Ming Du Email and Phone Number
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• Developed production-level image processing, deep learning, and optimization algorithms for semiconductor process control equipment. • Created large-scale x-ray 3D computational imaging algorithms on HPC platforms with MPI-based parallel computing.• Image reconstruction/restoration using both deep learning and model-based optimization methods.• Intensive experience in using automatic differentiation for inverse problem solving with PyTorch and TensorFlow.• Leadership experience as project PI for an ALCC large-scale computing grant.• Knowledge in cloud computing for ML proven by the AWS Certified Machine Learning – Specialty certification. • Please also visit my personal GitHub page: https://mdw771.github.io/ and ResearchGate page: https://www.researchgate.net/profile/Ming_Du6
Argonne National Laboratory
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Assistant Computational ScientistArgonne National Laboratory Oct 2023 - PresentLemont, Il, UsLeveraging AI, Bayesian statistics, and large-scale computing, I develop algorithms for data analysis and autonomous experimentation in the domain of X-ray science. My past and ongoing works include:- Using single-shot phase retrieval networks and image registration techniques to predict ptychographic scan positions without any initial guess;- Developing HPC-compatible training frameworks and deploying them on ALCF Polaris with >100 GPUs;- Developing transformer-based neural networks for crystallography structure prediction and training them on over 15 million samples;- Developing adaptive sampling and smart scanning approaches for x-ray imaging and spectroscopy using AI and Bayesian optimization.
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Senior Algorithm EngineerKla Mar 2023 - Sep 2023Milpitas, California, Us -
Algorithm EngineerKla Apr 2021 - Mar 2023Milpitas, California, Us• Developed image processing algorithms for modeling the image formation process in KLA’s high-precision photomask inspection systems used for sub-3-nm processes. Implemented algorithm solutions in the C++ codebase.• Led the development and productization a deep learning algorithm for defect detection, achieving 60% reduction of false positives. Optimized inference throughput using techniques and tools including OpenVINO. • Using computer vision and numerical optimization techniques, developed image correction and artifact removal algorithms that reduced the false positive rate of the photomask inspection system by over 70%. • Directed an internship project on modeling the artifacts generated in the image formation process using deep learning.
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Postdoctoral ScholarArgonne National Laboratory Aug 2019 - Apr 2021Lemont, Il, Us• Developed Adorym, a reconstruction framework capable of performing large-scale 2D/3D phase retrieval, image reconstruction, and parameter refinement for multiple x-ray imaging techniques, built on automatic differentiation of PyTorch. • Developed a generative neural network-based method using “deep image prior” to reconstruct clean images from artifact-corrupted images in x-ray multislice ptychography. • Developed a distributed algorithm for large 2D wavefield propagation on high performance computers (HPCs). • Led the proposal and research of an ASCR Leadership Computing Challenge (ALCC) project, which is a highly selective HPC resource award, on large-scale 3D reconstruction.
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Phd CandidateNorthwestern University Sep 2015 - Jun 2019Evanston, Il, Us• Developed Tomosaic, a Python software package for beyond-field-of-view x-ray micro-CT. Achieved 3D reconstruction of a whole mouse brain with 10^13 voxels from 5.8 TB of raw data, using supercomputers at Ar-gonne Leadership Computing Facility. • Developed an innovative algorithm for 3D phase retrieval under complicated imaging scenarios, utilizing the automatic differentiation capability of deep learning tools.• Conducted x-ray tomography and ptychography experiments at the Advanced Photon Source.• Involved in the commissioning of an automated tomography processing pipeline Automo/Ripple at beamline 32-ID of the Advanced Photon Source. • Built an improved theoretical model for dose estimation in the x-ray imaging of thick hydrated specimens. -
Research InternSingapore Institute Of Manufacturing Technology Jan 2014 - Jun 2014Singapore, Sg• Experimentally studied the pore size dependence of anodic aluminum oxide on voltage and electrolyte temperature.• Developed a tool for unsupervised data analysis.
Ming Du Skills
Ming Du Education Details
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Northwestern UniversityMaterials Science -
National University Of SingaporeMaterials Science And Engineering
Frequently Asked Questions about Ming Du
What company does Ming Du work for?
Ming Du works for Argonne National Laboratory
What is Ming Du's role at the current company?
Ming Du's current role is Assistant computational scientist at Argonne National Laboratory | analytical and AI methods for computational imaging.
What is Ming Du's email address?
Ming Du's email address is md****@****anl.gov
What schools did Ming Du attend?
Ming Du attended Northwestern University, National University Of Singapore.
What are some of Ming Du's interests?
Ming Du has interest in Politics, Science And Technology, Social Services.
What skills is Ming Du known for?
Ming Du has skills like Materials Science, Scanning Electron Microscopy, Characterization, Matlab, Nanotechnology, Physics, Digital Image Processing, Python.
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