Juliano Da Silva is a Computer Vision Engineer with 10 years of experience delivering end-to-end AI solutions for smart retail and agricultural monitoring, from embedded ESP32/Jetson Nano devices to cloud-deployed models. He specializes in object detection and classification using YOLO, PyTorch and TensorFlow, and builds scalable, low-latency APIs and MLOps pipelines with FastAPI, Docker, DVC, SageMaker and MLflow. His work has transformed traditional retail operations into autonomous self-service systems and automated inventory and payment flows, while also creating solar panel analysis and crop monitoring platforms. Juliano blends hands-on embedded systems integration with clean backend architecture and production observability, ensuring models are versioned, traceable and monitored. He holds an MSc in Computer Science focused on intelligent systems and has a track record of improving model performance through research-driven methods like stacking CNNs. Colleagues describe him as a pragmatic engineer who pairs deep technical rigor with a strong focus on measurable business impact.
10 years of coding experience
4 years of employment as a software developer
Mestrado em Ciências da Computação Inteligência Computacional, Mestrado em Ciências da Computação Inteligência Computacional at Universidade Estadual de Maringá
The Oxford-IIIT-Pet dataset - Image classification using CNN
Contributions:5 commits, 4 PRs, 13 pushes in 2 years 1 month
iiitpythondeep-learningdatasetoxford
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