Summary
Zong Fan is a data scientist and Ph.D. candidate in Bioengineering at UIUC with a decade of experience applying deep learning to healthcare, bioinformatics, and video/image analysis. Currently at Johnson & Johnson, he builds and benchmarks foundation models for time-series wearable data—designing 1D/2D adaptations of CNNs and ViTs, applying self-supervised pretraining, and innovating loss and augmentation strategies to improve noise robustness. His background spans translational bioinformatics (NGS and single-cell), multimodal fusion for chemical and cellular profiling, and production-ready algorithm engineering for computer vision. Comfortable moving between research and applied engineering, he combines rigorous academic training (UIUC, Zhejiang) with hands-on model development and pipeline design. Outside work he’s a tech geek and snowboarder, reflecting a practical curiosity and appetite for iterative problem-solving in both labs and mountains.
11 years of coding experience
10 years of employment as a software developer
Doctor of Philosophy Bioengineering and Biomedical Engineering, Doctor of Philosophy Bioengineering and Biomedical Engineering at University of Illinois Urbana-Champaign
Bachelor of Science (BS) Biology, General, Bachelor of Science (BS) Biology, General at Zhejiang University
English