Jianqiang Zhou is a machine learning engineer and physicist based in Paris with nine years of experience building and deploying computer vision and image-quality models for product and research teams. He holds a Ph.D.-level research background and has translated that into industry impact—training multi-task ResNet, ViT and Swin Transformer models, optimizing HDR/SDR mixed-bit-depth pipelines, and deploying reproducible ML stacks with DVC, MLflow and FastAPI. Jianqiang has led end-to-end projects from data annotation and algorithm design to production APIs, improving detection and segmentation systems and cutting false positives through tailored deep-learning solutions. His work blends strong quantitative rigor from optics and image/color science with pragmatic engineering: he is equally comfortable deriving algorithms in Python and running scalable experiments in production. A detail that sets him apart is his focus on real-world viewing conditions and dataset curation, not just model architecture, to boost perceptual performance.
9 years of coding experience
7 years of employment as a software developer
Ecole polytechnique
Master's degree, Engineering Physics/Applied Physics, Master's degree, Engineering Physics/Applied Physics at Ecole Normale superieure de Cachan
Bachelor's degree, optoelectronics, Bachelor's degree, optoelectronics at Harbin Institute of Technology
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Jianqiang Zhou - Machine Learning Engineer at DXOMARK