Product Design / Data Science
Bridging physical product design and data-driven systems.
I am Loris Emanuelli, an MEng candidate at UC Berkeley. I build wearable systems, mechanisms, and analytics pipelines that turn engineering insight into measurable outcomes.
Focus
Sports, wearables, and applied analytics
From instrumented biomechanics to predictive pipelines, my work balances physical prototyping with data-driven decision support.
Note: FormaFlow was developed at UC Berkeley; all other design projects are from Arts et Metiers.
7
Design projects
3
Featured data projects
Featured Design
Selected product case studies
Featured Data
Applied ML and forecasting work
About
Bridging engineering and product narrative
I work across research, CAD, prototyping, and analytics to deliver reliable systems. My background in mechanics helps me evaluate materials and mechanisms, while my data practice turns experiments into measurable insights.
Currently exploring sports engineering, mobility, and forecasting systems that improve safety and performance.
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