Rui Ma
Software Engineer at Ant Group
Pittsburgh, Pennsylvania, United States
Summary
🤩
Rockstar🎓
Top SchoolRui Ma is a software engineer with 11 years of experience, currently pursuing an MS in Electrical and Computer Engineering at Carnegie Mellon and working at Ant Group in Pittsburgh. He specializes in backend systems and has shipped resilient, high-throughput trade and order services—improving order send success rates from 99.999% to 99.9999% through middleware, dual message queues, and scheduled recovery tasks. His background in control technology and coursework in data structures, systems, and web app design inform a methodical approach to robustness and data correctness. Rui also contributes to open-source ML tooling by fixing critical training pipeline issues in the widely-cited PointCNN repository, demonstrating attention to reproducible experimentation and operational details.
11 years of coding experience
Bachelor of Science - BS, Automation Engineer Technology/Technician, 3.52/4.0, Bachelor of Science - BS, Automation Engineer Technology/Technician, 3.52/4.0 at Harbin Institute of TechnologyMaster of Science - MS, Electrical and Computer Engineer, 3.56/4.0, Master of Science - MS, Electrical and Computer Engineer, 3.56/4.0 at Carnegie Mellon University
Github Skills (8)
sh10
script10
shell10
scripting10
python9
tensorflow9
machine-learning9
computer-vision8
Programming languages (8)
Github contributions (5)
yangyanli/PointCNN
Jan 2018 - Dec 2019
PointCNN: Convolution On X-Transformed Points (NeurIPS 2018)
Role in this project:
Back-end Developer
Back-end DeveloperContributions:66 commits, 6 PRs, 59 pushes in 1 year 11 months
Contributions summary:Rui primarily addressed path-related bugs within the shell scripts of the repository, specifically in the context of training and validation procedures for the PointCNN models. They corrected file paths within the training scripts for different datasets, which is essential for proper data loading and model execution. The commits reflect a focus on ensuring the correct execution of training and evaluation pipelines by fixing file paths and ensuring correct data loading.
pytorchclassificationdeep-learningneuripsconvolution
burui11087/DeepLearning-500-questions
Jul 2020 - Dec 2020
深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为15个章节，近20万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系scutjy2015@163.com 版权所有，违权必究 Tan 2018.06
Contributions:2 commits, 4 PRs, 2 pushes in 4 months
deep-learningtancomputer-visionmachine-learningtensorflow
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