Huijuan Wang
PhD Candidate
Los Angeles, California, United States
Summary
🤩
Rockstar🎓
Top School
Top expert inAdvanced Chinese Natural Language Processing and Machine Learning Technologies
Huijuan Wang is a PhD candidate in Computer Science at USC with nine years of industry and research experience bridging machine learning, NLP, and graph learning systems. Previously an algorithm engineer at Baidu, she has contributed substantial back-end and ML engineering work to major open-source projects like PaddlePaddle’s PGL and PaddleNLP, improving knowledge-graph link prediction pipelines and adding Chinese biomedical datasets and sequence-classification examples. Her hands-on contributions span core score-function fixes, dataset/dataloader development for the large-scale WikiKG90M corpus, and fine-tuning workflows for domain-specific models such as ernie-health-chinese. Based in Los Angeles, she combines production-focused engineering with academic rigor, bringing practical optimizations that boost both model accuracy and data throughput.
9 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of Southern CaliforniaMaster's degree, Computer Science, Master's degree, Computer Science at 中山大学Bachelor's degree, Computer Science, Bachelor's degree, Computer Science at Sun Yat-sen University
Github Skills (18)
python10
data-science10
graph10
machine-learning10
text-classification10
data-preprocessing10
graph-embedding10
knowledge-graph10
trainings10
data-processing10
paddlepaddle10
nlp10
modeling10
data-set9
datasets9
Programming languages (2)
Github contributions (5)
PaddlePaddle/PaddleNLP
Jan 2022 - Jan 2023
👑 Easy-to-use and powerful NLP and LLM library with 🤗 Awesome model zoo, supporting wide-range of NLP tasks from research to industrial applications, including 🗂Text Classification, 🔍 Neural Search, ❓ Question Answering, ℹ️ Information Extraction, 📄 Document Intelligence, 💌 Sentiment Analysis etc.
Role in this project:
Data Scientist & ML Engineer
Data Scientist & ML EngineerContributions:1 release, 247 reviews, 123 commits in 11 months
Contributions summary:Huijuan's contributions focused on adding and modifying datasets related to the Chinese Biomedical Language Understanding Evaluation (CBLUE) benchmark. They added datasets for sequence classification tasks, including defining new datasets, adding parameter settings, and fixing associated problems within training scripts and model definitions. The user implemented a sequence classification example leveraging the "ernie-health-chinese" model, indicating involvement in fine-tuning or training models for text classification within the medical domain.
extractionsemantic-similaritybertnlp-tasksfinetuning
PaddlePaddle/PGL
Sep 2021 - Jun 2022
Paddle Graph Learning (PGL) is an efficient and flexible graph learning framework based on PaddlePaddle
Role in this project:Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:42 reviews, 72 commits, 9 PRs in 9 months
Contributions summary:Huijuan primarily focused on modifying and optimizing core components of the knowledge graph learning framework. Their work included fixing bugs in the score function and improving data processing pipelines, specifically within the context of the WikiKG90M dataset. These changes suggest an effort to enhance the performance and accuracy of link prediction models. Additionally, the user contributed to the development of dataset and dataloader functionalities, critical for model training and evaluation.
graph-learningpaddlepaddleheterogeneous-graph-learninggraph-neural-networkgraph-neural-networks
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