Cheng Hou is a construction and design professional turned machine learning engineer who blends nine years of hands-on structural engineering, design coordination, and construction management with graduate-level computer science training. Based in the San Francisco Bay Area, he has managed large K–12 and data center programs, developed project dashboards and cloud project databases, and recently applied software and AI to streamline real project workflows. His ML work includes fine-tuning LLMs, building RAG pipelines and KBQA systems for enterprise platforms, and contributing backend fixes and model conversion improvements to an open-source PyTorch pre-training framework. Comfortable translating between construction stakeholders and engineering teams, Cheng brings a rare hybrid of field-tested construction delivery and practical ML/engineering execution.
5 years of coding experience
9 years of employment as a software developer
Master's degree, Computer Science, Master's degree, Computer Science at Georgia Institute of Technology
Open Source Pre-training Model Framework in PyTorch & Pre-trained Model Zoo
Role in this project:
Back-end Developer
Contributions:132 commits, 23 PRs, 119 pushes in 1 year 11 months
Contributions summary:Cheng primarily contributed to the UER-py framework by addressing data processing bugs, updating and converting BERT and T5 models, and adding the classification target. They made changes to data loading, model conversion scripts, and the training process. Additionally, the user added support for various features related to model training, including support for classification tasks.
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