Haoyu Chen
Research Assistant at UC Berkeley
Berkeley, California, United States
Summary
🤩
Rockstar🎓
Top SchoolHaoyu Chen is a research-focused software engineer and data scientist with 11 years of experience building GPU-accelerated machine learning systems and probabilistic models. Based in Berkeley, he holds MS degrees in EECS and Statistics and a PhD in Civil Engineering from UC Berkeley, blending rigorous statistical training with practical systems engineering. At UC Berkeley he worked on auto-tuning GPU convolutional neural networks and implemented Gibbs sampling and Bayesian network learners in the BIDMach library, contributing to a notable CPU/GPU ML project. He interned on backend systems for Android Location at Google, bringing production-oriented engineering experience to research code. Haoyu is seeking a full-time role where he can bridge data science and software engineering to deploy efficient, scalable ML solutions. A less obvious strength is his interdisciplinary background spanning economics, civil engineering and statistics, which helps him frame technical problems in broader socio-technical contexts.
11 years of coding experience
Master’s Degree, Computer Science, 3.821, Master’s Degree, Computer Science, 3.821 at University of California, BerkeleyBachelor’s Degree, Economics, 92.3, Bachelor’s Degree, Economics, 92.3 at Tsinghua University
Github Skills (4)
bayesian-network10
machine-learning10
scala9
gpu-acceleration8
Programming languages (2)
Github contributions (5)
BIDData/BIDMach
Apr 2015 - May 2016
CPU and GPU-accelerated Machine Learning Library
Role in this project:
ML Engineer
ML EngineerContributions:53 commits, 46 pushes, 6 branches in 1 year
Contributions summary:Haoyu primarily contributed to the `BayesNetMooc3` class within the `bidmach/bidmach` repository, a machine learning library. Their work involved converting and adapting code, specifically `BayesNetMooc2`, into the learner framework. They focused on implementing and initializing the Bayesian Network model, including Gibbs sampling functionality and updating conditional probability tables.
cudacpudeep-learninggpuaccelerated
WillCh/WillCh.github.io
Jan 2015 - Jul 2017
Contributions:4 pushes, 1 branch in 2 years 5 months
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