Helen Gao
Data Scientist
United States
Summary
🤩
Rockstar🎓
Top SchoolTianyu Gao is a Member of Technical Staff at OpenAI with 11 years of software engineering experience and a PhD candidate in Computer Science at Princeton University. He blends deep research expertise with production engineering, having contributed core CNN-based architectures for neural relation extraction in notable open-source projects like OpenNRE. Based in the San Francisco Bay Area, Tianyu has a strong academic foundation from Tsinghua University and Princeton, enabling him to bridge theoretical ML advances and real-world systems. His work focuses on backend model implementations, training pipelines, and embedding-rich architectures that power NLP tasks. Colleagues describe him as a developer who translates complex research ideas into robust, maintainable code that scales. Quietly, he often drives low-level model optimizations that materially improve training stability and throughput.
11 years of coding experience
2 years of employment as a software developer
Bachelor of Science - BS Computer Science, Bachelor of Science - BS Computer Science at Princeton University
Github Skills (9)
neural-network10
mask-rcnn10
faster-rcnn10
pytorch10
machine-learning10
word-embeddings10
nlp10
relation-extraction10
python10
Programming languages (6)
Github contributions (5)
thunlp/OpenNRE
Jul 2018 - Dec 2021
An Open-Source Package for Neural Relation Extraction (NRE)
Role in this project:
Back-end Developer
Back-end DeveloperContributions:211 commits, 13 PRs, 146 pushes in 3 years 5 months
Contributions summary:Helen's commits primarily revolve around implementing and modifying the `CNNSentenceEncoder` and `CNNSoftmax` models within the `nrekit` package. These changes involve defining the architecture, including word embeddings, position embeddings, and convolutional layers. The user appears to be working on the core functionality of a neural relation extraction (NRE) model based on convolutional neural networks (CNNs), including the training process.
extractionrelation-extractionnreinformation-retrievalrelation
princeton-nlp/LM-BFF
Dec 2020 - Aug 2022
ACL'2021: LM-BFF: Better Few-shot Fine-tuning of Language Models https://arxiv.org/abs/2012.15723
Contributions:19 commits, 3 PRs, 16 pushes in 1 year 8 months
nlplanguage-modelarxivabsfine
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