CV
Academic and professional background in physics, scientific computing, and data science.
Contact Information
| Name | Ronaldo Givisiez Melo Rodrigues |
| Professional Title | Physicist (Ph.D.) - Postdoctoral Researcher |
| Website | https://github.com/RGivisiez |
Professional Summary
Ph.D. physicist with expertise in programming, statistical physics, and scientific computing. Skilled in automation, data analysis, and computational problem-solving.
Experience
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2024 - Campinas, Sao Paulo, Brazil
Postdoctoral Researcher
Institute of Computing, State University of Campinas (Unicamp)
Postdoctoral research position at the Institute of Computing.
- Seismic data analysis using supercomputers.
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2022 - 2023 Carangola, Minas Gerais, Brazil
Professor
State University of Minas Gerais (UEMG)
Full-time professor position.
- Taught Statistics, Physics, Mathematics, and Introduction to Programming.
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2022 - 2023 Sao Paulo, Brazil
Data Scientist
Blue AI
Full-time remote role focused on predictive modeling in healthcare applications.
- Developed predictive models for diabetes, chronic diseases, and hospitalizations, contributing to an approximately 30% improvement in diagnostic accuracy.
Education
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2017 - 2021 Belo Horizonte, Brazil
PhD in Statistical Physics
Federal University of Minas Gerais (UFMG)
Statistical Physics
- Researched phase transitions using moment-generating function zeros and Fisher zeros.
- Specialized in statistical physics, computational simulation, and scientific programming.
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2015 - 2017 Belo Horizonte, Brazil
MSc in Physics
Federal University of Minas Gerais (UFMG)
Physics
- Studied phase transitions in the Ising and planar rotor models using computational simulations.
- Applied and investigated EPD zeros as a method for identifying phase transitions in magnetic systems.
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2009 - 2014 Viçosa, Brazil
BSc in Physics
Federal University of Viçosa (UFV)
Physics
- Held an undergraduate research scholarship for four years.
- Worked on computational simulation projects involving magnetic materials and polymers with Monte Carlo and molecular dynamics methods.
Projects
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Blood Vessel Segmentation and Statistical Analysis
Interdisciplinary project in collaboration with a pharmacy research group at UFMG. The project focuses on developing a machine learning pipeline for blood vessel segmentation to improve precision, reproducibility, and analysis speed.
- Built to reduce manual effort in segmentation workflows.
- Aims to generate higher-quality data for downstream statistical analysis and publications.
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Additional GitHub Projects
Additional programming, data science, and scientific computing projects are available on GitHub.
Publications
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Pushing the Limits of EPD Zeros Method
Computer Physics Communications
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2021 Moment-generating function zeros in the study of phase transitions
Physical Review E
Certificates
- TensorFlow: Advanced Techniques - Coursera, DeepLearning.AI (2021)
- Build Basic Generative Adversarial Networks (GANs) - Coursera, DeepLearning.AI (2020)
- Build Better Generative Adversarial Networks (GANs) - Coursera, DeepLearning.AI (2020)
- HTML5 e CSS - Alura (2020)
- Structuring Machine Learning Projects - Coursera, DeepLearning.AI (2019)
- Git e GitHub: Controle e Compartilhe Seu Código - Alura (2019)
- Convolutional Neural Networks - Coursera, DeepLearning.AI (2019)
- Neural Networks and Deep Learning - Coursera, DeepLearning.AI (2019)
- Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization - Coursera, DeepLearning.AI (2019)
- Sequence Models - Coursera, DeepLearning.AI (2019)
Skills
Technical Skills: Fortran, Python, TensorFlow, Keras, PyTorch, Scikit-learn, Machine learning, Monte Carlo simulation, Git, HTML, CSS, Linux
Languages
Portuguese : Native
English : Intermediate