Bernardo F.Machine Learning/AI Engineer
Skills
Machine Learning Engineer with a Ph.D. in Mechanical Engineering, holding over nine years of experience in development and innovation. Proven track record of authoring articles that address analytical problems through quantitative methods, including machine learning, stochastic techniques, and optimization, with findings presented at both national and international forums. Proficient in programming languages and tools such as Python, MatLab, C++, and machine learning frameworks including TensorFlow, Keras, PyTorch, and Scikit-learn. Possesses foundational knowledge in SQL and Power BI, and adept in agile methodologies such as Scrum and Kanban. Interests encompass areas such as Artificial Intelligence, Acoustics, Data Science, Time Series Analysis, and Structural Health Monitoring/Condition Monitoring.
SCIENTIFIC INITIATION SCHOLARSHIP
1/1/2012 - 12/31/2013
Specialized in the analysis of residual stresses using the X-ray diffraction and Barkhausen methods. Conducted comprehensive data analysis for heat treatments, hardness tests, and microstructural evaluations, ensuring detailed and precise results.Machine Learning Engineer
2/1/2022 - Present
Developed a variety of machine learning models for tasks including condition monitoring and fault diagnosis in automobiles, acoustic monitoring, anomaly detection in multivariate time series, sentiment analysis, and text clustering. Specialized in developing AI solutions embedded in low processing capacity devices, with a focus on environmental acoustic monitoring. Deployed machine learning models in production environments using Docker, REST API frameworks such as Flask and FastAPI, and IoT development platforms. Served as a consultant in Artificial Intelligence for R&D projects, engaging directly with clients to identify needs and design appropriate solutions. Led and conducted algorithm development within a team, leveraging GPU computing with CUDA, cloud computing platforms like Google Cloud Platform, AWS, and Oracle, and maintained collaborative workflows using Git for version control.PhD Research Student
3/1/2018 - 2/1/2022
Served as a project analyst in the Acoustics and Vibrations Laboratory (LAVI) at Coppe/UFRJ. Developed expertise in mathematical modeling, stochastic methods, optimization techniques, machine learning, and structural health analysis. Contributed to extensive project work for a major oil and gas company in Brazil, leveraging advanced analytical methods and technical proficiency to drive project success.Master's Research Student
3/1/2016 - 3/1/2018
Served as a scholarship holder at the Laboratory of Acoustics and Vibrations (LAVI) - Coppe/UFRJ. Developed expertise in mathematical modeling and programming with a focus on numerical simulation and inverse problems. Specialized in wave propagation analysis for structural health assessment of submerged composite materials.Intern
11/1/2014 - 4/30/2015
Designed a hypobaric chamber, leveraging advanced skills in mechanical design. Conducted extensive modeling and numerical simulations within the field of biomechanics, utilizing tools and frameworks pertinent to the discipline. Assisted in the preparation of technical manuals, comprehensive reports, and supporting documentation, ensuring clarity and precision in technical communication.Technological Innovation Scholar (PIBIT)
1/1/2014 - 12/31/2014
Contributed significantly to the technological innovation project within the Applied Theoretical Mechanics Laboratory (LMTA), focusing on numerical simulation in heat transfer involving physical adsorption phenomena. Enhanced programming expertise through dedicated advanced coursework and hands-on project work, leading to a deeper understanding of numerical simulation techniques and thermal transfer processes.
Mechanical Engineering at Fluminense Federal University
2010 - 2016Mechanical Engineering at Federal University of Rio de Janeiro
2018 - 2023
Introduction to Embedded Machine Learning at Coursera
2/1/2023Introduction to Probability and Data with R at Duke University | Coursera
2/1/2023Version Control with Git at Coursera
2/1/2023Machine Learning Engineering for Production (MLOps) at Coursera
1/1/2023Conference Presentation - SIMEA2022 at AEA - Associação Brasileira de Engenharia Automotiva
8/1/2022Deep Learning Specialization at Coursera
8/1/2022Machine Learning with Python at freeCodeCamp
12/1/2021Power BI Complete - from Basic to Advanced at Udemy
12/1/2021Research Paper Presentation - DEEP LEARNING FOR INTERFACIAL DAMAGE ESTIMATION IN AN INVERSE ULTRASOUND SCATTERING ANALYSIS at CILAMCE PANACM
11/1/2021
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