Gustavo Daré
PANDA - Data Processing and Analysis Group
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Envie uma proposta de trabalho diretamente para este candidato
Sobre
Development of projects focused on data analysis and processing Data cleaning, manipulation, and exploratory data analysis using Python Application of statistical concepts and data visualization techniques
Experiência
PANDA - Data Processing and Analysis Group at UFSCar - Universidade Federal de São Carlos (2025-07 – Present)
- Development of projects focused on data analysis and processing
- Data cleaning, manipulation, and exploratory data analysis using Python
- Application of statistical concepts and data visualization techniques
- Collaborative teamwork in the development of analytical solutions
EDROM - Mobile Robotics Development Team at UFU - Universidade Federal de Uberlândia (2021-05 – 2022-11)
- Development of automation and computational logic programs
- Participation in virtual robotics automation competitions
- Team leadership in automation projects, task organization, and technical support
Explainability od AI Models through Fuzzy Rule-Based Systems, PIBIC (June, 2025 - Present)
- Study and application of Explanaible AI (XAI) techniques
- Adaptation and integration of the LIME library for fuzzy systems
- Implementation of fuzzy classification models in Python
- Development of inference functions and local interpretability mechanisms
- Comparative analysis between fuzzy models and classical Machine Learning models
- Experimental evaluation using real and synthetic datasets
- Assessment of variable impact on predictive decisions
Fuzzy-Based Modeling of Variables and Indicators for the Analysis of Sustainable
Development Goals (SDGs) in Disaster Risk Management, FAPESP (Feb, 2025 - May, 2025)
- Systematic literature review on fuzzy modeling and decision-support systems
- Definition and modeling of fuzzy sets and linguistic variables for indicator represetation
- Implementation of fuzzy rule-based systems in Python
- Evaluation of different membership funcion configurations
- Experimental validation of the proposed model
Formação
Bachelor's Degree in Computer Science – UFSCar - Universidade Federal de São Carlos (2023-03)
