cv
Full academic CV is available as a PDF (button to the right) or webpage (provided below).
Basics
| Name | George Pu |
| Label | Applied Scientist |
| pu.george99@gmail.com | |
| Phone | 904-316-1566 |
| Url | https://georgerpu.github.io/ |
| Summary | Applied Scientist at Amazon building AI agents and ML systems at scale. Published researcher in deep learning and federated learning. 4+ years of experience spanning research, ML infrastructure, and software development. |
Work
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2025.07 - Present Applied Scientist
Amazon, Sustainability Science and Innovation
Created agents to scale sustainability science.
- Developed deep research agent that auto-generates bills of materials, extending actionable environmental impact analysis to 75% of Amazon's carbon footprint with a <30% MAPE.
- Led sustainability scientists to annotate hundreds of life cycle inventories/assessments, creating 2 new internal benchmarks.
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2024.10 - 2025.07 Machine Learning Engineer / Applied Scientist
Amazon, Customer Trust
Trained machine learning models to stop bad actors on the Amazon Store.
- Created time series classification models that helped reduce bad seller debt by an estimated $3 million.
- Trained LightGBM models to reduce investigator case load, saving an estimated $500,000 per year.
- Trained graph machine learning models on SageMaker.
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2021.07 - 2024.10 Software Developer/Engineer
Amazon, Customer Trust
Built software to stop bad actors on the Amazon Store.
- Automated bad actor investigation case creation, saving 2 hours of investigator time per week.
- Onboarded ML models to SageMaker, saving >184 hours annually of scientist effort retraining models and batch inferencing.
- Designed and implemented an offline graph query execution engine over hundreds of millions of nodes on Amazon Neptune that helped stop $500,000+ in fraudulent sales; work featured on the AWS Database Blog.
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2017.09 - 2021.05 Research Assistant
University of Florida
Conducted research in deep learning, federated learning, and mathematical biology.
- Collaborated with a PhD student and professor to fit multi-compartment epidemiological models to Leishmaniasis data.
- Published 5 papers at top venues (IROS, NeurIPS) with over 250+ citations.
Education
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2017.08 - 2021.05
Awards
- 2020
JP Morgan Best Hack for Disaster Relief
SwampHacks VI
- 2019
University Scholars Program
University of Florida
- 2018
Infinite Energy Best Hack
SwampHacks IV
Publications
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2021.12 Seeing Through Walls: Real-Time Digital Twin Modeling of Indoor Spaces
Winter Simulation Conference
George Pu, Paul Wei, Amanda Aribe, James Boultinghouse, Nhi Dinh, Fang Xu, Jing Du
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2020.12 Communication-Efficient Federated Learning via Dataset Distillation
NeurIPS Workshop on Scalability, Privacy, and Security in Federated Learning (SpicyFL)
Yanlin Zhou*, George Pu*, Xiyao Ma, Xiaolin Li, Dapeng Wu. *Equal contribution
-
2019.11 Adaptive Leader-Follower Formation Control and Obstacle Avoidance via Deep Reinforcement Learning
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Yanlin Zhou*, Fan Lu*, George Pu*, Xiyao Ma, Runhan Sun, Hsi-Yuan Chen, Xiaolin Li. *Equal contribution
Skills
| Languages | |
| Java | |
| JavaScript | |
| Python | |
| SQL | |
| TypeScript |
| Python Packages | |
| AutoGluon | |
| LangChain | |
| Matplotlib | |
| NumPy | |
| Pandas | |
| Polars | |
| PyTorch | |
| Scikit-learn | |
| TensorFlow |
| AI/ML | |
| Agents | |
| LLM Evaluation | |
| Deep Learning | |
| Graph Neural Networks | |
| Prompt Engineering | |
| RAG | |
| Tabular Machine Learning | |
| Time Series Classification |
| Cloud | |
| AWS | |
| Bedrock | |
| CloudWatch | |
| DynamoDB | |
| IAM | |
| Neptune | |
| S3 | |
| SageMaker | |
| Step Functions |
Languages
| English | |
| Native speaker |
| Chinese | |
| Elementary |
Interests
| Artificial Intelligence | |
| Deep Learning | |
| Machine Learning | |
| Reinforcement Learning | |
| AI Agents | |
| Large Language Models |
| Applications | |
| AI4Science | |
| Robotics |