Bio-Medical Applications | Prof. Eojin Rho

Overview

My research extends beyond traditional robotics into bio-medical applications, leveraging deep learning to solve complex problems in healthcare and diagnostics.

I have worked on Surface-Enhanced Raman Spectroscopy (SERS) analysis for rapid bacterial detection. By using deep learning models like DualWKNet, we can identify bacteria in arbitrary media without the need for time-consuming separation procedures.

Key Publications

Separation-free bacterial identification in arbitrary media via deep neural network-based SERS analysis

Eojin Rho, Minjoon Kim, Seunghee H. Cho, Bongjae Choi, Hyungjoon Park, Hanhwi Jang, Yeon Sik Jung, Sungho Jo

Demonstrated "DualWKNet" for rapid, separation-free bacterial detection using Surface-Enhanced Raman Spectroscopy (SERS) and deep learning. With outstanding classification accuracies up to 98%, this method serves as an effective platform for detection of bacteria in arbitrary media.

SERS Deep Learning Bio-Medical

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Reflection-Enhanced Raman Identification of Single Bacterial Cells Patterned Using Capillary Assembly

Joong Bum Lee, Eojin Rho, Minjoon Kim, Sejoon Huh, Seoyoung Kim, Stefan A. Maier, Emiliano Cortes, Sungho Jo, Yeon Sik Jung, Yoonsung Nam

Research on reflection-enhanced Raman identification of single bacterial cells patterned using capillary assembly.

Raman Spectroscopy Bacterial Identification Capillary Assembly

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