Honored to contribute to AI cardiovascular diagnostics!

．Developed automated validation protocols using C# for Panther system software, streamlining validation workflows and enhancing release efficiency.

．Designed and executed software V&V test cases for Panther system, ensuring seamless LIS integration and compliance with FDA, ISO 13485 regulations.

Graduate Capstone project | Collab. with UCSF, Advisor: Edilberto Amorim

．Extracted and analyzed burst suppression features from terabytes of EEG data, applying machine learning models to predict coma recovery outcomes (CPC scores).

．Developed logistic regression models on 5M+ clinical records to predict coma recovery (CPC scores), identifying key prognostic factors using SHAP analysis.

．Performed feature clustering using UMAP & PaCMAP, improving visualization of EEG burst patterns correlated with coma recovery prognosis.

Secured Government Funding | Top15/122, National TSMC Innovation Plan | YEF 1st

．Led and managed a cross-functional team (3 engineers & UI/UX designers) in the agile development of PLOGIN, a text-visualization platform prototyped since the 2021 YEF competition.

．Developed BERT-based model modifications with self-engineered text-to-graph algorithms, trained on 1M+ text data. Achieved 80%+ comprehension in graduate-level reasoning and text structuring through rigorous benchmarking.

．Designed and implemented automated text-analytics tools aligned with market needs, integrating Figma, ReactJS, and Django for an optimized user experience.

The Blood Capillary Refill Time (CRT) project (AI Clinical Program)

Supervisors : Prof. Chun-Yen Lin and Dr. Kai-Sheng Hsieh (Under Patent Review)

．Collaborated with Shuang-Ho Hospital to develop an AI/ML solution model that resolved clinical issues.

．Trained a hand gesture recognition machine learning model and visualized the results of the CRT value.