There was proposed a data analysis project, methodology, and processes to detect early potential customer’s cancellations for an internet service provider. The results were used to implement new processes for customer attention and operations areas. The cancellations got reduced in a 30%.

The robot’s processing is based on a Cortex M5 microprocessor. The implementation of the logic and algorithms is in C. There was implemented a C2 server to command, control and receive remotely information from the autonomous vehicle. It was used in Python to mount the server code and the information is stored using a non-relational database architecture with MongoDB.

Institutional project as professor of the bachelor’s subject of ‘Assembly Language’. The goal was to develop an ‘easy to use’ interface to connect applications in assembly through a C wrapper to be implemented in a Linux environment with an architecture x86.

Implement a newer version for the administrative software tool. The project included a business analysis to focus the solution to the internal processes, the database schema design and the back-end and front-end implementation. It included the compatibility to use a RADIUS server to control the access and accounting for the customer’s internet services.

Certification project where there was implemented an arithmetic solver in C from a string expression and oriented to the secure use of memory. There was implemented a special feature to select the operands of the expression from a given result, selecting each of the data values using a genetic algorithm.

Library to generate at low level fixed waves in order to be applied for sonar algorithms. It was also coded the function to generate a WAV file from the data generated based on the Linux Kernel C standard library Libc.

Master’s degree project. There was developed an algorithm based on a statistical fashion to automatically detect musical chords in an audio file. It also was implemented a comparative of different artificial intelligence’s algorithms (neural networks, KNN, Support Vector Machines) to compare their performance against the proposed method.