Mo Chen
Principal Research Scientist at SenseTime Group Limited
Hong Kong, China
Summary
🤩
Rockstar🎓
Top SchoolMo Chen is a Principal Research Scientist with 13 years of experience specializing in deep learning and Bayesian inference, currently driving research at SenseTime in Hong Kong. He holds a PhD in Information Engineering and blends rigorous statistical modeling with practical applications across computer vision and social network analysis. Mo is the lead contributor to PRMLT, a widely used Matlab toolbox for Bishop's Pattern Recognition and Machine Learning that ranks among the top Matlab projects on GitHub, reflecting his commitment to reproducible, educational open-source code. His background spans industry research at Microsoft, quant work at Sentient and Deutsche Bank, and a strong academic foundation from Tsinghua and Beihang, enabling him to bridge theory, finance-grade modeling, and production ML systems. Notably, his contributions include fixing numerical precision issues and extending functionality for regression and information-theoretic methods, underscoring a practical attention to algorithmic robustness.
13 years of coding experience
1 year of employment as a software developer
Bachelor’s Degree Finance, Bachelor’s Degree Finance at Beihang UniversityMaster’s Degree Computer Science, Master’s Degree Computer Science at Tsinghua UniversityThe Chinese University of Hong Kong (CUHK)
English, Chinese
Stackoverflow
11reputation
132reached
0answers
1question
Github Skills (6)
algorithms10
machine-learning10
machine-learning-algorithms10
matlab10
regression9
lapack6
Programming languages (9)
Github contributions (5)
PRML/PRMLT
Sep 2012 - Mar 2020
Matlab code of machine learning algorithms in book PRML
Role in this project:
ML Engineer
ML EngineerContributions:22 releases, 505 commits, 34 PRs in 7 years 7 months
Contributions summary:Mo primarily contributed to the implementation of machine-learning algorithms within the provided Matlab code base. Their work focused on implementing algorithms and fixing potential numerical precision issues in existing functions for areas such as information theory. The contributions included adding new functionalities and refactoring existing ones for regression tasks.
matlabmachine-learning-algorithmsmachine-learninglearning-algorithmsoctave
sth4nth/MixtureModel
Jan 2016 - Nov 2016
Contributions:12 commits, 8 pushes, 1 branch in 9 months
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