Summary
Steve Niu is an AI data scientist with nine years of experience applying machine learning and statistical methods to challenging biomedical problems, currently building AI systems at Genentech in New York. He holds a Tri-Institutional PhD in Computational Biology & Medicine from Cornell and a strong track record in multimodal integration—developing unsupervised graph learning, network fusion, and optimal-transport approaches to link single-cell transcriptomics, proteomics, and imaging. His work spans production-quality pipelines (Dockerized CT/MRI DICOM processing, cloud apps) and deep learning for image segmentation, including a top-ranked fovea prediction model, plus large-scale NLP and NER systems built on billions of tweets. Active in the computational biology community, he served on the ICML workshop program committee and blends rigorous statistical thinking with practical engineering to push translational impact.
9 years of coding experience
9 years of employment as a software developer
Bachelor’s Degree, Cell Biology, Applied Physics, Bachelor’s Degree, Cell Biology, Applied Physics at University of California, Davis
Master of Science - MS, Bioinformatics, 3.9/4.0, Master of Science - MS, Bioinformatics, 3.9/4.0 at New York University
Doctor of Philosophy - PhD, Computational Biology and Medicine, Bioinformatics, Machine Learning, 3.9/4.0, Doctor of Philosophy - PhD, Computational Biology and Medicine, Bioinformatics, Machine Learning, 3.9/4.0 at Cornell University
English, Chinese