Kunjie Fan is a computational biologist and AI scientist with a Ph.D. in Biomedical Informatics and eight years of experience applying deep learning and graph-based models to genomics, proteomics, and drug discovery. He currently leads bioinformatics and AI efforts at Duality Biologics, building models for ADC target identification and large cellular models that integrate single-cell data with knowledge graphs. Previously he advanced DNA and protein large-language models and generative design at GenScript and developed transformer and GNN approaches for peptide-HLA binding and cancer synthetic lethality during his Ph.D. tenure at The Ohio State University. He combines rigorous statistical training with hands-on engineering—scaling algorithms for millions of single cells and productionizing sequence models for sequencing and synthesis workflows. Kunjie is fluent at bridging academic innovation and industry impact, routinely guiding experimental follow-up with active learning and reinforcement strategies. Based in Shanghai, he brings a rare mix of deep-methods research and product-focused delivery in computational biology.
8 years of coding experience
7 years of employment as a software developer
Ph.D. Biomedical Informatics, Ph.D. Biomedical Informatics at The Ohio State University
学士 Internet of Things, 学士 Internet of Things at Beijing Institute of Technology
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