K K
Tech Cofounder at NyquistAI
San Francisco Bay Area United States
Summary
🤩
Rockstar🎓
Top SchoolK 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.
11 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy - PhD Informatics, Doctor of Philosophy - PhD Informatics at Indiana University IndianapolisBachelor of Science (BS) Statistics, Bachelor of Science (BS) Statistics at Sun Yat-sen University
English, Chinese
Stackoverflow
522reputation
12kreached
23answers
0questions
Github Skills (14)
mxnet10
machine-learning10
deep-learning10
r10
apidoc9
api9
computer-vision8
image-processing8
testing7
rcpp6
venn-diagram6
lattice6
forloop6
dataframe6
Programming languages (10)
Github contributions (5)
apache/mxnet
Feb 2017 - Aug 2017
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
Back-end DeveloperContributions:1 review, 46 commits, 182 PRs in 6 months
Contributions summary:K 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.
pythonschedulerdataflowmutationdata-science
dmlc/drat
Oct 2015 - Jul 2017
Contributions:1 PR, 67 pushes, 13 comments in 1 year 8 months
r-packager-packagesrstats
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