People / Students / Class of 2027
Juntong Ye earned her Bachelor of Science in Data Science from the University of California, San Diego. Her academic training spans statistical computing, machine learning, neural networks, and statistical genomics, supported by technical proficiency in Python, R, SQL, and cloud platforms including AWS.
Prior to joining the MLDS program, Juntong contributed to single-cell genomics research at Scripps Research and HHMI, building automated RNA sequencing pipelines and fine-tuning gene expression transformer models across tissue types. Her undergraduate capstone project developed an end-to-end machine learning pipeline for early ICU sepsis detection on AWS, achieving strong sensitivity and F1 performance up to four hours before clinical onset. She also conducted neural decoding research with the SoCal Data Science group, designing models to classify neural activity patterns from spike recordings with high accuracy.
Through the MLDS program, Juntong aims to deepen her expertise at the intersection of machine learning and biomedical applications, with a particular interest in building models that translate directly into clinical decision support tools. She is drawn to questions of model interpretability, data pipeline reproducibility, and the responsible deployment of predictive systems in high-stakes healthcare settings.
