Han Liu is a Senior Research Scientist specializing in machine learning for medical image analysis with eight years of research experience spanning academia and industry. He holds a PhD in Computer Science from Vanderbilt and has led state-of-the-art work on 3D segmentation, modality dropout, partial-label learning, and cross-modality synthesis—winning first place in the MICCAI 2023 CrossMoDA validation and publishing novel methods like COSST. His work bridges algorithmic innovation and clinical application, from automated DBS target localization with uncertainty estimation to synthetic CT generation for MR-guided interventions. Now at Siemens Healthineers in New Jersey, he translates cutting-edge research into deployable solutions for medical imaging products. Beyond publications and challenge wins, he consistently improves practical annotation efficiency and robustness across heterogeneous, multi-institutional datasets.
8 years of coding experience
8 years of employment as a software developer
Master of Science Biomedical Engineering, Master of Science Biomedical Engineering at Yale University
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Vanderbilt University
Bachelor of Science Biomedical Engineering Electrical Engingeering, Bachelor of Science Biomedical Engineering Electrical Engingeering at Rensselaer Polytechnic Institute
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Han Liu - Senior Research Scientist at Siemens Healthineers