Ming Du is an Assistant Computational Scientist with nine years of experience building scalable AI, optimization, and HPC systems for real-world X-ray imaging and autonomous experimentation. Based at Argonne National Laboratory, he combines deep learning, Bayesian methods, and large-scale computing to deliver production-grade tools—from GPU-accelerated ptychography reconstruction libraries (Pty-Chi) to MPI/PyTorch DDP training on >100 GPUs and 30M-sample crystallography models. His background spans industry-grade defect-detection and image-formation algorithms at KLA to pioneering 10^13-voxel tomographic reconstructions and distributed wavefield propagation during his PhD and postdoc. Notably, he bridges research and production by deploying on-prem MLOps/DevOps and leading selective HPC proposals, reflecting a rare blend of experimental beamline experience and systems engineering.
9 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy - PhD Materials Science, Doctor of Philosophy - PhD Materials Science at Northwestern University
Bachelor of Engineering Materials Science and Engineering, Bachelor of Engineering Materials Science and Engineering at National University of Singapore
Contributions:360 pushes, 13 branches in 1 year 5 months
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