Domenico Stefani is an Assistant Professor and music-technology researcher with nine years of experience building real-time audio systems, spatial-audio VSTs and embedded deep-learning pipelines for music information retrieval. He combines modern C++ audio development (JUCE, VST3), low-latency optimization for embedded CPUs, and Python-based DL training to deploy models with sub-10ms inference on single-board computers. His work includes a 300% performance improvement of a 6DoF convolution plugin, headless Elk Audio OS plugins, and live experimental performances integrating Max/MSP and FluCoMa. Equally comfortable wire-to-algorithm, he prototypes sensor-driven musical interfaces (Arduino/Teensy) and converts models across frameworks (TensorFlow, PyTorch, ONNX, TFLite). Based in Trentino, Italy, he runs an audio tools studio (OnyxDSP) while leading applied research at the University of Trento, blending academic publication rigor with product-focused engineering.
9 years of coding experience
3 years of employment as a software developer
Doctor of Philosophy - PhD Informatica, Doctor of Philosophy - PhD Informatica at Università di Trento
Package used by student to complete the assignment of the course.
Contributions:22 PRs, 74 pushes, 22 branches in 8 months
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Domenico Stefani - Assistant Professor (Ricercatore RTDA)