Jianxu Chen
Jianxu obtained his Ph.D. in Computer Science in 2017 from University of Notre Dame under the supervision of Prof. Danny Chen. His Ph.D. research focused on large scale biomedical image analysis using both classic and AI-based methods. Before joining ISAS, Jianxu was a senior scientist at the Allen Institute for Cell Science, leading the R&D and productionization of AI-based image analysis methods and tools for large scale high-resolution 3D/4D light microscopy image data of live cells.
Jianxu’s research interests lie in the synergy between deep learning and image analysis for effectively extracting meaningful information from large scale microscopy data. At Jianxu’s group, it is believed that innovative AI-based microscopy image analysis research will only happen when microscopists, biomedical experts, and deep learning researchers collaborate deeply. All his research is driven by real applications in important life science problems, covering a broad spectrum, e.g., training 3D segmentation models with “biological” annotations, partial annotations or key point annotations, deep learning based image super-resolution, cell tracking, 3D image registration, self-supervised learning and contrastive learning of latent space representation from large scale microscopy images, etc., with publications in NeurIPS, AAAI, MICCAI, ISBI, IEEE TMI and more. Novelty is never the mere objetive and outperforming state-of-the-art by 2% will never be thing to pursue. The ultimate goal is to solve fundamental computational problems to move biomedical research forward.
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