Physiological Signal Modeling with Deep Learning
Heart Rate Variability interpreted via deep learning, spanning peer-reviewed research and patented methods. Focused on extracting clinically meaningful structure from noisy physiological data.
Davide Morelli
I design systems that think, and music that listens.
Work
AI & software development consultant. Fractional CTO / Head of AI for startups and scale-ups, with focus on technology and healthcare.
Capabilities
- Designing AI systems that survive production and scrutiny.
- Translating research into deployable products with clear operational constraints.
- Providing technical leadership where product, engineering, and regulation intersect.
- Aligning founders, engineers, and investors around what is feasible now.
Academic Research Directions
Probabilistic Deep Learning
Uncertainty-aware modeling and inference in deep systems, with emphasis on robustness, interpretability, and decision-critical applications.
Large Language Models
Research on LLMs as computational systems, including Herbert, with focus on behavior, structure, and applicability beyond prompt-level usage.
Affiliations
- PhD in Computer Science — University of Pisa
- DPhil in Biomedical Engineering — University of Oxford
- Ongoing academic affiliation — University of Oxford