K K is a tech cofounder and Ph.D. in Informatics with 11 years of experience building production-ready machine learning and backend systems from research prototypes to startup products in the San Francisco Bay Area. He brings deep C/C++ expertise and a strong open-source pedigree, having improved the R bindings and multi-GPU support for the high-profile Apache MXNet project. Prior roles include senior engineering at H2O.ai and applied research and internships at AWS and other ML platforms, blending algorithm design, GPU-enabled deep learning, and R package development. Equally at home in research and product engineering, he has a track record of shipping robust tools for mass spectrometry, distributed deep learning, and scalable data interfaces. Notably, his background spans statistics and biotechnology, giving him a rare combination of domain insight and systems-level engineering.
Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more
Role in this project:
Back-end Developer
Contributions:1 review, 46 commits, 182 PRs in 6 months
Contributions summary:Qiang primarily focused on improving the R package within the MXNet repository. Their contributions include fixing message errors, updating image classification examples, addressing issues related to RNN models, implementing a captcha example, and ensuring compatibility with R 3.2.0 and later versions. They also worked on fixing predict functions, updating optimizers for multi-GPU support, adding image segmentation examples, and integrating new features.
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