Franco Caspe

Franco Caspe is a PhD researcher at Queen Mary University of London's School of Electronic Engineering and Computer Science, focusing on AI-assisted sound synthesis and embedded systems. His work bridges music technology, machine learning, and hardware design, with a particular emphasis on real-time audio generation and neural synthesizer development.

• Affiliations: Queen Mary University of London (PhD candidate), AIM CDT, C4DM Sound Synthesis and Augmented Instruments Research Theme

Education: M.Sc. in Image Processing and Computer Vision (Erasmus Mundus), Electronic Engineering diploma (Argentina), with research internships in India (RF Metamaterials) and Italy (Tonewheel Organ Synthesizer development).

Research Interests: Neural synthesis, instrument augmentation, sound matching, FM synthesis, FPGA-based neural networks, and embedded AI systems. His projects include real-time DNN serving frameworks, low-latency audio synthesis, and hardware-accelerated neural network implementations on embedded platforms like the Zybo-Z7 FPGA board.

Publications span topics in music technology, signal processing, and embedded systems, with a focus on interdisciplinary approaches combining data science and engineering. He has contributed to open-source projects like BNN-PYNQ for FPGA-accelerated neural networks, demonstrating expertise in hardware-software co-design.