MLflow

Sound of Vision: audio-haptic navigation for the visually impaired

Software Developer & DevOps Engineer, PhD candidate, ACS-UPB

Real-time detection of obstacles, text, pedestrians and stairs rendered as spatial audio and wireless haptic feedback, running on a GPU-accelerated NVIDIA Jetson edge cluster orchestrated with Kubernetes and MLOps.

• Detection algorithms for obstacles, text, pedestrians, sidewalks and elements of interest (stairs, doors, potholes) using deep-learning computer vision.
• Spatial-audio rendering optimised so users can classify objects and navigate a scene by sound.
• Designed the fully wireless haptic belt: wireless charging and ESP-NOW communication via an ESP32-C3, and the algorithms controlling haptic parameters.

KubernetesKubeflowTriton Inference ServerCUDAArgo CD+30

Apr 2024 - Present