Applied AI · Computer Vision · Edge Systems
I'm Yahia Ghallale, an engineer focused on real-time perception, edge inference, and machine learning for autonomous and physical systems.
Where I've contributed
Applied engineering work across computer vision, embedded telemetry, and real-time systems.
Prospecto
Built and deployed real-time agricultural computer-vision systems for on-device perception and field-video analysis.
GIVI UniBS Motorsport
Developed embedded telemetry and backend systems for motorcycle test sessions.
Selected work
Systems built to investigate, measure, and solve practical machine-learning problems.
An interpretable anomaly-detection system that combines unsupervised ML scoring, rule-based findings, contribution analysis, and interactive PX4 telemetry exploration.
A full-stack intelligence system for live article ingestion, semantic retrieval, source ranking, and grounded answers with citations.
A reproducible computer-vision study comparing a custom CNN with established architectures across internal and external chest X-ray datasets.
Working principles
I work where machine learning meets real systems: cameras, sensors, autonomous platforms, and the software that makes their data useful. I care about measurable performance, clear evaluation, and engineering that survives outside a notebook.
Technical toolkit
Academic foundation
Sep 2023 — Oct 2026
University of Brescia
Coursework includes Machine Learning, Deep Learning, Statistics, Electronics, Software Engineering, and Data Structures and Algorithms.
Jul 2025
Universidade da Beira Interior
From Smart Sensors to Industrial Applications: sensor networks, Industrial IoT, FPGA, PLC, industrial standards, and real-time monitoring.
Start a conversation
Have a role or project where applied AI needs to work beyond the demo? Let's talk.
y.ghallale@studenti.unibs.it