AI Sport Tech Consultant
Andrea Zignoli
I help sport tech startups turn physiology and performance data into production-ready AI solutions that drive subscriptions, enhance UX, and deliver new features.
I bridge the gap between sports science research and deployed code: whiteboarding with exercise physiologists in the morning, shipping containerised APIs by evening.
Education
PhD Sports Science
M.Eng. Mechatronics
Editorial
Associate Editor
Sports Engineering (Springer)
Research
51 peer-reviewed papers
609 citations
Services
What I do
Four areas where I have shipped work for clients and published peer-reviewed research.
Training Prescription & Assessment
Adaptive algorithms that personalise training load based on individual athlete physiology, historical performance data, and real-time feedback signals.
Cardiopulmonary Exercise Testing
ML models for automated threshold detection and CPET interpretation, from ventilatory thresholds to VO₂ kinetics, deployed at scale.
Continuous Glucose Monitoring
Insights extraction from CGM data for metabolic optimisation in endurance athletes: identifying fuelling patterns, glycaemic responses, and actionable recommendations.
Pacing & Race Strategy
Simulation models for optimal pacing, incorporating aerodynamics, terrain, fatigue dynamics, and competitive constraints to maximise performance.
Approach
How I work
I combine first-principles modelling with machine learning. Depending on the problem, I write differential equations by hand, train neural networks, or blend both approaches.
I prototype fast, validate against real data, and iterate until the model delivers business value. Full-stack: from research and model development to Docker containers, Flask/FastAPI services, and production deployment.
Recent work: educational courses, performance models deployed as APIs, web apps connected to CMS via LLM pipelines.
- 01
Model
First-principles equations, machine learning, or a blend of both, chosen for the problem.
- 02
Validate
Tested against real athlete data and iterated until it delivers business value.
- 03
Deploy
Shipped as Docker containers and Flask/FastAPI services, ready for production.
Tech stack
Background
Who I am
Research & Education
M.Eng. Mechatronics + PhD Sports Science. I enrolled to study robotics and ended up studying the most wonderfully made machine: the human body.
Post-doctoral research at the University of Trento (sport performance modelling), Yokohama National University (rehabilitation robotics), and the University of Verona (exercise physiology).
I maintain active research collaborations and publish in peer-reviewed journals. Associate Editor at Sports Engineering (Springer) and peer reviewer for several top sports science journals.
I also teach: an open course on Technology and Innovation in Sports covers wearables, data analytics, and AI tools for coaches, athletes, and sport scientists.
Clients & Collaborations
AI-driven training platform
Modelling, feature design, backend development
Research & speaking
Published and on the record
Selected AI & data papers
All 51 papers →38
citations
- Expert‐level classification of ventilatory thresholds from cardiopulmonary exercising test data with recurrent neural networks
European Journal of Sport Science · 2019
30
citations
24
citations
Recent talks & podcasts
All talks →Contact
Work together?
Is there a project idea you want to discuss? Whether it's a research collaboration, a custom model, or a tool you'd like to build, I'm always happy to explore new ideas. Send me a message and let's talk.
andrea.zignoli@unitn.it