"I would rather fail in a cause that will ultimately triumph than to triumph in a cause that will ultimately fail."
- Woodrow Wilson
-Designed a novel architecture integrating attention mechanisms and clustering methods to enhance interpretability and discriminate abnormalities in thyroid WSIs.
-Designed the 2-step cascaded architecture based on CNN and CRNN(CNN+RNN) to predict TERT promoter mutational status in thyroid cancer.
-Built 3D models to identify the correlation between appendicitis diagnoses from non-contrast CT scan and enhanced CT scan.
-Developed a cascaded deep learning architecture, considering diverse window values to enhance the sensitivity of predicting hemorrhages in brain CT images.
-Designed novel deep neural networks by combining the VGG16 architecture with the Unet concept and modified pooling layers based on semantic segmentation method.
-Developed back-end engines for the deep learning medical platform to integrate in front-end UI/UX.
Graded submitted materials and provided feedback with guidance for over a year in two classes of computer science department; COMP.1000 Media Computing, COMP.2030 Computer Org & Assembly Language.
On weekends, I love spending time outdoors. During the spring and summer, I play baseball and enjoy riding my motorcycle.
In my spare time, I dive into music production. I believe musical creativity can inspire a positive and motivated outlook on life. I also enjoy exploring and keeping up with cutting-edge developments in artificial intelligence.