Interests

Topics of most interest

• Bioinformatics

• Artificial Intelligence

• Machine Learning

• Data Analysis

• Back-End Development

Experiences

My experiences and work (portfolio) I've done

Wine Quality

1. During a scientific initiation project at the Laboratory of Artificial Intelligence and Formal Methods (LIAMF), I did this project as preparation for larger projects involving deep learning.
2. I obtained a dataset from Kaggle that contains a .csv file with various chemical compositions determining the quality of wine.
3. Using Python, I trained a neural network on this dataset to determine the quality of any wine based on its chemical factors.
4. All of this can be found at this link to my GitHub repository.

Single-Cell Analysis of Zebrafish Cardiac Cells

1. This project was a collaboration between the Laboratory of Immunology and Experimental Fibrosis (LiFE) and the High Performance and Efficient Systems (HiPES) labs.
2. I was involved for a short time, only 5 months, as an assistant to another student who had been in the course longer. However, due to a teacher strike that lasted over two months, I had to leave the project.
3. During this time, I learned many interesting things about bioinformatics, such as RNA sequencing indexing and analysis, and performing data analysis using R.
4. I analyzed data at the single-cell level and used software tools like Salmon and Alevin to aid in the analyses.
5. Additionally, I utilized machine learning techniques like PCA and clustering to facilitate data visualization.

Transfer Learning

1. This project was part of a scientific initiation at the Laboratory of Artificial Intelligence and Formal Methods (LIAMF), focused on applying transfer learning techniques using a diverse dataset.
2. The goal was to leverage pre-trained models to enhance the performance of machine learning tasks on new, related datasets.
3. By utilizing transfer learning, we aimed to reduce the amount of data and computational power required for training while achieving high accuracy.
4. This approach also allowed us to explore the potential of transfer learning in various applications, including image classification and natural language processing.

Memory compression using ZRAM software

1. This project was conducted in the Computer Architecture course, focusing on using zRAM for memory compression in modern operating systems.
2. The project involved implementing and analyzing the performance of memory compression across various hardware configurations, including machines with 4GB and 16GB of RAM.
3. In addition to matrix multiplication tests, we used the NASA Parallel Benchmarks (BT) to evaluate the impact of memory compression under demanding computational loads.
4. Memory compression proved effective in optimizing resource management, especially in systems with limited RAM.
5. The full report (in Portuguese) can be found at this link.

Space Impact 303

1. This project was developed as the final assignment for the Programming 2 course, focusing on creating a game inspired by the classic Space Impact 303.
2. The primary objective was to implement object-oriented programming concepts using the C language and the Allegro library for 2D game development.
3. The project involved techniques such as event management, graphical interface creation, sprite manipulation, and collision detection.
4. The final result was a functional game that stood out for its interactive mechanics and intuitive design, and the source code can be accessed through this link.

Liamf's Website

1. I discussed with my advisor about redoing the laboratory website, and he accepted the idea since the current site was outdated as shown in the image.
2. This was my first front-end project; it was quite challenging, but I really enjoyed the experience.
3. I invited my friend Marquesini, a front-end developer, to help me with the project.
4. I received approval from the coordinator of the Biomedical Informatics course and the professor in charge of the laboratory website to access the lab's account and launch the new site.

Contact

How to find me?