS Sensors and Circuits for Life Science Applications

Our laboratory contributes to CMOS chip design by developing architectures that integrate sensors with on-chip interface circuitry (conditioning, readout, processing). This co-design enables miniaturized, low-power, high-integrity platforms with reduced parasitics and scalable manufacturing potential. Our work emphasizes CMOS- compatible capacitive sensing for high-throughput systems applied to health diagnostics, environmental monitoring, and related bioengineering and industrial applications..

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Open Gate Junction Field Effect Transistor (OG-JFET) sensor diagram

Open Gate Junction Field effect Transistors for Life Science Applications

OG-JFET is a novel FET configuration featuring a back gate and an open-top architecture fabricated through a standard CMOS foundry process. Our laboratory has contributed to this area by developing multiple OG-JFET chip generations and their companion interface/readout circuits, enabling highly precise sensing of charged and polar molecules.

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Electrochemical sensor for COVID-19 detection

Electrochemical Sensing Reader for Cellular and Molecular Quantification

Electrochemical sensors based on impedimetric and cyclic voltammetry techniques are widely used across diverse applications. BioSA has developed embedded interface and readout systems that enable these sensing modalities for multiple use cases, including cellular monitoring and COVID-19 detection.

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Firefighter in a hazardous environment, representing PAH exposure assessment research

Real-Time Sensing Platforms for Carcinogenic Contamination and Exposure Assessment in Firefighting Environments

Firefighters operate in complex and highly toxic environments where exposure to carcinogenic compounds, including polycyclic aromatic hydrocarbons (PAHs), can be significant. This project focuses on developing advanced chemical sensor technologies that enable real-time detection and quantification of these hazards, supporting rapid assessment of contamination and exposure risk during firefighting operations.

DePerio: Deep Learning–Based Periodontal Disease Quantification

We pioneered an integrated platform that combines AI, microfluidics, and microelectronics with established periodontal assessment methods to quantify the oral inflammatory load. This quantification provides a measurable biomarker that can support early detection and monitoring of periodontal disease. Because periodontal inflammation is increasingly associated with broader systemic health risks, DePerio also enables research and potential screening pathways related to comorbid conditions such as cardiovascular disease, Alzheimer’s disease, and diabetes.

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