Ran Ding
Member Of Technical Staff at OpenAI
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolRan Ding is a seasoned AI and engineering leader with nine years of experience building production machine learning systems and scaling teams from startups to hyperscale tech companies. Currently a Member of Technical Staff at OpenAI working on multimodal ChatGPT, he previously led turnarounds and 0→1 efforts at Meta—building Threads relevance and rebooting Instagram Home Feed—after founding ML groups and infrastructure at Compass and contributing core research and product work at AWS AI/SageMaker. He holds a PhD in Electrical Engineering and has translated deep research on neural topic models and variational inference into deployed semantic search and ML algorithms. Ran blends deep mathematical rigor (evident in focused GitHub contributions refining probability and numerical-stability code for popular deep-learning resources) with hands-on product delivery and ops experience, including a hardware startup and chip commercialization. Known as a fixer who thrives on high-ambiguity problems, he moves fluidly between research, engineering management, and shipping customer-facing ML services. Based in San Francisco, he combines academic depth with a track record of driving measurable business impact across AI, search, and recommendation systems.
9 years of coding experience
13 years of employment as a software developer
Doctor of Philosophy - PhD Electrical Engineering, Doctor of Philosophy - PhD Electrical Engineering at University of WashingtonBachelor of Science - BS EE, Bachelor of Science - BS EE at Nanjing University
Github Skills (7)
jupyter-notebook10
machine-learning10
logistic-regression10
probability-theory10
python10
data-science10
naive-bayes9
Programming languages (10)
Github contributions (5)
zackchase/mxnet-the-straight-dope
Nov 2017 - Apr 2018
An interactive book on deep learning. Much easy, so MXNet. Wow. [Straight Dope is growing up] ---> Much of this content has been incorporated into the new Dive into Deep Learning Book available at https://d2l.ai/.
Role in this project:
Data Scientist
Data ScientistContributions:13 commits, 8 PRs, 3 comments in 4 months
Contributions summary:Ran's commits primarily focus on correcting and refining code related to probability concepts, distributions, and the derivation of binary cross-entropy, indicating a strong focus on the mathematical foundations of machine learning. They made code modifications in a Jupyter notebook format, particularly in areas related to Naive Bayes and logistic regression, showcasing expertise in supervised learning techniques. Furthermore, their edits show an understanding of the numerical stability considerations involved in deep learning model implementation.
deep-learningmxnet
dingran/angellist-webscrape
Oct 2016 - Aug 2017
Contributions:18 commits, 11 pushes, 1 branch in 9 months
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