natmourajr/CPE883-2025-02
Sep 2025 – Sep 2025
1 Month active
Languages Used
Python
Technical Skills
Cross-ValidationData PreprocessingDeep LearningImbalanced-learnMachine LearningModel Development
Luiza Helena
PROFILE
Luiza Helena
Developed a scalable experimentation stack for Room Occupancy Estimation, delivering prototype models and end-to-end pipelines within the natmourajr/CPE883-2025-02 repository. Focused on building robust data preprocessing routines, training workflows, and cross-validation processes to support rapid benchmarking of deep learning architectures. Implemented and evaluated models including LSTM, MLP, DeepONet, and KANTransformer, expanding the modeling toolkit for occupancy estimation tasks. Leveraged Python, PyTorch, and Scikit-learn to ensure reproducibility and facilitate experimentation at scale. The work enabled faster iteration cycles and laid the groundwork for seamless integration with future production workflows, emphasizing maintainability and extensibility in model development practices.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
2,372
Activity Months1
Your Network
16 peopleSame Organization
@lps.ufrj.br2
gabrielhblisboaMember
Rodrigo Petrus DominguesMember
Work History
September 2025
1 Commits • 1 Features
Sep 1, 2025September 2025: Delivered a scalable Room Occupancy Estimation experimentation stack, including prototype models and end-to-end pipelines. Implemented data preprocessing, training routines, and cross-validation workflows to enable rapid benchmarking of multiple deep learning architectures and prepare for production-ready experimentation.
1 Commits • 1 Features
Sep 1, 2025September 2025: Delivered a scalable Room Occupancy Estimation experimentation stack, including prototype models and end-to-end pipelines. Implemented data preprocessing, training routines, and cross-validation workflows to enable rapid benchmarking of multiple deep learning architectures and prepare for production-ready experimentation.
September 2025
Activity
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Quality Metrics
Correctness90.0%
Maintainability80.0%
Architecture90.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Cross-ValidationData PreprocessingDeep LearningImbalanced-learnMachine LearningModel DevelopmentPyTorchScikit-learn
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