As a PhD student, my project is focused in Machine Learning applied to healthcare industry. I have two years experience with Data Science, based in different research projects. Some of my projects are published in scientific journals and conferences. My mindset was built upon 4 years of experience in Industry, as a field engineer, focused on maintenance, debugging and troubleshooting.
All my post-grad studies are devoted into develop Machine Learning-based solutions to approach different problems. My Engineering degree was mainly focused on building solid skills to work on field.
Project: An novel approach for processing ECG signals, to improve medical diagnoses in heart diseases.
This is a high-score graduate program at the Federal University of CearĂ¡, Brazil. More info.
I just started my PhD and going to finish by 2022.
Keywords: Biomedicine, Signal Processing, ECG, Machine Learning.
Project: Faults Detection and Classification of Short-curcuit faults in Wind Turbine Generators, using Machine Learning.
I've design a wind turbine test-bench and a DAQ system. The turbine was porperly design to insert incipient failures. A network of sensor's are installed in the setup and being acquired in real time to compose a reference database of Wind Turbine Generator Faults. This work is held from a solid research group in electrical machines in my institution and developed in partnership with two laboratories. I've finished this degree in 2018.
Keywords: Predictive Maintenance, Monitoring systems, Neural Networks
Project: Fault Prognosis in Aircraft Turbofan Engines.
This is a professional master's course, focused in aviation safety. We use a consolidade dataset provided by NASA, to develop an algorithm to estimate remaining useful life. More info.
During my period on scholl I have had experience in small, medium and big Industries, of different types.
I also worked as a field Engineering department in a world-wide elevators company and have experience in problem analysis and providing technical support.