• Developed and optimized automated RNAseq and WES analysis pipelines using Python and R, achieving a 40% reduction in data processing time and enhancing the efficiency of research and clinical insights. • Implemented automated pipelines for disease risk analysis using SNP data, driving a 50% reduction in analysis time and enabling faster identification of high-risk individuals within the population. • Designed a highly efficient sanger sequencing analysis pipeline to accurately detect and analyze specific position mutations, resulting in a 45% reduction in analysis time and empowering faster genetic research breakthroughs. • Mentored and guided two interns, providing hands-on training in project management skills and research methodologies, equipping them with valuable industry insights and best practices, resulting in a 30% increase in their ability to tackle complex challenges. • Streamlined service workflow for all products by applying ERP system, collaborated with backend and frontend developer, resulting in a 40% reduction in response time and a 30% increase in case tracking efficiency. • Collaborated with cross-functional teams to design, deliver and customize comprehensive data visualizations and reports, enabling stakeholders to easily interpret complex data sets and make informed decisions, leading to a 70% increase in repurchase rate. • Assisted in IPO preparation and participated in drafting internal control system documents.

於陽明生醫資訊所擔任所學會會長，協助所上舉辦活動。如耶誕晚會、生醫資訊所校友回娘家等各項活動。

• Conducted comprehensive quantitative analysis on clinical and demographic data using statistical and machine learning approaches, resulting in the development of a hepatocellular carcinoma (HCC) risk prediction model. • Trained logistic regression model via 20 years of cohort data to predict the risk of HCC, which performances (AUC) of 10-year and 20-year were 0.91 and 0.85, respectively.