| Proj No. | A2247-251 |
| Title | A Smart APP for Glucose Analysis on a Chip |
| Summary | Light emission technology is a new sensing platform which can help identify many diseases and disorders. Laser emitting arrays will generate light and its intensity changes can provide critical information. In general, it is very difficult for us manually analyze and correlate images and identify the signals - as it is a tedious process and image interpretation is subjective from person to person. Here the goal of the project is to build an APP with image processing capability to quantify glucose. Hence, we are inviting students to work with us in developing smart algorithms to automate the analysis and subsequent classification/regression of data of light emitting colors as well as intensities. The student would work in a multi-disciplinary team on the following tasks: - Develop and apply feature extraction algorithms on microarray images and spectral data - Develop a simple user interface to facilitate the readout - Bonus: Develop or utilize deep learning models to train image data collected from chips Note that the arrays, device, and biosensors will be done by senior PhD students. FYP do NOT need to involve hardware part of experiments (unless interested). Please send me an email if you are interested. yucchen@ntu.edu.sg |
| Supervisor | A/P Yu-Cheng, Chen (Loc:S1 > S1 B1A > S1 B1A 26, Ext: +65 8228 7812) |
| Co-Supervisor | - |
| RI Co-Supervisor | - |
| Lab | CBB2 (formerly Machine Learning Lab) (Loc: S1-B4c-10, ext: 4882) |
| Single/Group: | Single |
| Area: | Intelligent Systems and Control Engineering |
| ISP/RI/SMP/SCP?: |