Lei Ma
Engineer at Dejavu Info Tech Ltd.
Earth, Texas, Singapore
Summary
👤
Senior🎓
Top SchoolLei Ma is an engineer with 11 years of experience building data-driven systems, from payment platforms and big-data credit risk pipelines to blockchain and smart contract projects. He has led engineering teams across Asia, driving lending risk modeling that supported over ¥1B monthly transactions and heading Ethereum data analysis and consortium blockchain efforts. A contributor to the widely used SMILE machine learning library (and a 2020 GitHub Arctic Code Vault contributor), he combines hands-on model implementation and unit testing with production-grade system design. His background spans R&D, enterprise replication systems at SAP, and academic research at NYU focused on high-speed networking algorithms. Comfortable in Java, C, NodeJS and ML toolchains, he excels at translating complex statistical models into scalable services. Based in Texas with ties to Singapore, he brings a pragmatic blend of research rigor and product-focused engineering leadership.
11 years of coding experience
8 years of employment as a software developer
Master, Electrical and Computer Engineering, Master, Electrical and Computer Engineering at New York UniversityBachelor, Automation, Information School, Bachelor, Automation, Information School at East China University of Science and Technology
Github Skills (10)
machine-learning10
naive-bayes10
classification10
data-science9
statistics9
javas8
testing8
java8
visualizations7
visualization7
Programming languages (16)
Github contributions (5)
haifengl/smile
May 2018 - Jan 2022
Statistical Machine Intelligence & Learning Engine
Role in this project:
Data Scientist
Data ScientistContributions:1 review, 32 commits, 32 PRs in 3 years 8 months
Contributions summary:Lei primarily contributed to the `smile` repository by adding and refining machine learning models and demo applications. The initial commit involved creating a demo for Naive Bayes with the Iris dataset, including code for data loading, model training, and visualization. Subsequent commits included the addition of the Polya Urn model for Naive Bayes and related unit tests, demonstrating model implementation and validation skills. Further commits also fixed typos and refined the code format, with an emphasis on improving the accuracy of existing models.
orangepythonndarraymathematicamultidimensional-scaling
rayeaster/smile
May 2018 - Jan 2022
Statistical Machine Intelligence & Learning Engine
Contributions:77 pushes, 22 branches in 3 years 9 months
statisticspythonknn-classificationlogistic-regressiondata-science
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