Shenghan Zhang

Shenghan's research interests focus on developing some practical and effective deep learning models to help automatically classify medical images in various formats. During college, Shenghan has designed an improved contrastive learning method based on the SimCLR to distinguish positive Covid-19 CT scans. He also worked on a data mining research project in electronic health records (EHR) like Mimic series datasets as a research assistant at Rice University. 

His research interests include computer vision, deep learning, medical image classification, data mining. 

Previous Education: 

BEng., Data Science and Big Data Technology - Xi'an Jiatong-Liverpool University