About me #
Researcher at SENAI Institute of Innovation /
Data Scientist
M.Sc in Electrical Engineering
Hey, this is Rodrigo! I’m an AI Researcher at the SENAI Institute of Innovation in Embedded Systems and an Electronic Engineer with a keen interest in the application of machine learning models in the industry. . I hold a master’s degree in Electrical Engineering from UFSC, where I conducted studies on machine learning applied to industry in collaboration with a company. My main professional goal is to enhance industrial efficiency through data-driven solutions.
Over the past five years, I have been improving my skills in Python programming and machine learning techniques. At the same time, I have also been developing expertise in innovation project management through technical leadership in projects at the SENAI Institute of Innovation. My expertise lies in developing innovative algorithms and implementing machine learning models in real-world applications. I thrive on the challenge of solving complex problems by leveraging state-of-the-art technologies to drive advancements in the industry.
Experience #
March/2024 - Present #
Machine Learning Researcher
- Leadership as a Technical Lead in industry innovation projects;
- Development of technical project reports and scientific articles for publication;
- Designed PoCs for querying internal processes using AI Agents with LLMs;
- Created extraction, transformation, and loading (ETL) pipelines and ML model orchestration pipelines;
- Experiment tracking, model monitoring, and AutoML with MLOps tools.
November/2021 - February/2024 #
Machine Learning Researcher
- Applied machine learning algorithms for predictive maintenance using real vibration data;
- Worked with state-of-the-art convolutional network models and a public bearing fault dataset;
- Conducted exploratory data analysis and data cleaning;
- Performed extraction, transformation, and loading (ETL) pipelines;
- Implemented machine learning models and optimized hyperparameters;
- Tracked experiments using MLOps tools.
February/2021 - October/2021 #
Machine Learning Engineer
- Developed and deployed a failure forecasting and classification model for HVAC-R monitoring systems;
- Trained machine learning models for demand and price forecasting for the automotive sector;
- Built data pipelines and machine learning model pipelines using Airflow;
- Monitoring of deployed models' performance;
- Data wrangling and exploration.
February/2020 - February/2021 #
Machine Learning Engineer Intern
- Developed and evaluated several ML models for stress corrosion cracking failures in the gas industry;
- Developed and deployed an anomaly detection model for HVAC-R monitoring systems;
- Performed data wrangling and exploration and helped with the model data ingestion by creating ETL pipelines.
Papers #
Benchmarking deep learning models for bearing fault diagnosis using the CWRU dataset: A multi-label approach
Rodrigo Kobashikawa Rosa, Danilo Braga, Danilo Silva
Arxiv pre-print
[link]Diagnóstico de Falhas em Rolamentos usando Redes Convolucionais: Otimização da Representação de Sinais e uma Nova Metodologia de Avaliação
Rodrigo Kobashikawa Rosa, Vicente Knobel Borges, Danilo de Souza Braga, Danilo Silva
XLI Simpósio Brasileiro de Telecomunicações e Processamento de Sinais-SBrT 2023
[link]Bearing fault diagnosis using machine learning and a novel set of fault-related spectral features
João Paulo Vieira, Rodrigo Kobashikawa Rosa, Victor Afonso Bauler, Danilo Braga, Danilo Silva
XXI Encontro Nacional de Inteligência Artificial e Computacional
[link]Fault detection for rotating machinery based on vibration data using machine learning
Lucas de Toledo Barreto, Rodrigo Kobashikawa Rosa, Danilo Silva, Danilo Braga
[link]Conversão Texto-Fala para o Português Brasileiro Utilizando Tacotron 2 com Vocoder Griffin-Lim
Rodrigo Kobashikawa Rosa, Danilo Silva
XXXIX Simpósio Brasileiro de Telecomunicações e Processamento de Sinais-SBrT 2021
[link]
Contact #
You can reach me at rodrigokrosa@gmail.com