François B.

I am a DSP and AI engineer specialized in developing intelligent algorithms for real-world sensing systems, with a strong focus on signal processing, machine learning and embedded AI.

My work sits at the intersection of signal processing, detection algorithms and production machine learning systems. I particularly enjoy solving complex technical problems involving noisy sensor data, real-time constraints and hardware limitations.

I have experience developing end-to-end AI solutions, from algorithm design and model training to deployment on embedded systems and production environments.

My main areas of expertise include:

• Real-time detection, tracking and classification algorithms

• Radar and LiDAR signal processing

• Medical image processing on CT, MRI and PET modalities

• Feature engineering and statistical learning for medical imaging and sensor data

• Edge AI and TinyML deployment on constrained hardware

• Machine learning pipelines and MLOps

• Software development

Throughout my experience, I have worked on:

• AI models for sensor-based people and vehicle detection

• Multi-object tracking and classification systems

• Medical imaging models for diagnosis and outcome prediction

• Deployment of neural networks on microcontrollers

• Data and ML infrastructure for reproducible AI development

My technical stack includes:

• Programming languages: Python | C | Matlab

• Machine learning: Tensorflow | LiteRT | MLflow

• Software development: Azure DevOps | Git | Docker

I am particularly interested in projects involving innovation, real-world impact and technically challenging environments, especially in domains such as intelligent sensing systems, medical technologies and advanced AI applications.

Driven by curiosity and a strong engineering mindset, I enjoy collaborating with multidisciplinary teams and turning complex ideas into robust and deployable solutions.