San Wang
About San Wang
San Wang is a Senior Data Scientist with extensive experience in machine learning and data science, currently working at Enolink in the Greater Boston Area. He holds a Master of Science in Data Science from The George Washington University and has contributed to significant research in gastric cancer risk prediction.
Work at Enolink
San Wang currently serves as a Senior Data Scientist at Enolink, a position held since 2022. Prior to this role, he worked as a Data Scientist at the same company from 2019 to 2022. His tenure at Enolink spans a total of five years, during which he has contributed to various data-driven projects in the Greater Boston Area.
Education and Expertise
San Wang earned a Master of Science in Data Science from The George Washington University, studying from 2016 to 2018. He also holds a Bachelor's degree in Statistics from Sichuan University, where he studied from 2011 to 2015. His educational background equips him with a solid foundation in data analysis and statistical methodologies.
Background
Before joining Enolink, San Wang worked at Harvard Medical School as a Machine Learning Research Associate and Consultant in 2019. His experience at Harvard Medical School included a five-month role as a research associate and a six-month consultancy, both located in the Greater Boston Area. Additionally, he served as an NLP Research Assistant at The George Washington University in 2017.
Research Contributions
San Wang co-authored a research paper focused on explainable gastric cancer risk prediction using machine learning models. He participated in a significant study that gathered data from 129,223 patients to enhance gastric cancer risk prediction. His work involved the application of SHapley Additive exPlanations (SHAP) analysis to elucidate model predictions and the development of machine learning-based risk stratification models for gastric cancer.
Collaborations
San Wang collaborated with the Seoul National University Hospital Healthcare System Gangnam Center on a research project. This partnership highlights his engagement in international research efforts aimed at improving healthcare outcomes through data science and machine learning.