Backend & AI Engineer focused on industrial systems, intelligent configurators, and applied artificial intelligence.
I work on the development of backend services, APIs, and AI-driven features for industrial systems. My experience combines software engineering, distributed systems, Internet of Things (IoT) and applied AI, including constraint programming and Large Language Models (LLMs). My background includes research and development in Electrical Engineering and Computer Science, with experience in transforming research prototypes into production-ready systems.
- Backend Development (Java, Spring, APIs, Microservices)
- Distributed Systems and System Integration
- Artificial Intelligence (LLMs, Constraint Programming, Machine Learning)
- Industrial Systems and IoT
- Languages: Java, Python, Go, C++
- Frameworks: Spring Framework
- Tools: Git, Docker
- Other: Cloud & IoT Systems
- IoT-based monitoring systems for industrial and agricultural environments
- AI-driven industrial optimization and recommendation systems
- Signal processing and data analysis applications
- Signal Processing and Data Analysis;
- Industrial Internet of Things (Hardware and Software);
- Artificial Intelligence utilizing Constraint Satisfaction Problems (CSP), Large Language Model, Machine Learning, and Deep Learning;
- Cloud Computing.
- Development of intelligent engineering systems;
- Constraint Solver Programming;
- Industrial applications, from tools to full-scale solutions;
- Energy consumption and transmission;
- Time series study and applications.
- Portuguese (Native)
- English (Advanced)
- German (Learning)
- At some point still learn Italian, Spanish and Chinese
-
[1] G. A. David, P. M. d. C. Monson, C. Soares, P. d. O. Conceição, P. R. de Aguiar and A. Simeone, IoT-Driven Deep Learning for Enhanced Industrial Production Forecasting, in IEEE Internet of Things Journal, doi: 10.1109/JIOT.2024.3447579. https://doi.org/10.1109/JIOT.2024.3447579.
-
[2] G. A. David, P. O. C. Junior, F. R. L. Dotto and B. R. D. Santos, New Signal Processing-Based Methodology for Optimal Feature Selection of Corona Discharges Measurement in HVDC Systems, in IEEE Transactions on Instrumentation and Measurement, vol. 72, pp. 1-9, 2023, Art no. 3511309. https://doi.org/10.1109/TIM.2023.3260879.
-
[3] David, G.A.; Junior, P.O.C.; Dotto, F.R.L.; Santos, B.R. A Feasibility Study of the Application of Signal Processing Techniques to Corona Discharge Characterization on HVDC Systems. Eng. Proc. 2021, 10, 28. https://doi.org/10.3390/ecsa-8-11318
-
[4] G. A. David, R. Guarnetti, G. De Oliveira, E. P. Godoy and P. De Oliveira Conceição, Gestão de Ativos Industriais de uma Linha de Transporte de Paletes usando IIoT, 2021 14th IEEE International Conference on Industry Applications (INDUSCON), São Paulo, Brazil, 2021, pp. 488-494, https://doi.org/10.1109/INDUSCON51756.2021.9529747.
-
[5] G. A. David, Detecção e caracterização da ocorrência de descargas corona em sistemas HVDC por meio de técnicas de processamento digital de sinais, 2023. [Online]. Available: https://repositorio.unesp.br/items/8908995e-c05e-4236-8909-5d2c08e52e01.